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Overview and Principles of Internet Traffic Engineering

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Author Adrian Farrel
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TEAS Working Group                                        A. Farrel, Ed.
Internet-Draft                                        Old Dog Consulting
Obsoletes: 3272 (if approved)                              April 7, 2021
Intended status: Informational
Expires: October 9, 2021

        Overview and Principles of Internet Traffic Engineering


   This document describes the principles of traffic engineering (TE) in
   the Internet.  The document is intended to promote better
   understanding of the issues surrounding traffic engineering in IP
   networks and the networks that support IP networking, and to provide
   a common basis for the development of traffic engineering
   capabilities for the Internet.  The principles, architectures, and
   methodologies for performance evaluation and performance optimization
   of operational networks are also discussed.

   This work was first published as RFC 3272 in May 2002.  This document
   obsoletes RFC 3272 by making a complete update to bring the text in
   line with best current practices for Internet traffic engineering and
   to include references to the latest relevant work in the IETF.

Status of This Memo

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   provisions of BCP 78 and BCP 79.

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   This Internet-Draft will expire on October 9, 2021.

Copyright Notice

   Copyright (c) 2021 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

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   ( in effect on the date of
   publication of this document.  Please review these documents
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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   4
     1.1.  What is Internet Traffic Engineering? . . . . . . . . . .   4
     1.2.  Components of Traffic Engineering . . . . . . . . . . . .   6
     1.3.  Scope . . . . . . . . . . . . . . . . . . . . . . . . . .   8
     1.4.  Terminology . . . . . . . . . . . . . . . . . . . . . . .   8
   2.  Background  . . . . . . . . . . . . . . . . . . . . . . . . .  11
     2.1.  Context of Internet Traffic Engineering . . . . . . . . .  11
     2.2.  Network Domain Context  . . . . . . . . . . . . . . . . .  12
     2.3.  Problem Context . . . . . . . . . . . . . . . . . . . . .  14
       2.3.1.  Congestion and its Ramifications  . . . . . . . . . .  15
     2.4.  Solution Context  . . . . . . . . . . . . . . . . . . . .  16
       2.4.1.  Combating the Congestion Problem  . . . . . . . . . .  18
     2.5.  Implementation and Operational Context  . . . . . . . . .  21
   3.  Traffic Engineering Process Models  . . . . . . . . . . . . .  21
     3.1.  Components of the Traffic Engineering Process Model . . .  22
   4.  Review of TE Techniques . . . . . . . . . . . . . . . . . . .  22
     4.1.  Overview of IETF Projects Related to Traffic Engineering   23
       4.1.1.  Constraint-Based Routing  . . . . . . . . . . . . . .  23
       4.1.2.  Integrated Services . . . . . . . . . . . . . . . . .  25
       4.1.3.  RSVP  . . . . . . . . . . . . . . . . . . . . . . . .  25
       4.1.4.  Differentiated Services . . . . . . . . . . . . . . .  26
       4.1.5.  QUIC  . . . . . . . . . . . . . . . . . . . . . . . .  27
       4.1.6.  Multiprotocol Label Switching (MPLS)  . . . . . . . .  28
       4.1.7.  Generalized MPLS (GMPLS)  . . . . . . . . . . . . . .  29
       4.1.8.  IP Performance Metrics  . . . . . . . . . . . . . . .  29
       4.1.9.  Flow Measurement  . . . . . . . . . . . . . . . . . .  30
       4.1.10. Endpoint Congestion Management  . . . . . . . . . . .  30
       4.1.11. TE Extensions to the IGPs . . . . . . . . . . . . . .  31
       4.1.12. Link-State BGP  . . . . . . . . . . . . . . . . . . .  31
       4.1.13. Path Computation Element  . . . . . . . . . . . . . .  32
       4.1.14. Multi-Layer Traffic Engineering . . . . . . . . . . .  32
       4.1.15. Application-Layer Traffic Optimization  . . . . . . .  33
       4.1.16. Segment Routing with MPLS Encapsulation (SR-MPLS) . .  34
       4.1.17. Network Virtualization and Abstraction  . . . . . . .  36
       4.1.18. Network Slicing . . . . . . . . . . . . . . . . . . .  37
       4.1.19. Deterministic Networking  . . . . . . . . . . . . . .  38

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       4.1.20. Network TE State Definition and Presentation  . . . .  38
       4.1.21. System Management and Control Interfaces  . . . . . .  39
     4.2.  Content Distribution  . . . . . . . . . . . . . . . . . .  39
   5.  Taxonomy of Traffic Engineering Systems . . . . . . . . . . .  40
     5.1.  Time-Dependent Versus State-Dependent Versus Event-
           Dependent . . . . . . . . . . . . . . . . . . . . . . . .  40
     5.2.  Offline Versus Online . . . . . . . . . . . . . . . . . .  42
     5.3.  Centralized Versus Distributed  . . . . . . . . . . . . .  42
       5.3.1.  Hybrid Systems  . . . . . . . . . . . . . . . . . . .  42
       5.3.2.  Considerations for Software Defined Networking  . . .  43
     5.4.  Local Versus Global . . . . . . . . . . . . . . . . . . .  44
     5.5.  Prescriptive Versus Descriptive . . . . . . . . . . . . .  44
       5.5.1.  Intent-Based Networking . . . . . . . . . . . . . . .  44
     5.6.  Open-Loop Versus Closed-Loop  . . . . . . . . . . . . . .  45
     5.7.  Tactical versus Strategic . . . . . . . . . . . . . . . .  46
   6.  Recommendations for Internet Traffic Engineering  . . . . . .  46
     6.1.  Generic Non-functional Recommendations  . . . . . . . . .  46
     6.2.  Routing Recommendations . . . . . . . . . . . . . . . . .  48
     6.3.  Traffic Mapping Recommendations . . . . . . . . . . . . .  51
     6.4.  Measurement Recommendations . . . . . . . . . . . . . . .  51
     6.5.  Network Survivability . . . . . . . . . . . . . . . . . .  52
       6.5.1.  Survivability in MPLS Based Networks  . . . . . . . .  54
       6.5.2.  Protection Options  . . . . . . . . . . . . . . . . .  55
     6.6.  Traffic Engineering in Diffserv Environments  . . . . . .  56
     6.7.  Network Controllability . . . . . . . . . . . . . . . . .  58
   7.  Inter-Domain Considerations . . . . . . . . . . . . . . . . .  58
   8.  Overview of Contemporary TE Practices in Operational IP
       Networks  . . . . . . . . . . . . . . . . . . . . . . . . . .  60
   9.  Security Considerations . . . . . . . . . . . . . . . . . . .  63
   10. IANA Considerations . . . . . . . . . . . . . . . . . . . . .  63
   11. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . .  63
   12. Contributors  . . . . . . . . . . . . . . . . . . . . . . . .  65
   13. Informative References  . . . . . . . . . . . . . . . . . . .  66
   Appendix A.  Historic Overview  . . . . . . . . . . . . . . . . .  78
     A.1.  Traffic Engineering in Classical Telephone Networks . . .  78
     A.2.  Evolution of Traffic Engineering in Packet Networks . . .  80
       A.2.1.  Adaptive Routing in the ARPANET . . . . . . . . . . .  80
       A.2.2.  Dynamic Routing in the Internet . . . . . . . . . . .  81
       A.2.3.  ToS Routing . . . . . . . . . . . . . . . . . . . . .  82
       A.2.4.  Equal Cost Multi-Path . . . . . . . . . . . . . . . .  82
       A.2.5.  Nimrod  . . . . . . . . . . . . . . . . . . . . . . .  83
     A.3.  Development of Internet Traffic Engineering . . . . . . .  83
       A.3.1.  Overlay Model . . . . . . . . . . . . . . . . . . . .  83
   Appendix B.  Overview of Traffic Engineering Related Work in
                Other SDOs . . . . . . . . . . . . . . . . . . . . .  83
     B.1.  Overview of ITU Activities Related to Traffic Engineering  84
   Appendix C.  Summary of Changes Since RFC 3272  . . . . . . . . .  85
     C.1.  RFC 3272  . . . . . . . . . . . . . . . . . . . . . . . .  85

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     C.2.  This Document . . . . . . . . . . . . . . . . . . . . . .  88
   Author's Address  . . . . . . . . . . . . . . . . . . . . . . . .  91

1.  Introduction

   This document describes the principles of Internet traffic
   engineering (TE).  The objective of the document is to articulate the
   general issues and principles for Internet traffic engineering, and
   where appropriate to provide recommendations, guidelines, and options
   for the development of online and offline Internet traffic
   engineering capabilities and support systems.

   This document provides a terminology and taxonomy for describing and
   understanding common Internet traffic engineering concepts.

   Even though Internet traffic engineering is most effective when
   applied end-to-end, the focus of this document is traffic engineering
   within a given domain (such as an autonomous system).  However,
   because a preponderance of Internet traffic tends to originate in one
   autonomous system and terminate in another, this document also
   provides an overview of aspects pertaining to inter-domain traffic

   This work was first published as [RFC3272] in May 2002.  This
   document obsoletes [RFC3272] by making a complete update to bring the
   text in line with best current practices for Internet traffic
   engineering and to include references to the latest relevant work in
   the IETF.  It is worth noting around three fifths of the RFCs
   referenced in this document post-date the publication of RFC 3272.
   Appendix C provides a summary of changes between RFC 3272 and this

1.1.  What is Internet Traffic Engineering?

   One of the most significant functions performed by the Internet is
   the routing of traffic from ingress nodes to egress nodes.
   Therefore, one of the most distinctive functions performed by
   Internet traffic engineering is the control and optimization of the
   routing function, to steer traffic through the network.

   Internet traffic engineering is defined as that aspect of Internet
   network engineering dealing with the issues of performance evaluation
   and performance optimization of operational IP networks.  Traffic
   engineering encompasses the application of technology and scientific
   principles to the measurement, characterization, modeling, and
   control of Internet traffic [RFC2702], [AWD2].

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   It is the performance of the network as seen by end users of network
   services that is paramount.  The characteristics visible to end users
   are the emergent properties of the network, which are the
   characteristics of the network when viewed as a whole.  A central
   goal of the service provider, therefore, is to enhance the emergent
   properties of the network while taking economic considerations into
   account.  This is accomplished by addressing traffic oriented
   performance requirements while utilizing network resources
   economically and reliably.  Traffic oriented performance measures
   include delay, delay variation, packet loss, and throughput.

   Internet traffic engineering responds to network events.  Aspects of
   capacity management respond at intervals ranging from days to years.
   Routing control functions operate at intervals ranging from
   milliseconds to days.  Packet level processing functions operate at
   very fine levels of temporal resolution, ranging from picoseconds to
   milliseconds while reacting to the real-time statistical behavior of

   Thus, the optimization aspects of traffic engineering can be viewed
   from a control perspective, and can be both pro-active and reactive.
   In the pro-active case, the traffic engineering control system takes
   preventive action to protect against predicted unfavorable future
   network states, for example, by engineering backup paths.  It may
   also take action that will lead to a more desirable future network
   state.  In the reactive case, the control system responds to correct
   issues and adapt to network events, such as routing after failure.

   Another important objective of Internet traffic engineering is to
   facilitate reliable network operations [RFC2702].  Reliable network
   operations can be facilitated by providing mechanisms that enhance
   network integrity and by embracing policies emphasizing network
   survivability.  This reduces the vulnerability of services to outages
   arising from errors, faults, and failures occurring within the
   network infrastructure.

   The optimization aspects of traffic engineering can be achieved
   through capacity management and traffic management.  In this
   document, capacity management includes capacity planning, routing
   control, and resource management.  Network resources of particular
   interest include link bandwidth, buffer space, and computational
   resources.  In this document, traffic management includes:

   1.  nodal traffic control functions such as traffic conditioning,
       queue management, scheduling

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   2.  other functions that regulate traffic flow through the network or
       that arbitrate access to network resources between different
       packets or between different traffic streams.

   One major challenge of Internet traffic engineering is the
   realization of automated control capabilities that adapt quickly and
   cost effectively to significant changes in network state, while still
   maintaining stability of the network.  Performance evaluation can
   assess the effectiveness of traffic engineering methods, and the
   results of this evaluation can be used to identify existing problems,
   guide network re-optimization, and aid in the prediction of potential
   future problems.  However, this process can also be time consuming
   and may not be suitable to act on short-lived changes in the network.

   Performance evaluation can be achieved in many different ways.  The
   most notable techniques include analytical methods, simulation, and
   empirical methods based on measurements.

   Traffic engineering comes in two flavors: either a background process
   that constantly monitors traffic and optimizes the use of resources
   to improve performance; or a form of a pre-planned optimized traffic
   distribution that is considered optimal.  In the later case, any
   deviation from the optimum distribution (e.g., caused by a fiber cut)
   is reverted upon repair without further optimization.  However, this
   form of traffic engineering relies upon the notion that the planned
   state of the network is optimal.  Hence, in such a mode there are two
   levels of traffic engineering: the TE-planning task to enable optimum
   traffic distribution, and the routing task keeping traffic flows
   attached to the pre-planned distribution.

   As a general rule, traffic engineering concepts and mechanisms must
   be sufficiently specific and well-defined to address known
   requirements, but simultaneously flexible and extensible to
   accommodate unforeseen future demands.

1.2.  Components of Traffic Engineering

   As mentioned in Section 1.1, Internet traffic engineering provides
   performance optimization of operational IP networks while utilizing
   network resources economically and reliably.  Such optimization is
   supported at the control/controller level and within the data/
   forwarding plane.

   The key elements required in any TE solution are as follows:

   1.  Policy

   2.  Path steering

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   3.  Resource management

   Some TE solutions rely on these elements to a lesser or greater
   extent.  Debate remains about whether a solution can truly be called
   traffic engineering if it does not include all of these elements.
   For the sake of this document, we assert that all TE solutions must
   include some aspects of all of these elements.  Other solutions can
   be classed as "partial TE" and also fall in scope of this document.

   Policy allows for the selection of next hops and paths based on
   information beyond basic reachability.  Early definitions of routing
   policy, e.g., [RFC1102] and [RFC1104], discuss routing policy being
   applied to restrict access to network resources at an aggregate
   level.  BGP is an example of a commonly used mechanism for applying
   such policies, see [RFC4271] and [RFC8955].  In the traffic
   engineering context, policy decisions are made within the control
   plane or by controllers, and govern the selection of paths.  Examples
   can be found in [RFC4655] and [RFC5394].  Standard TE solutions may
   cover the mechanisms to distribute and/or enforce polices, but
   specific policy definition is generally unspecified.

   Path steering is the ability to forward packets using more
   information than just knowledge of the next hop.  Examples of path
   steering include IPv4 source routes [RFC0791], RSVP-TE explicit
   routes [RFC3209], and Segment Routing [RFC8402].  Path steering for
   TE can be supported via control plane protocols, by encoding in the
   data plane headers, or by a combination of the two.  This includes
   when control is provided by a controller using a southbound (i.e.,
   controller to router) control protocol.

   Resource management provides resource aware control and forwarding.
   Examples of resources are bandwidth, buffers, and queues, all of
   which can be managed to control loss and latency.

      Resource reservation is the control aspect of resource management.
      It provides for domain-wide consensus about which network
      resources are used by a particular flow.  This determination may
      be made at a very course or very fine level.  Note that this
      consensus exists at the network control or controller level, not
      within the data plane.  It may be composed purely of accounting/
      bookkeeping, but it typically includes an ability to admit,
      reject, or reclassify a flow based on policy.  Such accounting can
      be done based on any combination of a static understanding of
      resource requirements, and the use of dynamic mechanisms to
      collect requirements (e.g., via [RFC3209]) and resource
      availability (e.g., via [RFC4203]).

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      Resource allocation is the data plane aspect of resource
      management.  It provides for the allocation of specific node and
      link resources to specific flows.  Example resources include
      buffers, policing, and rate-shaping mechanisms that are typically
      supported via queuing.  It also includes the matching of a flow
      (i.e., flow classification) to a particular set of allocated
      resources.  The method of flow classification and granularity of
      resource management is technology specific.  Examples include
      Diffserv with dropping and remarking [RFC4594], MPLS-TE [RFC3209],
      and GMPLS based label switched paths [RFC3945], as well as
      controller-based solutions [RFC8453].  This level of resource
      control, while optional, is important in networks that wish to
      support congestion management policies to control or regulate the
      offered traffic to deliver different levels of service and
      alleviate congestion problems, or those networks that wish to
      control latencies experienced by specific traffic flows.

1.3.  Scope

   The scope of this document is intra-domain traffic engineering.  That
   is, traffic engineering within a given autonomous system in the
   Internet.  This document discusses concepts pertaining to intra-
   domain traffic control, including such issues as routing control,
   micro and macro resource allocation, and the control coordination
   problems that arise consequently.

   This document describes and characterizes techniques already in use
   or in advanced development for Internet traffic engineering.  The way
   these techniques fit together is discussed and scenarios in which
   they are useful will be identified.

   Although the emphasis in this document is on intra-domain traffic
   engineering, in Section 7, an overview of the high level
   considerations pertaining to inter-domain traffic engineering will be
   provided.  Inter-domain Internet traffic engineering is crucial to
   the performance enhancement of the global Internet infrastructure.

   Whenever possible, relevant requirements from existing IETF documents
   and other sources are incorporated by reference.

1.4.  Terminology

   This section provides terminology which is useful for Internet
   traffic engineering.  The definitions presented apply to this
   document.  These terms may have other meanings elsewhere.

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   Busy hour:  A one hour period within a specified interval of time
      (typically 24 hours) in which the traffic load in a network or
      sub-network is greatest.

   Congestion:  A state of a network resource in which the traffic
      incident on the resource exceeds its output capacity over an
      interval of time.

   Congestion avoidance:  An approach to congestion management that
      attempts to obviate the occurrence of congestion.

   Congestion control:  An approach to congestion management that
      attempts to remedy congestion problems that have already occurred.

   Constraint-based routing:  A class of routing protocols that take
      specified traffic attributes, network constraints, and policy
      constraints into account when making routing decisions.
      Constraint-based routing is applicable to traffic aggregates as
      well as flows.  It is a generalization of QoS routing.

   Demand side congestion management:  A congestion management scheme
      that addresses congestion problems by regulating or conditioning
      offered load.

   Effective bandwidth:  The minimum amount of bandwidth that can be
      assigned to a flow or traffic aggregate in order to deliver
      'acceptable service quality' to the flow or traffic aggregate.

   Hot-spot:  A network element or subsystem which is in a state of

   Inter-domain traffic:  Traffic that originates in one Autonomous
      system and terminates in another.

   Metric:  A parameter defined in terms of standard units of

   Measurement methodology:  A repeatable measurement technique used to
      derive one or more metrics of interest.

   Network survivability:  The capability to provide a prescribed level
      of QoS for existing services after a given number of failures
      occur within the network.

   Offline traffic engineering:  A traffic engineering system that
      exists outside of the network.

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   Online traffic engineering:  A traffic engineering system that exists
      within the network, typically implemented on or as adjuncts to
      operational network elements.

   Performance measures:  Metrics that provide quantitative or
      qualitative measures of the performance of systems or subsystems
      of interest.

   Performance metric:  A performance parameter defined in terms of
      standard units of measurement.

   Provisioning:  The process of assigning or configuring network
      resources to meet certain requests.

   QoS routing:  Class of routing systems that selects paths to be used
      by a flow based on the QoS requirements of the flow.

   Service Level Agreement (SLA):  A contract between a provider and a
      customer that guarantees specific levels of performance and
      reliability at a certain cost.

   Service Level Objective (SLO):  A key element of an SLA between a
      provider and a customer.  SLOs are agreed upon as a means of
      measuring the performance of the Service Provider and are outlined
      as a way of avoiding disputes between the two parties based on

   Stability:  An operational state in which a network does not
      oscillate in a disruptive manner from one mode to another mode.

   Supply-side congestion management:  A congestion management scheme
      that provisions additional network resources to address existing
      and/or anticipated congestion problems.

   Traffic characteristic:  A description of the temporal behavior or a
      description of the attributes of a given traffic flow or traffic

   Traffic engineering system:  A collection of objects, mechanisms, and
      protocols that are used together to accomplish traffic engineering

   Traffic flow:  A stream of packets between two end-points that can be
      characterized in a certain way.  A micro-flow has a more specific
      definition A micro-flow is a stream of packets with the same
      source and destination addresses, source and destination ports,
      and protocol ID.

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   Traffic matrix:  A representation of the traffic demand between a set
      of origin and destination abstract nodes.  An abstract node can
      consist of one or more network elements.

   Traffic monitoring:  The process of observing traffic characteristics
      at a given point in a network and collecting the traffic
      information for analysis and further action.

   Traffic trunk:  An aggregation of traffic flows belonging to the same
      class which are forwarded through a common path.  A traffic trunk
      may be characterized by an ingress and egress node, and a set of
      attributes which determine its behavioral characteristics and
      requirements from the network.

2.  Background

   The Internet must convey IP packets from ingress nodes to egress
   nodes efficiently, expeditiously, and economically.  Furthermore, in
   a multiclass service environment (e.g., Diffserv capable networks -
   see Section 4.1.4), the resource sharing parameters of the network
   must be appropriately determined and configured according to
   prevailing policies and service models to resolve resource contention
   issues arising from mutual interference between packets traversing
   through the network.  Thus, consideration must be given to resolving
   competition for network resources between traffic streams belonging
   to the same service class (intra-class contention resolution) and
   traffic streams belonging to different classes (inter-class
   contention resolution).

2.1.  Context of Internet Traffic Engineering

   The context of Internet traffic engineering includes:

   1.  A network domain context that defines the scope under
       consideration, and in particular the situations in which the
       traffic engineering problems occur.  The network domain context
       includes network structure, network policies, network
       characteristics, network constraints, network quality attributes,
       and network optimization criteria.

   2.  A problem context defining the general and concrete issues that
       traffic engineering addresses.  The problem context includes
       identification, abstraction of relevant features, representation,
       formulation, specification of the requirements on the solution
       space, and specification of the desirable features of acceptable

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   3.  A solution context suggesting how to address the issues
       identified by the problem context.  The solution context includes
       analysis, evaluation of alternatives, prescription, and

   4.  An implementation and operational context in which the solutions
       are instantiated.  The implementation and operational context
       includes planning, organization, and execution.

   The context of Internet traffic engineering and the different problem
   scenarios are discussed in the following subsections.

2.2.  Network Domain Context

   IP networks range in size from small clusters of routers situated
   within a given location, to thousands of interconnected routers,
   switches, and other components distributed all over the world.

   At the most basic level of abstraction, an IP network can be
   represented as a distributed dynamic system consisting of:

   o  a set of interconnected resources which provide transport services
      for IP traffic subject to certain constraints

   o  a demand system representing the offered load to be transported
      through the network

   o  a response system consisting of network processes, protocols, and
      related mechanisms which facilitate the movement of traffic
      through the network (see also [AWD2]).

   The network elements and resources may have specific characteristics
   restricting the manner in which the traffic demand is handled.
   Additionally, network resources may be equipped with traffic control
   mechanisms managing the way in which the demand is serviced.  Traffic
   control mechanisms may be used to:

   o  control packet processing activities within a given resource

   o  arbitrate contention for access to the resource by different

   o  regulate traffic behavior through the resource.

   A configuration management and provisioning system may allow the
   settings of the traffic control mechanisms to be manipulated by
   external or internal entities in order to exercise control over the

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   way in which the network elements respond to internal and external

   The details of how the network carries packets are specified in the
   policies of the network administrators and are installed through
   network configuration management and policy based provisioning
   systems.  Generally, the types of service provided by the network
   also depend upon the technology and characteristics of the network
   elements and protocols, the prevailing service and utility models,
   and the ability of the network administrators to translate policies
   into network configurations.

   Internet networks have three significant characteristics:

   o  they provide real-time services

   o  they are mission critical

   o  their operating environments are very dynamic.

   The dynamic characteristics of IP and IP/MPLS networks can be
   attributed in part to fluctuations in demand, to the interaction
   between various network protocols and processes, to the rapid
   evolution of the infrastructure which demands the constant inclusion
   of new technologies and new network elements, and to transient and
   persistent faults which occur within the system.

   Packets contend for the use of network resources as they are conveyed
   through the network.  A network resource is considered to be
   congested if, for an interval of time, the arrival rate of packets
   exceed the output capacity of the resource.  Congestion may result in
   some of the arriving packets being delayed or even dropped.

   Congestion increases transit delay, delay variation, may lead to
   packet loss, and reduces the predictability of network services.
   Clearly, congestion is highly undesirable.  Combating congestion at a
   reasonable cost is a major objective of Internet traffic engineering.

   Efficient sharing of network resources by multiple traffic streams is
   a basic operational premise for the Internet.  A fundamental
   challenge in network operation is to increase resource utilization
   while minimizing the possibility of congestion.

   The Internet has to function in the presence of different classes of
   traffic with different service requirements.  RFC 2475 provides an
   architecture for Differentiated Services (Diffserv) and makes this
   requirement clear [RFC2475].  The RFC allows packets to be grouped
   into behavior aggregates such that each aggregate has a common set of

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   behavioral characteristics or a common set of delivery requirements.
   Delivery requirements of a specific set of packets may be specified
   explicitly or implicitly.  Two of the most important traffic delivery
   requirements are capacity constraints and QoS constraints.

   Capacity constraints can be expressed statistically as peak rates,
   mean rates, burst sizes, or as some deterministic notion of effective
   bandwidth.  QoS requirements can be expressed in terms of:

   o  integrity constraints such as packet loss

   o  temporal constraints such as timing restrictions for the delivery
      of each packet (delay) and timing restrictions for the delivery of
      consecutive packets belonging to the same traffic stream (delay

2.3.  Problem Context

   There are several large problems associated with operating a network
   described in the previous section.  This section analyzes the problem
   context in relation to traffic engineering.  The identification,
   abstraction, representation, and measurement of network features
   relevant to traffic engineering are significant issues.

   A particular challenge is to formulate the problems that traffic
   engineering attempts to solve.  For example:

   o  how to identify the requirements on the solution space

   o  how to specify the desirable features of solutions

   o  how to actually solve the problems

   o  how to measure and characterize the effectiveness of solutions.

   Another class of problems is how to measure and estimate relevant
   network state parameters.  Effective traffic engineering relies on a
   good estimate of the offered traffic load as well as a view of the
   underlying topology and associated resource constraints.  A network-
   wide view of the topology is also a must for offline planning.

   Still another class of problem is how to characterize the state of
   the network and how to evaluate its performance.  The performance
   evaluation problem is two-fold: one aspect relates to the evaluation
   of the system-level performance of the network; the other aspect
   relates to the evaluation of resource-level performance, which
   restricts attention to the performance analysis of individual network

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   In this document, we refer to the system-level characteristics of the
   network as the "macro-states" and the resource-level characteristics
   as the "micro-states."  The system-level characteristics are also
   known as the emergent properties of the network.  Correspondingly, we
   refer to the traffic engineering schemes dealing with network
   performance optimization at the systems level as "macro-TE" and the
   schemes that optimize at the individual resource level as "micro-TE."
   Under certain circumstances, the system-level performance can be
   derived from the resource-level performance using appropriate rules
   of composition, depending upon the particular performance measures of

   Another fundamental class of problem concerns how to effectively
   optimize network performance.  Performance optimization may entail
   translating solutions for specific traffic engineering problems into
   network configurations.  Optimization may also entail some degree of
   resource management control, routing control, and capacity

2.3.1.  Congestion and its Ramifications

   Congestion is one of the most significant problems in an operational
   IP context.  A network element is said to be congested if it
   experiences sustained overload over an interval of time.  Congestion
   almost always results in degradation of service quality to end users.
   Congestion control schemes can include demand-side policies and
   supply-side policies.  Demand-side policies may restrict access to
   congested resources or dynamically regulate the demand to alleviate
   the overload situation.  Supply-side policies may expand or augment
   network capacity to better accommodate offered traffic.  Supply-side
   policies may also re-allocate network resources by redistributing
   traffic over the infrastructure.  Traffic redistribution and resource
   re-allocation serve to increase the 'effective capacity' of the

   The emphasis of this document is primarily on congestion management
   schemes falling within the scope of the network, rather than on
   congestion management systems dependent upon sensitivity and
   adaptivity from end-systems.  That is, the aspects that are
   considered in this document with respect to congestion management are
   those solutions that can be provided by control entities operating on
   the network and by the actions of network administrators and network
   operations systems.

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2.4.  Solution Context

   The solution context for Internet traffic engineering involves
   analysis, evaluation of alternatives, and choice between alternative
   courses of action.  Generally the solution context is based on making
   reasonable inferences about the current or future state of the
   network, and making decisions that may involve a preference between
   alternative sets of action.  More specifically, the solution context
   demands reasonable estimates of traffic workload, characterization of
   network state, derivation of solutions which may be implicitly or
   explicitly formulated, and possibly instantiating a set of control
   actions.  Control actions may involve the manipulation of parameters
   associated with routing, control over tactical capacity acquisition,
   and control over the traffic management functions.

   The following list of instruments may be applicable to the solution
   context of Internet traffic engineering.

   o  A set of policies, objectives, and requirements (which may be
      context dependent) for network performance evaluation and
      performance optimization.

   o  A collection of online and possibly offline tools and mechanisms
      for measurement, characterization, modeling, and control traffic,
      and control over the placement and allocation of network
      resources, as well as control over the mapping or distribution of
      traffic onto the infrastructure.

   o  A set of constraints on the operating environment, the network
      protocols, and the traffic engineering system itself.

   o  A set of quantitative and qualitative techniques and methodologies
      for abstracting, formulating, and solving traffic engineering

   o  A set of administrative control parameters which may be
      manipulated through a Configuration Management (CM) system.  The
      CM system itself may include a configuration control subsystem, a
      configuration repository, a configuration accounting subsystem,
      and a configuration auditing subsystem.

   o  A set of guidelines for network performance evaluation,
      performance optimization, and performance improvement.

   Determining traffic characteristics through measurement or estimation
   is very useful within the realm the traffic engineering solution
   space.  Traffic estimates can be derived from customer subscription
   information, traffic projections, traffic models, and from actual

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   measurements.  The measurements may be performed at different levels,
   e.g., at the traffic-aggregate level or at the flow level.
   Measurements at the flow level or on small traffic aggregates may be
   performed at edge nodes, when traffic enters and leaves the network.
   Measurements for large traffic-aggregates may be performed within the
   core of the network.

   To conduct performance studies and to support planning of existing
   and future networks, a routing analysis may be performed to determine
   the paths the routing protocols will choose for various traffic
   demands, and to ascertain the utilization of network resources as
   traffic is routed through the network.  Routing analysis captures the
   selection of paths through the network, the assignment of traffic
   across multiple feasible routes, and the multiplexing of IP traffic
   over traffic trunks (if such constructs exist) and over the
   underlying network infrastructure.  A model of network topology is
   necessary to perform routing analysis.  A network topology model may
   be extracted from:

   o  network architecture documents

   o  network designs

   o  information contained in router configuration files

   o  routing databases

   o  routing tables

   o  automated tools that discover and collate network topology

   Topology information may also be derived from servers that monitor
   network state, and from servers that perform provisioning functions.

   Routing in operational IP networks can be administratively controlled
   at various levels of abstraction including the manipulation of BGP
   attributes and interior gateway protocol (IGP) metrics.  For path
   oriented technologies such as MPLS, routing can be further controlled
   by the manipulation of relevant traffic engineering parameters,
   resource parameters, and administrative policy constraints.  Within
   the context of MPLS, the path of an explicitly routed label switched
   path (LSP) can be computed and established in various ways including:

   o  manually

   o  automatically, online using constraint-based routing processes
      implemented on label switching routers

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   o  automatically, offline using constraint-based routing entities
      implemented on external traffic engineering support systems.

2.4.1.  Combating the Congestion Problem

   Minimizing congestion is a significant aspect of Internet traffic
   engineering.  This subsection gives an overview of the general
   approaches that have been used or proposed to combat congestion.

   Congestion management policies can be categorized based upon the
   following criteria (see [YARE95] for a more detailed taxonomy of
   congestion control schemes):

   1.  Congestion Management based on Response Time Scales

       *  Long (weeks to months): Expanding network capacity by adding
          new equipment, routers, and links takes time and is
          comparatively costly.  Capacity planning needs to take this
          into consideration.  Network capacity is expanded based on
          estimates or forecasts of future traffic development and
          traffic distribution.  These upgrades are typically carried
          out over weeks or months, or maybe even years.

       *  Medium (minutes to days): Several control policies fall within
          the medium timescale category.  Examples include:

          a.  Adjusting routing protocol parameters to route traffic
              away or towards certain segments of the network.

          b.  Setting up or adjusting explicitly routed LSPs in MPLS
              networks to route traffic trunks away from possibly
              congested resources or toward possibly more favorable

          c.  Re-configuring the logical topology of the network to make
              it correlate more closely with the spatial traffic
              distribution using, for example, an underlying path-
              oriented technology such as MPLS LSPs or optical channel

          Many of these adaptive schemes rely on measurement systems.  A
          measurement system monitors changes in traffic distribution,
          traffic loads, and network resource utilization and then
          provides feedback to the online or offline traffic engineering
          mechanisms and tools so that they can trigger control actions
          within the network.  The traffic engineering mechanisms and
          tools can be implemented in a distributed or centralized
          fashion.  A centralized scheme may have global visibility into

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          the network state and may produce more optimal solutions.
          However, centralized schemes are prone to single points of
          failure and may not scale as well as distributed schemes.
          Moreover, the information utilized by a centralized scheme may
          be stale and might not reflect the actual state of the
          network.  It is not an objective of this document to make a
          recommendation between distributed and centralized schemes:
          that is a choice that network administrators must make based
          on their specific needs.

       *  Short (picoseconds to minutes): This category includes packet
          level processing functions and events that are recorded on the
          order of several round trip times.  It also includes router
          mechanisms such as passive and active buffer management.  All
          of these mechanisms are used to control congestion or signal
          congestion to end systems so that they can adaptively regulate
          the rate at which traffic is injected into the network.  One
          of the most popular active queue management schemes,
          especially for TCP traffic, is Random Early Detection (RED)
          [FLJA93].  During congestion (but before the queue is filled),
          the RED scheme chooses arriving packets to "mark" according to
          a probabilistic algorithm which takes into account the average
          queue size.  A router that does not utilize explicit
          congestion notification (ECN) [FLOY94] can simply drop marked
          packets to alleviate congestion and implicitly notify the
          receiver about the congestion.  On the other hand, if the
          router supports ECN, it can set the ECN field in the packet
          header.  Several variations of RED have been proposed to
          support different drop precedence levels in multi-class
          environments [RFC2597].  RED provides congestion avoidance
          which is not worse than traditional Tail-Drop (TD) queue
          management (drop arriving packets only when the queue is
          full).  Importantly, RED reduces the possibility of global
          synchronization where retransmission burst become synchronized
          across the whole network, and improves fairness among
          different TCP sessions.  However, RED by itself cannot prevent
          congestion and unfairness caused by sources unresponsive to
          RED, e.g., UDP traffic and some misbehaved greedy connections.
          Other schemes have been proposed to improve the performance
          and fairness in the presence of unresponsive traffic.  Some of
          those schemes (such as Longest Queue Drop (LQD) and Dynamic
          Soft Partitioning with Random Drop (RND) [SLDC98]) were
          proposed as theoretical frameworks and are typically not
          available in existing commercial products.

   2.  Congestion Management: Reactive Versus Preventive Schemes

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       *  Reactive: Reactive (recovery) congestion management policies
          react to existing congestion problems.  All the policies
          described above for the long and medium time scales can be
          categorized as being reactive.  They are based on monitoring
          and identifying congestion problems that exist in the network,
          and on the initiation of relevant actions to ease a situation.

       *  Preventive: Preventive (predictive/avoidance) policies take
          proactive action to prevent congestion based on estimates and
          predictions of future congestion problems.  Some of the
          policies described for the long and medium time scales fall
          into this category.  Preventive policies do not necessarily
          respond immediately to existing congestion problems.  Instead,
          forecasts of traffic demand and workload distribution are
          considered, and action may be taken to prevent potential
          future congestion problems.  The schemes described for the
          short time scale can also be used for congestion avoidance
          because dropping or marking packets before queues actually
          overflow would trigger corresponding TCP sources to slow down.

   3.  Congestion Management: Supply-Side Versus Demand-Side Schemes

       *  Supply-side: Supply-side congestion management policies
          increase the effective capacity available to traffic in order
          to control or reduce congestion.  This can be accomplished by
          increasing capacity or by balancing distribution of traffic
          over the network.  Capacity planning aims to provide a
          physical topology and associated link bandwidths that match or
          exceed estimated traffic workload and traffic distribution
          subject to traffic forecasts and budgetary or other
          constraints.  If the actual traffic distribution does not fit
          the topology derived from capacity panning, then the traffic
          can be mapped onto the topology by using routing control
          mechanisms, by applying path oriented technologies (e.g., MPLS
          LSPs and optical channel trails) to modify the logical
          topology, or by employing some other load redistribution

       *  Demand-side: Demand-side congestion management policies
          control or regulate the offered traffic to alleviate
          congestion problems.  For example, some of the short time
          scale mechanisms described earlier as well as policing and
          rate-shaping mechanisms attempt to regulate the offered load
          in various ways.

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2.5.  Implementation and Operational Context

   The operational context of Internet traffic engineering is
   characterized by constant changes that occur at multiple levels of
   abstraction.  The implementation context demands effective planning,
   organization, and execution.  The planning aspects may involve
   determining prior sets of actions to achieve desired objectives.
   Organizing involves arranging and assigning responsibility to the
   various components of the traffic engineering system and coordinating
   the activities to accomplish the desired TE objectives.  Execution
   involves measuring and applying corrective or perfective actions to
   attain and maintain desired TE goals.

3.  Traffic Engineering Process Models

   This section describes a generic process model that captures the
   high-level practical aspects of Internet traffic engineering in an
   operational context.  The process model is described as a sequence of
   actions that must be carried out to optimize the performance of an
   operational network (see also [RFC2702], [AWD2]).  This process model
   may be enacted explicitly or implicitly, by a software process or by
   a human.

   The traffic engineering process model is iterative [AWD2].  The four
   phases of the process model described below are repeated as a
   continual sequence.

   o  Define the relevant control policies that govern the operation of
      the network.

   o  Acquire measurement data from the operational network.

   o  Analyze the network state and characterize the traffic workload.
      Proactive analysis identifies potential problems that could
      manifest in the future.  Reactive analysis identifies existing
      problems and determines their causes.

   o  Optimize the performance of the network.  This involves a decision
      process which selects and implements a set of actions from a set
      of alternatives given the results of the three previous steps.
      Optimization actions may include the use of techniques to control
      the offered traffic and to control the distribution of traffic
      across the network.

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3.1.  Components of the Traffic Engineering Process Model

   The key components of the traffic engineering process model are as

   1.  Measurement is crucial to the traffic engineering function.  The
       operational state of a network can only be conclusively
       determined through measurement.  Measurement is also critical to
       the optimization function because it provides feedback data which
       is used by traffic engineering control subsystems.  This data is
       used to adaptively optimize network performance in response to
       events and stimuli originating within and outside the network.
       Measurement in support of the TE function can occur at different
       levels of abstraction.  For example, measurement can be used to
       derive packet level characteristics, flow level characteristics,
       user or customer level characteristics, traffic aggregate
       characteristics, component level characteristics, and network
       wide characteristics.

   2.  Modeling, analysis, and simulation are important aspects of
       Internet traffic engineering.  Modeling involves constructing an
       abstract or physical representation which depicts relevant
       traffic characteristics and network attributes.  A network model
       is an abstract representation of the network which captures
       relevant network features, attributes, and characteristic.
       Network simulation tools are extremely useful for traffic
       engineering.  Because of the complexity of realistic quantitative
       analysis of network behavior, certain aspects of network
       performance studies can only be conducted effectively using

   3.  Network performance optimization involves resolving network
       issues by transforming such issues into concepts that enable a
       solution, identification of a solution, and implementation of the
       solution.  Network performance optimization can be corrective or
       perfective.  In corrective optimization, the goal is to remedy a
       problem that has occurred or that is incipient.  In perfective
       optimization, the goal is to improve network performance even
       when explicit problems do not exist and are not anticipated.

4.  Review of TE Techniques

   This section briefly reviews different traffic engineering approaches
   proposed and implemented in telecommunications and computer networks
   using IETF protocols and architectures.  The discussion is not
   intended to be comprehensive.  It is primarily intended to illuminate
   existing approaches to traffic engineering in the Internet.  A
   historic overview of traffic engineering in telecommunications

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   networks is provided in Appendix A, while Appendix B describes
   approaches in other standards bodies.

4.1.  Overview of IETF Projects Related to Traffic Engineering

   This subsection reviews a number of IETF activities pertinent to
   Internet traffic engineering.

4.1.1.  Constraint-Based Routing

   Constraint-based routing refers to a class of routing systems that
   compute routes through a network subject to the satisfaction of a set
   of constraints and requirements.  In the most general case,
   constraint-based routing may also seek to optimize overall network
   performance while minimizing costs.

   The constraints and requirements may be imposed by the network itself
   or by administrative policies.  Constraints may include bandwidth,
   hop count, delay, and policy instruments such as resource class
   attributes.  Constraints may also include domain specific attributes
   of certain network technologies and contexts which impose
   restrictions on the solution space of the routing function.  Path
   oriented technologies such as MPLS have made constraint-based routing
   feasible and attractive in public IP networks.

   The concept of constraint-based routing within the context of MPLS
   traffic engineering requirements in IP networks was first described
   in [RFC2702] and led to developments such as MPLS-TE [RFC3209] as
   described in Section 4.1.6.

   Unlike QoS routing (for example, see [RFC2386] and [MA]) which
   generally addresses the issue of routing individual traffic flows to
   satisfy prescribed flow-based QoS requirements subject to network
   resource availability, constraint-based routing is applicable to
   traffic aggregates as well as flows and may be subject to a wide
   variety of constraints which may include policy restrictions.  IGP Flexible Algorithms (Flex-Algos)

   The traditional approach to routing in an IGP network relies on the
   IGPs deriving "shortest paths" over the network based solely on the
   IGP metric assigned to the links.  Such an approach is often limited:
   traffic may tend to converge toward the destination, possibly causing
   congestion; and it is not possible to steer traffic onto paths
   depending on the end-to-end qualities demanded by the applications.

   To overcome this limitation, various sorts of traffic engineering
   have been widely deployed (as described in this document), where the

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   TE component is responsible for computing the path based on
   additionalcmetrics and/or constraints.  Such paths (or tunnels) need
   to be installed in the routers' forwarding tables in addition to, or
   as a replacement for the original paths computed by IGPs.  The main
   drawback of these TE approaches is the additional complexity of
   protocols and management, and the state that may need to be
   maintained within the network.

   IGP flexible algorithms (flex-algos) [I-D.ietf-lsr-flex-algo] allow
   IGPs to construct constraint-based paths over the network by
   computing constraint- based next hops.  The intent of flex-algos is
   to reduce TE complexity by letting an IGP perform some basic TE
   computation capabilities.  Flex-algo includes a set of extensions to
   the IGPs that enable a router to send TLVs that:

   o  describe a set of constraints on the topology

   o  identify calculation-type

   o  describe a metric-type that is to be used to compute the best
      paths through the constrained topology.

   A given combination of calculation-type, metric-type, and constraints
   is known as a "Flexible Algorithm Definition" (or FAD).  A router
   that sends such a set of TLVs also assigns a specific identifier (the
   Flexible Algorithm) to the specified combination of calculation-type,
   metric-type, and constraints.

   There are two use cases for flex-algo: in IP networks
   [I-D.ietf-lsr-ip-flexalgo] and in segment routing networks
   [I-D.ietf-lsr-flex-algo].  In the first case, flex-algo computes
   paths to an IPv4 or IPv6 address, in the second case, flex-algo
   computes paths to a prefix SID (see Section 4.1.16).

   There are many use cases where flex-algo can bring big value, such

   o  Expansion of functionality of IP Performance metrics [RFC5664]
      when points of interest could instantiate specific constraint-
      based routing (flex-algo) based on the measurement results.

   o  Nested usage of flex-algo and TE extensions for IGP (see
      Section 4.1.11) when we can form 'underlay' by means of flex-algo
      and 'overlay' by TE.

   o  Flex-algo in SR-MPLS (Section 4.1.16) is a base use case when we
      can easily benefit from TE-like topology that will be built

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      without external TE component on routers or PCE (see
      Section 4.1.13).

   o  Building of network slices
      [I-D.nsdt-teas-ietf-network-slice-definition] where particular
      IETF network slice SLO can be guaranteed by flex-algo.

4.1.2.  Integrated Services

   The IETF developed the Integrated Services (Intserv) model that
   requires resources, such as bandwidth and buffers, to be reserved a
   priori for a given traffic flow to ensure that the quality of service
   requested by the traffic flow is satisfied.  The Integrated Services
   model includes additional components beyond those used in the best-
   effort model such as packet classifiers, packet schedulers, and
   admission control.  A packet classifier is used to identify flows
   that are to receive a certain level of service.  A packet scheduler
   handles the scheduling of service to different packet flows to ensure
   that QoS commitments are met.  Admission control is used to determine
   whether a router has the necessary resources to accept a new flow.

   The main issue with the Integrated Services model has been
   scalability [RFC2998], especially in large public IP networks which
   may potentially have millions of active micro-flows in transit

   A notable feature of the Integrated Services model is that it
   requires explicit signaling of QoS requirements from end systems to
   routers [RFC2753].  The Resource Reservation Protocol (RSVP) performs
   this signaling function and is a critical component of the Integrated
   Services model.  RSVP is described in Section 4.1.3.

4.1.3.  RSVP

   RSVP is a soft state signaling protocol [RFC2205].  It supports
   receiver initiated establishment of resource reservations for both
   multicast and unicast flows.  RSVP was originally developed as a
   signaling protocol within the Integrated Services framework (see
   Section 4.1.2) for applications to communicate QoS requirements to
   the network and for the network to reserve relevant resources to
   satisfy the QoS requirements [RFC2205].

   In RSVP, the traffic sender or source node sends a PATH message to
   the traffic receiver with the same source and destination addresses
   as the traffic which the sender will generate.  The PATH message
   contains: (1) a sender traffic specification describing the
   characteristics of the traffic, (2) a sender template specifying the
   format of the traffic, and (3) an optional advertisement

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   specification which is used to support the concept of One Pass With
   Advertising (OPWA) [RFC2205].  Every intermediate router along the
   path forwards the PATH message to the next hop determined by the
   routing protocol.  Upon receiving a PATH message, the receiver
   responds with a RESV message which includes a flow descriptor used to
   request resource reservations.  The RESV message travels to the
   sender or source node in the opposite direction along the path that
   the PATH message traversed.  Every intermediate router along the path
   can reject or accept the reservation request of the RESV message.  If
   the request is rejected, the rejecting router will send an error
   message to the receiver and the signaling process will terminate.  If
   the request is accepted, link bandwidth and buffer space are
   allocated for the flow and the related flow state information is
   installed in the router.

   One of the issues with the original RSVP specification was
   Scalability.  This is because reservations were required for micro-
   flows, so that the amount of state maintained by network elements
   tends to increase linearly with the number of micro-flows.  These
   issues are described in [RFC2961] which also modifies and extends
   RSVP to mitigate the scaling problems to make RSVP a versatile
   signaling protocol for the Internet.  For example, RSVP has been
   extended to reserve resources for aggregation of flows, to set up
   MPLS explicit label switched paths (see Section 4.1.6), and to
   perform other signaling functions within the Internet.  [RFC2961]
   also describes a mechanism to reduce the amount of Refresh messages
   required to maintain established RSVP sessions.

4.1.4.  Differentiated Services

   The goal of Differentiated Services (Diffserv) within the IETF was to
   devise scalable mechanisms for categorization of traffic into
   behavior aggregates, which ultimately allows each behavior aggregate
   to be treated differently, especially when there is a shortage of
   resources such as link bandwidth and buffer space [RFC2475].  One of
   the primary motivations for Diffserv was to devise alternative
   mechanisms for service differentiation in the Internet that mitigate
   the scalability issues encountered with the Intserv model.

   Diffserv uses the Differentiated Services field in the IP header (the
   DS field) consisting of six bits in what was formerly known as the
   Type of Service (TOS) octet.  The DS field is used to indicate the
   forwarding treatment that a packet should receive at a transit node
   [RFC2474].  Diffserv includes the concept of Per-Hop Behavior (PHB)
   groups.  Using the PHBs, several classes of services can be defined
   using different classification, policing, shaping, and scheduling

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   For an end-user of network services to utilize Differentiated
   Services provided by its Internet Service Provider (ISP), it may be
   necessary for the user to have an SLA with the ISP.  An SLA may
   explicitly or implicitly specify a Traffic Conditioning Agreement
   (TCA) which defines classifier rules as well as metering, marking,
   discarding, and shaping rules.

   Packets are classified, and possibly policed and shaped at the
   ingress to a Diffserv network.  When a packet traverses the boundary
   between different Diffserv domains, the DS field of the packet may be
   re-marked according to existing agreements between the domains.

   Differentiated Services allows only a finite number of service
   classes to be specified by the DS field.  The main advantage of the
   Diffserv approach relative to the Intserv model is scalability.
   Resources are allocated on a per-class basis and the amount of state
   information is proportional to the number of classes rather than to
   the number of application flows.

   The Diffserv model deals with traffic management issues on a per hop
   basis.  The Diffserv control model consists of a collection of micro-
   TE control mechanisms.  Other traffic engineering capabilities, such
   as capacity management (including routing control), are also required
   in order to deliver acceptable service quality in Diffserv networks.
   The concept of Per Domain Behaviors has been introduced to better
   capture the notion of Differentiated Services across a complete
   domain [RFC3086].

4.1.5.  QUIC

   QUIC [I-D.ietf-quic-transport] is a UDP-based multiplexed and secure
   transport protocol.  QUIC provides applications with flow-controlled
   streams for structured communication, low-latency connection
   establishment, and network path migration.

   QUIC is a connection-oriented protocol that creates a stateful
   interaction between a client and server.  QUIC uses a handshake
   procedure that combines negotiation of cryptographic and transport
   parameters.  This is a key differentiation from other transport

   Endpoints communicate in QUIC by exchanging QUIC packets that use a
   customized framing for protection.  Most QUIC packets contain frames,
   which carry control information and application data between
   endpoints.  QUIC authenticates all packets and encrypts as much as is
   practical.  QUIC packets are carried in UDP datagrams to better
   facilitate deployment within existing systems and networks.

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   Application protocols exchange information over a QUIC connection via
   streams, which are ordered sequences of bytes.  Two types of stream
   can be created: bidirectional streams, which allow both endpoints to
   send data; and unidirectional streams, which allow a single endpoint
   to send data.  A credit-based scheme is used to limit stream creation
   and to bound the amount of data that can be sent.

   QUIC provides the necessary feedback to implement reliable delivery
   and congestion control to avoid network congestion.

4.1.6.  Multiprotocol Label Switching (MPLS)

   MPLS is an advanced forwarding scheme which also includes extensions
   to conventional IP control plane protocols.  MPLS extends the
   Internet routing model and enhances packet forwarding and path
   control [RFC3031].

   At the ingress to an MPLS domain, Label Switching Routers (LSRs)
   classify IP packets into Forwarding Equivalence Classes (FECs) based
   on a variety of factors, including, e.g., a combination of the
   information carried in the IP header of the packets and the local
   routing information maintained by the LSRs.  An MPLS label stack
   entry is then prepended to each packet according to their forwarding
   equivalence classes.  The MPLS label stack entry is 32 bits long and
   contains a 20-bit label field.

   An LSR makes forwarding decisions by using the label prepended to
   packets as the index into a local next hop label forwarding entry
   (NHLFE).  The packet is then processed as specified in the NHLFE.
   The incoming label may be replaced by an outgoing label (label swap),
   and the packet may be forwarded to the next LSR.  Before a packet
   leaves an MPLS domain, its MPLS label may be removed (label pop).  A
   Label Switched Path (LSP) is the path between an ingress LSRs and an
   egress LSRs through which a labeled packet traverses.  The path of an
   explicit LSP is defined at the originating (ingress) node of the LSP.
   MPLS can use a signaling protocol such as RSVP or LDP to set up LSPs.

   MPLS is a very powerful technology for Internet traffic engineering
   because it supports explicit LSPs which allow constraint-based
   routing to be implemented efficiently in IP networks [AWD2].  The
   requirements for traffic engineering over MPLS are described in
   [RFC2702].  Extensions to RSVP to support instantiation of explicit
   LSP are discussed in [RFC3209].

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4.1.7.  Generalized MPLS (GMPLS)

   GMPLS extends MPLS control protocols to encompass time-division
   (e.g., Synchronous Optical Network / Synchronous Digital Hierarchy
   (SONET/SDH), Plesiochronous Digital Hierarchy (PDH), Optical
   Transport Network (OTN)), wavelength (lambdas), and spatial switching
   (e.g., incoming port or fiber to outgoing port or fiber) as well as
   continuing to support packet switching.  GMPLS provides a common set
   of control protocols for all of these layers (including some
   technology-specific extensions) each of which has a diverse data or
   forwarding plane.  GMPLS covers both the signaling and the routing
   part of that control plane and is based on the Traffic Engineering
   extensions to MPLS (see Section 4.1.6).

   In GMPLS, the original MPLS architecture is extended to include LSRs
   whose forwarding planes rely on circuit switching, and therefore
   cannot forward data based on the information carried in either packet
   or cell headers.  Specifically, such LSRs include devices where the
   switching is based on time slots, wavelengths, or physical ports.
   These additions impact basic LSP properties: how labels are requested
   and communicated, the unidirectional nature of MPLS LSPs, how errors
   are propagated, and information provided for synchronizing the
   ingress and egress LSRs.

4.1.8.  IP Performance Metrics

   The IETF IP Performance Metrics (IPPM) working group has developed a
   set of standard metrics that can be used to monitor the quality,
   performance, and reliability of Internet services.  These metrics can
   be applied by network operators, end-users, and independent testing
   groups to provide users and service providers with a common
   understanding of the performance and reliability of the Internet
   component 'clouds' they use/provide [RFC2330].  The criteria for
   performance metrics developed by the IPPM working group are described
   in [RFC2330].  Examples of performance metrics include one-way packet
   loss [RFC7680], one-way delay [RFC7679], and connectivity measures
   between two nodes [RFC2678].  Other metrics include second-order
   measures of packet loss and delay.

   Some of the performance metrics specified by the IPPM working group
   are useful for specifying SLAs.  SLAs are sets of service level
   objectives negotiated between users and service providers, wherein
   each objective is a combination of one or more performance metrics,
   possibly subject to certain constraints.

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4.1.9.  Flow Measurement

   The IETF Real Time Flow Measurement (RTFM) working group produced an
   architecture that defines a method to specify traffic flows as well
   as a number of components for flow measurement (meters, meter
   readers, manager) [RFC2722].  A flow measurement system enables
   network traffic flows to be measured and analyzed at the flow level
   for a variety of purposes.  As noted in RFC 2722, a flow measurement
   system can be very useful in the following contexts:

   o  understanding the behavior of existing networks

   o  planning for network development and expansion

   o  quantification of network performance

   o  verifying the quality of network service

   o  attribution of network usage to users.

   A flow measurement system consists of meters, meter readers, and
   managers.  A meter observes packets passing through a measurement
   point, classifies them into groups, accumulates usage data (such as
   the number of packets and bytes for each group), and stores the usage
   data in a flow table.  A group may represent any collection of user
   applications, hosts, networks, etc.  A meter reader gathers usage
   data from various meters so it can be made available for analysis.  A
   manager is responsible for configuring and controlling meters and
   meter readers.  The instructions received by a meter from a manager
   include flow specifications, meter control parameters, and sampling
   techniques.  The instructions received by a meter reader from a
   manager include the address of the meter whose date is to be
   collected, the frequency of data collection, and the types of flows
   to be collected.

4.1.10.  Endpoint Congestion Management

   [RFC3124] provides a set of congestion control mechanisms for the use
   of transport protocols.  It is also allows the development of
   mechanisms for unifying congestion control across a subset of an
   endpoint's active unicast connections (called a congestion group).  A
   congestion manager continuously monitors the state of the path for
   each congestion group under its control.  The manager uses that
   information to instruct a scheduler on how to partition bandwidth
   among the connections of that congestion group.

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4.1.11.  TE Extensions to the IGPs

   [RFC5305] describes the extensions to the Intermediate System to
   Intermediate System (IS-IS) protocol to support TE, similarly
   [RFC3630] specifies TE extensions for OSPFv2 ([RFC5329] has the same
   description for OSPFv3).

   The idea of redistribution TE extensions such as link type and ID,
   local and remote IP addresses, TE metric, maximum bandwidth, maximum
   reservable bandwidth and unreserved bandwidth, admin group in IGP is
   a common for both IS-IS and OSPF.

   The difference is in the details of their transmission: IS-IS uses
   the Extended IS Reachability TLV (type 22) and Sub-TLVs for those TE
   parameters, OSPFv2 uses Opaque LSA [RFC5250] type 10 (OSPFv3 uses
   Intra-Area-TE-LSA) with two top-level TLV (Router Address and Link)
   also with Sub-TLVs for that purpose.

   IS-IS also uses the Extended IP Reachability TLV (type 135, which
   have the new 32 bit metric) and the TE Router ID TLV (type 134).
   Those Sub-TLV details are described in [RFC8570] for IS-IS and in
   [RFC7471] for OSPFv2 ([RFC5329] for OSPFv3).

4.1.12.  Link-State BGP

   In a number of environments, a component external to a network is
   called upon to perform computations based on the network topology and
   current state of the connections within the network, including
   traffic engineering information.  This is information typically
   distributed by IGP routing protocols within the network (see
   Section 4.1.11.

   The Border Gateway Protocol (BGP) Section 7 is one of the essential
   routing protocols that glue the Internet together.  BGP Link State
   (BGP-LS) [RFC7752] is a mechanism by which link-state and traffic
   engineering information can be collected from networks and shared
   with external components using the BGP routing protocol.  The
   mechanism is applicable to physical and virtual IGP links, and is
   subject to policy control.

   Information collected by BGP-LS can be used to construct the Traffic
   Engineering Database (TED, see Section 4.1.20) for use by the Path
   Computation Element (PCE, see Section 4.1.13), or may be used by
   Application-Layer Traffic Optimization (ALTO) servers (see
   Section 4.1.15).

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4.1.13.  Path Computation Element

   Constraint-based path computation is a fundamental building block for
   traffic engineering in MPLS and GMPLS networks.  Path computation in
   large, multi-domain networks is complex and may require special
   computational components and cooperation between the elements in
   different domains.  The Path Computation Element (PCE) [RFC4655] is
   an entity (component, application, or network node) that is capable
   of computing a network path or route based on a network graph and
   applying computational constraints.

   Thus, a PCE can provide a central component in a traffic engineering
   system operating on the Traffic Engineering Database (TED, see
   Section 4.1.20) with delegated responsibility for determining paths
   in MPLS, GMPLS, or Segment Routing networks.  The PCE uses the Path
   Computation Element Communication Protocol (PCEP) [RFC5440] to
   communicate with Path Computation Clients (PCCs), such as MPLS LSRs,
   to answer their requests for computed paths or to instruct them to
   initiate new paths [RFC8281] and maintain state about paths already
   installed in the network [RFC8231].

   PCEs form key components of a number of traffic engineering systems.
   More information about the applicability of PCE can be found in
   [RFC8051], while [RFC6805] describes the application of PCE to
   determining paths across multiple domains.  PCE also has potential
   use in Abstraction and Control of TE Networks (ACTN) (see
   Section 4.1.17), Centralized Network Control [RFC8283], and Software
   Defined Networking (SDN) (see Section 5.3.2).

4.1.14.  Multi-Layer Traffic Engineering

   Networks are often arranged as layers.  A layer relationship may
   represent the interaction between technologies (for example, an IP
   network operated over an optical network), or the relationship
   between different network operators (for example, a customer network
   operated over a service provider's network).  Note that a multi-layer
   network does not imply the use of multiple technologies, although
   some form of encapsulation is often applied.

   Multi-layer traffic engineering presents a number of challenges
   associated with scalability and confidentiality.  These issues are
   addressed in [RFC7926] which discusses the sharing of information
   between domains through policy filters, aggregation, abstraction, and
   virtualization.  That document also discusses how existing protocols
   can support this scenario with special reference to BGP-LS (see
   Section 4.1.12).

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   PCE (see Section 4.1.13) is also a useful tool for multi-layer
   networks as described in [RFC6805] and [RFC8685].  Signaling
   techniques for multi-layer traffic engineering are described in

   See also Appendix A.3.1 for a discussion of how the overlay model has
   been important in the development of traffic engineering.

4.1.15.  Application-Layer Traffic Optimization

   This document describes various TE mechanisms available in the
   network.  However, distributed applications in general and, in
   particular, bandwidth-greedy P2P applications that are used, for
   example, for file sharing, cannot directly use those techniques.  As
   per [RFC5693], applications could greatly improve traffic
   distribution and quality by cooperating with external services that
   are aware of the network topology.  Addressing the Application-Layer
   Traffic Optimization (ALTO) problem means, on the one hand, deploying
   an ALTO service to provide applications with information regarding
   the underlying network (e.g., basic network location structure and
   preferences of network paths) and, on the other hand, enhancing
   applications in order to use such information to perform better-than-
   random selection of the endpoints with which they establish

   The basic function of ALTO is based on abstract maps of a network.
   These maps provide a simplified view, yet enough information about a
   network for applications to effectively utilize them.  Additional
   services are built on top of the maps.  [RFC7285] describes a
   protocol implementing the ALTO services as an information-publishing
   interface that allows a network to publish its network information
   such as network locations, costs between them at configurable
   granularities, and end-host properties to network applications.  The
   information published by the ALTO Protocol should benefit both the
   network and the applications.  The ALTO Protocol uses a REST-ful
   design and encodes its requests and responses using JSON [RFC8259]
   with a modular design by dividing ALTO information publication into
   multiple ALTO services (e.g., the Map service, the Map-Filtering
   Service, the Endpoint Property Service, and the Endpoint Cost

   [RFC8189] defines a new service that allows an ALTO Client to
   retrieve several cost metrics in a single request for an ALTO
   filtered cost map and endpoint cost map.  [RFC8896] extends the ALTO
   cost information service so that applications decide not only 'where'
   to connect, but also 'when'.  This is useful for applications that
   need to perform bulk data transfer and would like to schedule these
   transfers during an off-peak hour, for example.

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   [I-D.ietf-alto-performance-metrics] introducing network performance
   metrics, including network delay, jitter, packet loss rate, hop
   count, and bandwidth.  The ALTO server may derive and aggregate such
   performance metrics from BGP-LS (see Section 4.1.12) or IGP-TE (see
   Section 4.1.11), or management tools, and then expose the information
   to allow applications to determine 'where' to connect based on
   network performance criteria.  ALTO WG is evaluating the use of
   network TE properties while making application decisions for new use-
   cases such as Edge computing and Datacenter interconnect.

4.1.16.  Segment Routing with MPLS Encapsulation (SR-MPLS)

   Segment Routing (SR) [RFC8402] leverages the source routing and
   tunneling paradigms.  The path a packet takes is defined at the
   ingress and the packet is tunneled to the egress.  A node steers a
   packet through a controlled set of instructions, called segments, by
   prepending the packet with an SR header: a label stack in MPLS case.

   A segment can represent any instruction, topological or service-
   based, thanks to the MPLS architecture [RFC3031].  Labels can be
   looked up in a global context (platform wide) as well as in some
   other context (see "context labels" in Section 3 of [RFC5331]).  Base Segment Routing Identifier Types

   Segments are identified by Segment Identifiers (SIDs).  There are
   four types of SID that are relevant for traffic engineering.

   Prefix SID:  Uses the SR Global Block (SRGB), must be unique within
      the routing domain SRGB, and is advertised by an IGP.  The Prefix-
      SID can be configured as an absolute value or an index.

   Node SID:  A Prefix SID with the 'N' (node) bit set.  It is
      associated with a host prefix (/32 or /128) that identifies the
      node.  More than 1 Node SID can be configured per node.

   Adjacency SID:  Locally significant by default, an Adjacency SID can
      be made globally significant through use of the 'L' flag.  It
      identifies a unidirectional adjacency.  In most implementations
      Adjacency SIDs are automatically allocated for each adjacency.
      They are always encoded as an absolute (not indexed) value.

   Binding SID:  A Binding SID has two purposes:

      1.  Mapping Server in ISIS

             The SID/Label Binding TLV is used to advertise the mappings
             of prefixes to SIDs/Labels.  This functionality is called

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             the Segment Routing Mapping Server (SRMS).  The behavior of
             the SRMS is defined in [RFC8661]

      2.  Cross-connect (label to FEC mapping)

             This is fundamental for multi-domain/multi-layer operation.
             The Binding SID identifies a new path available at the
             anchor point.  It is always local to the originator, must
             not be present at the top of the stack, and must be looked
             up in the context of the Node SID.  It could be provisioned
             through Netconf/Restconf, PCEP, BGP, or the CLI.  Segment Routing Policy

   SR Policy [I-D.ietf-spring-segment-routing-policy] is an evolution of
   Segment Routing to enhance the TE capabilities.  It is a framework
   that enables instantiation of an ordered list of segments on a node
   for implementing a source routing policy with a specific intent for
   traffic steering from that node.

   An SR Policy is identified through the tuple <headend, color,
   endpoint>.  The headend is the IP address of the node where the
   policy is instantiated.  The endpoint is the IP address of the
   destination of the policy.  The color is an index that associates the
   SR Policy with an intent (e.g., low-latency).

   The headend node is notified of SR Policies and associated SR paths
   via configuration or by a extensions to protocols such as PCEP
   [RFC8664] or BGP [I-D.ietf-idr-segment-routing-te-policy].  Each SR
   path consists of a Segment-List (an SR source-routed path), and the
   headend uses the endpoint and color parameters to classify packets to
   match the SR policy and so determine along which path to forward
   them.  If an SR Policy is associated with a set of SR paths, each is
   associated with a weight for weighted load balancing.  Furthermore,
   multiple SR Policies may be associated with a set of SR paths to
   allow multiple traffic flows to be placed on the same paths.

   An SR Binding SID (BSID) are also be associated with each candidate
   path associated with an SR Policy, or with the SR Policy itself.  The
   headend node installs a BSID-keyed entry in the forwarding plane and
   assigns it the action of steering packets that match the entry to the
   selected path of the SR Policy.  This steering can be done in various

   o  SID Steering: Incoming packets have an active SID matching a local
      BSID at the headend.

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   o  Per-destination Steering: Incoming packets match a BGP/Service
      route which indicates an SR Policy.

   o  Per-flow Steering: Incoming packets match a forwarding array (for
      example, the classic 5-tuple) which indicates an SR Policies.

   o  Policy-based Steering: Incoming packets match a routing policy
      which directs them to an SR Policy.

4.1.17.  Network Virtualization and Abstraction

   One of the main drivers for Software Defined Networking (SDN)
   [RFC7149] is a decoupling of the network control plane from the data
   plane.  This separation has been achieved for TE networks with the
   development of MPLS/GMPLS (see Section 4.1.6 and Section 4.1.7) and
   the Path Computation Element (PCE) (Section 4.1.13).  One of the
   advantages of SDN is its logically centralized control regime that
   allows a global view of the underlying networks.  Centralized control
   in SDN helps improve network resource utilization compared with
   distributed network control.

   Abstraction and Control of TE Networks (ACTN) [RFC8453] defines a
   hierarchical SDN architecture which describes the functional entities
   and methods for the coordination of resources across multiple
   domains, to provide end-to-end traffic engineered services.  ACTN
   facilitates end-to-end connections and provides them to the user.
   ACTN is focused on:

   o  Abstraction of the underlying network resources and how they are
      provided to higher-layer applications and customers.

   o  Virtualization of underlying resources for use by the customer,
      application, or service.  The creation of a virtualized
      environment allows operators to view and control multi-domain
      networks as a single virtualized network.

   o  Presentation to customers of networks as a virtual network via
      open and programmable interfaces.

   The ACTN managed infrastructure is built from traffic engineered
   network resources, which may include statistical packet bandwidth,
   physical forwarding plane sources (such as wavelengths and time
   slots), forwarding and cross-connect capabilities.  The type of
   network virtualization seen in ACTN allows customers and applications
   (tenants) to utilize and independently control allocated virtual
   network resources as if resources as if they were physically their
   own resource.  The ACTN network is "sliced", with tenants being given

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   a different partial and abstracted topology view of the physical
   underlying network.

4.1.18.  Network Slicing

   An IETF Network Slice is a logical network topology connecting a
   number of endpoints using a set of shared or dedicated network
   resources [I-D.nsdt-teas-ietf-network-slice-definition].  The
   resources are used to satisfy specific Service Level Objectives
   (SLOs) specified by the consumer.

   IETF Network Slices are created and managed within the scope of one
   or more network technologies (e.g., IP, MPLS, optical).  They are
   intended to enable a diverse set of applications that have different
   requirements to coexist on the same network infrastructure.  IETF
   Network Slices are defined such that they are independent of the
   underlying infrastructure connectivity and technologies used.  This
   is to allow an IETF Network Slice consumer to describe their network
   connectivity and relevant objectives in a common format, independent
   of the underlying technologies used.

   An IETF Network Slice is a well-defined composite of a set of
   endpoints, the connectivity requirements between subsets of these
   endpoints, and associated service requirements.  The service
   requirements are expressed in terms of quantifiable characteristics
   or service level objectives (SLOs).  SLOs along with terms Service
   Level Indicator (SLI) and Service Level Agreement (SLA) are used to
   define the performance of a service at different levels

   The concept of an IETF network slice is consistent with an enhanced
   VPN (VPN+) [I-D.ietf-teas-enhanced-vpn].  That is, from a consumer's
   perspective it looks like a VPN connectivity matrix with additional
   information about the level of service required between endpoints,
   while from an operator's perspective it looks like a set of routing
   or tunneling instructions with the network resource reservations
   necessary to provide the required service levels as specified by the

   IETF network slices are not, of themselves, TE constructs.  However,
   a network operator that offers IETF network slices is likely to use
   many TE tools in order to manage their network and provide the

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4.1.19.  Deterministic Networking

   Deterministic Networking (DetNet) [RFC8655] is an architecture for
   applications with critical timing and reliability requirements.  The
   layered architecture particularly focuses on developing DetNet
   service capabilities in the data plane [RFC8938].  The DetNet service
   sub-layer provides a set of Packet Replication, Elimination, and
   Ordering Functions (PREOF) functions to provide end-to-end service
   assurance.  The DetNet forwarding sub-layer provides corresponding
   forwarding assurance (low packet loss, bounded latency, and in-order
   delivery) functions using resource allocations and explicit route

   The separation into two sub-layers allows a greater flexibility to
   adapt Detnet capability over a number of TE data plane mechanisms
   such as IP, MPLS, and Segment Routing.  More importantly it
   interconnects IEEE 802.1 Time Sensitive Networking (TSN)
   [I-D.ietf-detnet-ip-over-tsn] deployed in Industry Control and
   Automation Systems (ICAS).

   DetNet can be seen as a specialized branch of TE, since it sets up
   explicit optimized paths with allocation of resources as requested.
   A DetNet application can express its QoS attributes or traffic
   behavior using any combination of DetNet functions described in sub-
   layers.  They are then distributed and provisioned using well-
   established control and provisioning mechanisms adopted for traffic-

   In DetNet, a considerable state information is required to maintain
   per flow queuing disciplines and resource reservation for a large
   number of individual flows.  This can be quite challenging for
   network operations during network events such as faults, change in
   traffic volume or re-provisioning.  Therefore, DetNet recommends
   support for aggregated flows, however, it still requires large amount
   of control signaling to establish and maintain DetNet flows.

4.1.20.  Network TE State Definition and Presentation

   The network states that are relevant to the traffic engineering need
   to be stored in the system and presented to the user.  The Traffic
   Engineering Database (TED) is a collection of all TE information
   about all TE nodes and TE links in the network, which is an essential
   component of a TE system, such as MPLS-TE [RFC2702] and GMPLS
   [RFC3945].  In order to formally define the data in the TED and to
   present the data to the user with high usability, the data modeling
   language YANG [RFC7950] can be used as described in [RFC8795].

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4.1.21.  System Management and Control Interfaces

   The traffic engineering control system needs to have a management
   interface that is human-friendly and a control interfaces that is
   programmable for automation.  The Network Configuration Protocol
   (NETCONF) [RFC6241] or the RESTCONF Protocol [RFC8040] provide
   programmable interfaces that are also human-friendly.  These
   protocols use XML or JSON encoded messages.  When message compactness
   or protocol bandwidth consumption needs to be optimized for the
   control interface, other protocols, such as Group Communication for
   the Constrained Application Protocol (CoAP) [RFC7390] or gRPC, are
   available, especially when the protocol messages are encoded in a
   binary format.  Along with any of these protocols, the data modeling
   language YANG [RFC7950] can be used to formally and precisely define
   the interface data.

   The Path Computation Element Communication Protocol (PCEP) [RFC5440]
   is another protocol that has evolved to be an option for the TE
   system control interface.  The messages of PCEP are TLV-based, not
   defined by a data modeling language such as YANG.

4.2.  Content Distribution

   The Internet is dominated by client-server interactions, principally
   Web traffic although in the future, more sophisticated media servers
   may become dominant.  The location and performance of major
   information servers has a significant impact on the traffic patterns
   within the Internet as well as on the perception of service quality
   by end users.

   A number of dynamic load balancing techniques have been devised to
   improve the performance of replicated information servers.  These
   techniques can cause spatial traffic characteristics to become more
   dynamic in the Internet because information servers can be
   dynamically picked based upon the location of the clients, the
   location of the servers, the relative utilization of the servers, the
   relative performance of different networks, and the relative
   performance of different parts of a network.  This process of
   assignment of distributed servers to clients is called traffic
   directing.  It is an application layer function.

   Traffic directing schemes that allocate servers in multiple
   geographically dispersed locations to clients may require empirical
   network performance statistics to make more effective decisions.  In
   the future, network measurement systems may need to provide this type
   of information.

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   When congestion exists in the network, traffic directing and traffic
   engineering systems should act in a coordinated manner.  This topic
   is for further study.

   The issues related to location and replication of information
   servers, particularly web servers, are important for Internet traffic
   engineering because these servers contribute a substantial proportion
   of Internet traffic.

5.  Taxonomy of Traffic Engineering Systems

   This section presents a short taxonomy of traffic engineering systems
   constructed based on traffic engineering styles and views as listed
   below and described in greater detail in the following subsections of
   this document.

   o  Time-dependent versus State-dependent versus Event-dependent

   o  Offline versus Online

   o  Centralized versus Distributed

   o  Local versus Global Information

   o  Prescriptive versus Descriptive

   o  Open Loop versus Closed Loop

   o  Tactical versus Strategic

5.1.  Time-Dependent Versus State-Dependent Versus Event-Dependent

   Traffic engineering methodologies can be classified as time-
   dependent, state-dependent, or event-dependent.  All TE schemes are
   considered to be dynamic in this document.  Static TE implies that no
   traffic engineering methodology or algorithm is being applied - it is
   a feature of network planning, but lacks the reactive and flexible
   nature of traffic engineering.

   In time-dependent TE, historical information based on periodic
   variations in traffic (such as time of day) is used to pre-program
   routing and other TE control mechanisms.  Additionally, customer
   subscription or traffic projection may be used.  Pre-programmed
   routing plans typically change on a relatively long time scale (e.g.,
   daily).  Time-dependent algorithms do not attempt to adapt to short-
   term variations in traffic or changing network conditions.  An
   example of a time-dependent algorithm is a global centralized
   optimizer where the input to the system is a traffic matrix and

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   multi-class QoS requirements as described [MR99].  Another example of
   such a methodology is the application of data mining to Internet
   traffic [AJ19] which enables the use of various machine learning
   algorithms to identify patterns within historically collected
   datasets about Internet traffic, and to extract information in order
   to guide decision-making, and to improve efficiency and productivity
   of operational processes.

   State-dependent TE adapts the routing plans based on the current
   state of the network which provides additional information on
   variations in actual traffic (i.e., perturbations from regular
   variations) that could not be predicted using historical information.
   Constraint-based routing is an example of state-dependent TE
   operating in a relatively long time scale.  An example operating in a
   relatively short timescale is a load-balancing algorithm described in
   [MATE].  The state of the network can be based on parameters flooded
   by the routers.  Another approach is for a particular router
   performing adaptive TE to send probe packets along a path to gather
   the state of that path.  [RFC6374] defines protocol extensions to
   collect performance measurements from MPLS networks.  Another
   approach is for a management system to gather the relevant
   information directly from network elements using telemetry data
   collection "publication/subscription" techniques [RFC7923].  Timely
   gathering and distribution of state information is critical for
   adaptive TE.  While time-dependent algorithms are suitable for
   predictable traffic variations, state-dependent algorithms may be
   applied to increase network efficiency and resilience to adapt to the
   prevailing network state.

   Event-dependent TE methods can also be used for TE path selection.
   Event-dependent TE methods are distinct from time-dependent and
   state-dependent TE methods in the manner in which paths are selected.
   These algorithms are adaptive and distributed in nature and typically
   use learning models to find good paths for TE in a network.  While
   state-dependent TE models typically use available-link-bandwidth
   (ALB) flooding for TE path selection, event-dependent TE methods do
   not require ALB flooding.  Rather, event-dependent TE methods
   typically search out capacity by learning models, as in the success-
   to-the-top (STT) method.  ALB flooding can be resource intensive,
   since it requires link bandwidth to carry LSAs, processor capacity to
   process LSAs, and the overhead can limit area/Autonomous System (AS)
   size.  Modeling results suggest that event-dependent TE methods could
   lead to a reduction in ALB flooding overhead without loss of network
   throughput performance [I-D.ietf-tewg-qos-routing].

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5.2.  Offline Versus Online

   Traffic engineering requires the computation of routing plans.  The
   computation may be performed offline or online.  The computation can
   be done offline for scenarios where routing plans need not be
   executed in real-time.  For example, routing plans computed from
   forecast information may be computed offline.  Typically, offline
   computation is also used to perform extensive searches on multi-
   dimensional solution spaces.

   Online computation is required when the routing plans must adapt to
   changing network conditions as in state-dependent algorithms.  Unlike
   offline computation (which can be computationally demanding), online
   computation is geared toward relative simple and fast calculations to
   select routes, fine-tune the allocations of resources, and perform
   load balancing.

5.3.  Centralized Versus Distributed

   Under centralized control there is a central authority which
   determines routing plans and perhaps other TE control parameters on
   behalf of each router.  The central authority periodically collects
   network-state information from all routers, and sends routing
   information to the routers.  The update cycle for information
   exchange in both directions is a critical parameter directly
   impacting the performance of the network being controlled.
   Centralized control may need high processing power and high bandwidth
   control channels.

   Distributed control determines route selection by each router
   autonomously based on the router's view of the state of the network.
   The network state information may be obtained by the router using a
   probing method or distributed by other routers on a periodic basis
   using link state advertisements.  Network state information may also
   be disseminated under exception conditions.  Examples of protocol
   extensions used to advertise network link state information are
   defined in [RFC5305], [RFC6119], [RFC7471], [RFC8570], and [RFC8571].
   See also Section 4.1.11.

5.3.1.  Hybrid Systems

   In practice, most TE systems will be a hybrid of central and
   distributed control.  For example, a popular MPLS approach to TE is
   to use a central controller based on an active, stateful PCE, but to
   use routing and signaling protocols to make local decisions at
   routers within the network.  Local decisions may be able to respond
   more quickly to network events, but may result in conflicts with
   decisions made by other routers.

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   Network operations for TE systems may also use a hybrid of offline
   and online computation.  TE paths may be precomputed based on stable-
   state network information and planned traffic demands, but may then
   be modified in the active network depending on variations in network
   state and traffic load.  Furthermore, responses to network events may
   be precomputed offline to allow rapid reactions without further
   computation, or may be derived online depending on the nature of the

   Lastly, note that a fully functional TE system is likely to use all
   aspects of time-dependent, state-dependent, and event-dependent
   methodologies as described in Section 5.1.

5.3.2.  Considerations for Software Defined Networking

   As discussed in Section 4.1.17, one of the main drivers for SDN is a
   decoupling of the network control plane from the data plane
   [RFC7149].  However, SDN may also combine centralized control of
   resources, and facilitate application-to-network interaction via an
   application programming interface (API) such as [RFC8040].  Combining
   these features provides a flexible network architecture that can
   adapt to network requirements of a variety of higher-layer
   applications, a concept often referred to as the "programmable
   network" [RFC7426].

   The centralized control aspect of SDN helps improve global network
   resource utilization compared with distributed network control, where
   local policy may often override global optimization goals.  In an SDN
   environment, the data plane forwards traffic to its desired
   destination.  However, before traffic reaches the data plane, the
   logically centralized SDN control plane often determines the end-to-
   end path the application traffic will take in the network.
   Therefore, the SDN control plane needs to be aware of the underlying
   network topology, capabilities and current node and link resource

   Using a PCE-based SDN control framework [RFC7491], the available
   network topology may be discovered by running a passive instance of
   OSPF or IS-IS, or via BGP-LS [RFC7752], to generate a TED (see
   Section 4.1.20).  The PCE is used to compute a path (see
   Section 4.1.13) based on the TED and available bandwidth, and further
   path optimization may be based on requested objective functions
   [RFC5541].  When a suitable path has been computed the programming of
   the explicit network path may be performed using either end-to-end
   signaling protocol [RFC3209] or per-hop with each node being directly
   programmed [RFC8283] by the SDN controller.

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   By utilizing a centralized approach to network control, additional
   network benefits are also available, including Global Concurrent
   Optimization (GCO) [RFC5557].  A GCO path computation request will
   simultaneously use the network topology and set of new end-to-end
   path requests, along with their respective constraints, for optimal
   placement in the network.  Correspondingly, a GCO-based computation
   may be applied to recompute existing network paths to groom traffic
   and to mitigate congestion.

5.4.  Local Versus Global

   Traffic engineering algorithms may require local and global network-
   state information.

   Local information is the state of a portion of the domain.  Examples
   include the bandwidth and packet loss rate of a particular path, or
   the state and capabilities of a network link.  Local state
   information may be sufficient for certain instances of distributed
   control TE.

   Global information is the state of the entire TE domain.  Examples
   include a global traffic matrix, and loading information on each link
   throughout the domain of interest.  Global state information is
   typically required with centralized control.  Distributed TE systems
   may also need global information in some cases.

5.5.  Prescriptive Versus Descriptive

   TE systems may also be classified as prescriptive or descriptive.

   Prescriptive traffic engineering evaluates alternatives and
   recommends a course of action.  Prescriptive traffic engineering can
   be further categorized as either corrective or perfective.
   Corrective TE prescribes a course of action to address an existing or
   predicted anomaly.  Perfective TE prescribes a course of action to
   evolve and improve network performance even when no anomalies are

   Descriptive traffic engineering, on the other hand, characterizes the
   state of the network and assesses the impact of various policies
   without recommending any particular course of action.

5.5.1.  Intent-Based Networking

   Intent is defined in [I-D.irtf-nmrg-ibn-concepts-definitions] as a
   set of operational goals (that a network should meet) and outcomes
   (that a network is supposed to deliver), defined in a declarative
   manner without specifying how to achieve or implement them.  This

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   definition is based on [RFC7575] where, in the context of Autonomic
   Networks, it is described as "an abstract, high-level policy used to
   operate a network."

   Thus, intent-based management or Intent-Based Networking (IBN) is the
   concept of operating a network based on the concept of intent.

   Intent-Based Networking aims to produce networks that are simpler to
   manage and operate, requiring only minimal intervention.  Networks
   have no way of automatically knowing operational goals nor which
   instances of networking services to support, thus the operator's
   intent needs to be communicated to the network.

   More specifically, intent is a declaration of operational goals that
   a network should meet and outcomes that the network is supposed to
   deliver, without specifying how to achieve them.  Those goals and
   outcomes are defined in a purely declarative way: they specify what
   to accomplish, not how to achieve it.  Intent applies two concepts:

   o  It provides data abstraction: users and operators do not need to
      be concerned with low-level device configuration.

   o  It provides functional abstraction: users and operators do not
      need to be concerned with how to achieve a given intent.  What is
      specified is the desired outcome which is converted by the
      management system into the actions that will achieve the outcome.

   Intent-Based Networking is applicable to traffic engineering because
   many of the high-level objectives may be expressed as "intent."  For
   example, load balancing, delivery of services, and robustness against
   failures.  The intent is converted by the management system into
   traffic engineering actions within the network.

5.6.  Open-Loop Versus Closed-Loop

   Open-loop traffic engineering control is where control action does
   not use feedback information from the current network state.  The
   control action may use its own local information for accounting
   purposes, however.

   Closed-loop traffic engineering control is where control action
   utilizes feedback information from the network state.  The feedback
   information may be in the form of historical information or current

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5.7.  Tactical versus Strategic

   Tactical traffic engineering aims to address specific performance
   problems (such as hot-spots) that occur in the network from a
   tactical perspective, without consideration of overall strategic
   imperatives.  Without proper planning and insights, tactical TE tends
   to be ad hoc in nature.

   Strategic traffic engineering approaches the TE problem from a more
   organized and systematic perspective, taking into consideration the
   immediate and longer term consequences of specific policies and

6.  Recommendations for Internet Traffic Engineering

   This section describes high-level recommendations for traffic
   engineering in the Internet in general terms.

   The recommendations describe the capabilities needed to solve a
   traffic engineering problem or to achieve a traffic engineering
   objective.  Broadly speaking, these recommendations can be
   categorized as either functional or non-functional recommendations.

   o  Functional recommendations describe the functions that a traffic
      engineering system should perform.  These functions are needed to
      realize traffic engineering objectives by addressing traffic
      engineering problems.

   o  Non-functional recommendations relate to the quality attributes or
      state characteristics of a traffic engineering system.  These
      recommendations may contain conflicting assertions and may
      sometimes be difficult to quantify precisely.

6.1.  Generic Non-functional Recommendations

   The generic non-functional recommendations for Internet traffic
   engineering are listed in the paragraphs that follow.  In a given
   context, some of these recommendations may be critical while others
   may be optional.  Therefore, prioritization may be required during
   the development phase of a traffic engineering system to tailor it to
   a specific operational context.

   Usability:  Usability is a human aspect of traffic engineering
      systems.  It refers to the ease with which a traffic engineering
      system can be deployed and operated.  In general, it is desirable
      to have a TE system that can be readily deployed in an existing
      network.  It is also desirable to have a TE system that is easy to
      operate and maintain.

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   Automation:  Whenever feasible, a TE system should automate as many
      TE functions as possible to minimize the amount of human effort
      needed to analyze and control operational networks.  Automation is
      particularly important in large-scale public networks because of
      the high cost of the human aspects of network operations and the
      high risk of network problems caused by human errors.  Automation
      may entail the incorporation of automatic feedback and
      intelligence into some components of the TE system.

   Scalability:  Public networks continue to grow rapidly with respect
      to network size and traffic volume.  Therefore, to remain
      applicable as the network evolves, a TE system should be scalable.
      In particular, a TE system should remain functional as the network
      expands with regard to the number of routers and links, and with
      respect to the traffic volume.  A TE system should have a scalable
      architecture, should not adversely impair other functions and
      processes in a network element, and should not consume too many
      network resources when collecting and distributing state
      information, or when exerting control.

   Stability:  Stability is a very important consideration in TE systems
      that respond to changes in the state of the network.  State-
      dependent TE methodologies typically include a trade-off between
      responsiveness and stability.  It is strongly recommended that
      when a trade-off between responsiveness and stability is needed,
      it should be made in favor of stability (especially in public IP
      backbone networks).

   Flexibility:  A TE system should allow for changes in optimization
      policy.  In particular, a TE system should provide sufficient
      configuration options so that a network administrator can tailor
      the system to a particular environment.  It may also be desirable
      to have both online and offline TE subsystems which can be
      independently enabled and disabled.  TE systems that are used in
      multi-class networks should also have options to support class
      based performance evaluation and optimization.

   Visibility:  Mechanisms should exist as part of the TE system to
      collect statistics from the network and to analyze these
      statistics to determine how well the network is functioning.
      Derived statistics such as traffic matrices, link utilization,
      latency, packet loss, and other performance measures of interest
      which are determined from network measurements can be used as
      indicators of prevailing network conditions.  The capabilities of
      the various components of the routing system are other examples of
      status information which should be observable.

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   Simplicity:  A TE system should be as simple as possible and easy to
      use (i.e., have clean, convenient, and intuitive user interfaces).
      Simplicity in user interface does not necessarily imply that the
      TE system will use naive algorithms.  When complex algorithms and
      internal structures are used, the user interface should hide such
      complexities from the network administrator as much as possible.

   Interoperability:  Whenever feasible, TE systems and their components
      should be developed with open standards-based interfaces to allow
      interoperation with other systems and components.

   Security:  Security is a critical consideration in TE systems.  Such
      systems typically exert control over functional aspects of the
      network to achieve the desired performance objectives.  Therefore,
      adequate measures must be taken to safeguard the integrity of the
      TE system.  Adequate measures must also be taken to protect the
      network from vulnerabilities that originate from security breaches
      and other impairments within the TE system.

   The remaining subsections of this section focus on some of the high-
   level functional recommendations for traffic engineering.

6.2.  Routing Recommendations

   Routing control is a significant aspect of Internet traffic
   engineering.  Routing impacts many of the key performance measures
   associated with networks, such as throughput, delay, and utilization.
   Generally, it is very difficult to provide good service quality in a
   wide area network without effective routing control.  A desirable TE
   routing system is one that takes traffic characteristics and network
   constraints into account during route selection while maintaining

   Shortest path first (SPF) IGPs are based on shortest path algorithms
   and have limited control capabilities for TE [RFC2702], [AWD2].
   These limitations include:

   1.  Pure SPF protocols do not take network constraints and traffic
       characteristics into account during route selection.  For
       example, IGPs always select the shortest paths based on link
       metrics assigned by administrators) so load sharing cannot be
       performed across paths of different costs.  Using shortest paths
       to forward traffic may cause the following problems:

       *  If traffic from a source to a destination exceeds the capacity
          of a link along the shortest path, the link (and hence the
          shortest path) becomes congested while a longer path between
          these two nodes may be under-utilized

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       *  The shortest paths from different sources can overlap at some
          links.  If the total traffic from the sources exceeds the
          capacity of any of these links, congestion will occur.

       *  Problems can also occur because traffic demand changes over
          time, but network topology and routing configuration cannot be
          changed as rapidly.  This causes the network topology and
          routing configuration to become sub-optimal over time, which
          may result in persistent congestion problems.

   2.  The Equal-Cost Multi-Path (ECMP) capability of SPF IGPs supports
       sharing of traffic among equal cost paths between two nodes.
       However, ECMP attempts to divide the traffic as equally as
       possible among the equal cost shortest paths.  Generally, ECMP
       does not support configurable load sharing ratios among equal
       cost paths.  The result is that one of the paths may carry
       significantly more traffic than other paths because it may also
       carry traffic from other sources.  This situation can result in
       congestion along the path that carries more traffic.  Weighted
       ECMP (WECMP) (see, for example, [I-D.ietf-bess-evpn-unequal-lb])
       provides some mitigation.

   3.  Modifying IGP metrics to control traffic routing tends to have
       network-wide effects.  Consequently, undesirable and
       unanticipated traffic shifts can be triggered as a result.  Work
       described in Section 8 may be capable of better control [FT00],

   Because of these limitations, new capabilities are needed to enhance
   the routing function in IP networks.  Some of these capabilities are
   summarized below.

   o  Constraint-based routing computes routes to fulfill requirements
      subject to constraints.  This can be useful in public IP backbones
      with complex topologies.  Constraints may include bandwidth, hop
      count, delay, and administrative policy instruments such as
      resource class attributes [RFC2702], [RFC2386].  This makes it
      possible to select routes that satisfy a given set of
      requirements.  Routes computed by constraint-based routing are not
      necessarily the shortest paths.  Constraint-based routing works
      best with path-oriented technologies that support explicit
      routing, such as MPLS.

      Constraint-based routing can also be used as a way to distribute
      traffic onto the infrastructure, including for best effort
      traffic.  For example, congestion problems caused by uneven
      traffic distribution may be avoided or reduced by knowing the

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      reservable bandwidth attributes of the network links and by
      specifying the bandwidth requirements for path selection.

   o  A number of enhancements to the link state IGPs are needed to
      allow them to distribute additional state information required for
      constraint-based routing.  The extensions to OSPF are described in
      [RFC3630], and to IS-IS in [RFC5305].  Some of the additional
      topology state information includes link attributes such as
      reservable bandwidth and link resource class attribute (an
      administratively specified property of the link).  The resource
      class attribute concept is defined in [RFC2702].  The additional
      topology state information is carried in new TLVs and sub-TLVs in
      IS-IS, or in the Opaque LSA in OSPF [RFC5305], [RFC3630].

      An enhanced link-state IGP may flood information more frequently
      than a normal IGP.  This is because even without changes in
      topology, changes in reservable bandwidth or link affinity can
      trigger the enhanced IGP to initiate flooding.  A trade-off
      between the timeliness of the information flooded and the flooding
      frequency is typically implemented using a threshold based on the
      percentage change of the advertised resources to avoid excessive
      consumption of link bandwidth and computational resources, and to
      avoid instability in the TED.

   o  In a TE system, it is also desirable for the routing subsystem to
      make the load splitting ratio among multiple paths (with equal
      cost or different cost) configurable.  This capability gives
      network administrators more flexibility in the control of traffic
      distribution across the network.  It can be very useful for
      avoiding/relieving congestion in certain situations.  Examples can
      be found in [XIAO] and [I-D.ietf-bess-evpn-unequal-lb].

   o  The routing system should also have the capability to control the
      routes of subsets of traffic without affecting the routes of other
      traffic if sufficient resources exist for this purpose.  This
      capability allows a more refined control over the distribution of
      traffic across the network.  For example, the ability to move
      traffic away from its original path to another path (without
      affecting other traffic paths) allows the traffic to be moved from
      resource-poor network segments to resource-rich segments.  Path
      oriented technologies such as MPLS-TE inherently support this
      capability as discussed in [AWD2].

   o  Additionally, the routing subsystem should be able to select
      different paths for different classes of traffic (or for different
      traffic behavior aggregates) if the network supports multiple
      classes of service (different behavior aggregates).

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6.3.  Traffic Mapping Recommendations

   Traffic mapping is the assignment of traffic workload onto pre-
   established paths to meet certain requirements.  Thus, while
   constraint-based routing deals with path selection, traffic mapping
   deals with the assignment of traffic to established paths which may
   have been generated by constraint-based routing or by some other
   means.  Traffic mapping can be performed by time-dependent or state-
   dependent mechanisms, as described in Section 5.1.

   An important aspect of the traffic mapping function is the ability to
   establish multiple paths between an originating node and a
   destination node, and the capability to distribute the traffic
   between the two nodes across the paths according to some policies.  A
   pre-condition for this scheme is the existence of flexible mechanisms
   to partition traffic and then assign the traffic partitions onto the
   parallel paths as noted in [RFC2702].  When traffic is assigned to
   multiple parallel paths, it is recommended that special care should
   be taken to ensure proper ordering of packets belonging to the same
   application (or micro-flow) at the destination node of the parallel

   Mechanisms that perform the traffic mapping functions should aim to
   map the traffic onto the network infrastructure to minimize
   congestion.  If the total traffic load cannot be accommodated, or if
   the routing and mapping functions cannot react fast enough to
   changing traffic conditions, then a traffic mapping system may use
   short time scale congestion control mechanisms (such as queue
   management, scheduling, etc.) to mitigate congestion.  Thus,
   mechanisms that perform the traffic mapping functions complement
   existing congestion control mechanisms.  In an operational network,
   traffic should be mapped onto the infrastructure such that intra-
   class and inter-class resource contention are minimized (see
   Section 2).

   When traffic mapping techniques that depend on dynamic state feedback
   (e.g., MATE [MATE] and such like) are used, special care must be
   taken to guarantee network stability.

6.4.  Measurement Recommendations

   The importance of measurement in traffic engineering has been
   discussed throughout this document.  A TE system should include
   mechanisms to measure and collect statistics from the network to
   support the TE function.  Additional capabilities may be needed to
   help in the analysis of the statistics.  The actions of these
   mechanisms should not adversely affect the accuracy and integrity of

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   the statistics collected.  The mechanisms for statistical data
   acquisition should also be able to scale as the network evolves.

   Traffic statistics may be classified according to long-term or short-
   term timescales.  Long-term traffic statistics are very useful for
   traffic engineering.  Long-term traffic statistics may periodicity
   record network workload (such as hourly, daily, and weekly variations
   in traffic profiles) as well as traffic trends.  Aspects of the
   traffic statistics may also describe class of service characteristics
   for a network supporting multiple classes of service.  Analysis of
   the long-term traffic statistics may yield other information such as
   busy hour characteristics, traffic growth patterns, persistent
   congestion problems, hot-spot, and imbalances in link utilization
   caused by routing anomalies.

   A mechanism for constructing traffic matrices for both long-term and
   short-term traffic statistics should be in place.  In multi-service
   IP networks, the traffic matrices may be constructed for different
   service classes.  Each element of a traffic matrix represents a
   statistic about the traffic flow between a pair of abstract nodes.
   An abstract node may represent a router, a collection of routers, or
   a site in a VPN.

   Traffic statistics should provide reasonable and reliable indicators
   of the current state of the network on the short-term scale.  Some
   short term traffic statistics may reflect link utilization and link
   congestion status.  Examples of congestion indicators include
   excessive packet delay, packet loss, and high resource utilization.
   Examples of mechanisms for distributing this kind of information
   include SNMP, probing tools, FTP, IGP link state advertisements, and
   Netconf/Restconf, etc.

6.5.  Network Survivability

   Network survivability refers to the capability of a network to
   maintain service continuity in the presence of faults.  This can be
   accomplished by promptly recovering from network impairments and
   maintaining the required QoS for existing services after recovery.
   Survivability is an issue of great concern within the Internet
   community due to the demand to carry mission critical traffic, real-
   time traffic, and other high priority traffic over the Internet.
   Survivability can be addressed at the device level by developing
   network elements that are more reliable; and at the network level by
   incorporating redundancy into the architecture, design, and operation
   of networks.  It is recommended that a philosophy of robustness and
   survivability should be adopted in the architecture, design, and
   operation of traffic engineering that control IP networks (especially
   public IP networks).  Because different contexts may demand different

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   levels of survivability, the mechanisms developed to support network
   survivability should be flexible so that they can be tailored to
   different needs.  A number of tools and techniques have been
   developed to enable network survivability including MPLS Fast Reroute
   [RFC4090], RSVP-TE Extensions in Support of End-to-End GMPLS Recovery
   [RFC4872], and GMPLS Segment Recovery [RFC4873].

   The impact of service outages varies significantly for different
   service classes depending on the duration of the outage which can
   vary from milliseconds (with minor service impact) to seconds (with
   possible call drops for IP telephony and session time-outs for
   connection oriented transactions) to minutes and hours (with
   potentially considerable social and business impact).  Different
   duration outages have different impacts depending on the throughput
   of the traffic flows that are interrupted.

   Failure protection and restoration capabilities are available in
   multiple layers as network technologies have continued to evolve.
   Optical networks are capable of providing dynamic ring and mesh
   restoration functionality at the wavelength level.  At the SONET/SDH
   layer survivability capability is provided with Automatic Protection
   Switching (APS) as well as self-healing ring and mesh architectures.
   Similar functionality is provided by layer 2 technologies such as

   Rerouting is used at the IP layer to restore service following link
   and node outages.  Rerouting at the IP layer occurs after a period of
   routing convergence which may require seconds to minutes to complete.
   Path-oriented technologies such a MPLS ([RFC3469]) can be used to
   enhance the survivability of IP networks in a potentially cost
   effective manner.

   An important of multi-layer survivability is that technologies at
   different layers may provide protection and restoration capabilities
   at different granularities in terms of time scales and at different
   bandwidth granularity (from packet-level to wavelength level).
   Protection and restoration capabilities can also be sensitive to
   different service classes and different network utility models.
   Coordinating different protection and restoration capabilities across
   multiple layers in a cohesive manner to ensure network survivability
   is maintained at reasonable cost is a challenging task.  Protection
   and restoration coordination across layers may not always be
   feasible, because networks at different layers may belong to
   different administrative domains.

   The following paragraphs present some of the general recommendations
   for protection and restoration coordination.

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   o  Protection and restoration capabilities from different layers
      should be coordinated to provide network survivability in a
      flexible and cost effective manner.  Avoiding duplication of
      functions in different layers is one way to achieve the
      coordination.  Escalation of alarms and other fault indicators
      from lower to higher layers may also be performed in a coordinated
      manner.  The order of timing of restoration triggers from
      different layers is another way to coordinate multi-layer

   o  Network capacity reserved in one layer to provide protection and
      restoration is not available to carry traffic in a higher layer:
      it is not visible as spare capacity in the higher layer.  Placing
      protection/restoration functions in many layers may increase
      redundancy and robustness, but it can result in significant
      inefficiencies in network resource utilization.  Careful planning
      is needed to balance the trade-off between the desire for
      survivablity and the optimal use of resources.

   o  It is generally desirable to have protection and restoration
      schemes that are intrinsically bandwidth efficient.

   o  Failure notifications throughout the network should be timely and
      reliable if they are to be acted on as triggers for effective
      protection and restoration actions.

   o  Alarms and other fault monitoring and reporting capabilities
      should be provided at the right network layers so that the
      protection and restoration actions can be taken in those layers.

6.5.1.  Survivability in MPLS Based Networks

   Because MPLS is path-oriented, it has the potential to provide faster
   and more predictable protection and restoration capabilities than
   conventional hop by hop routed IP systems.  Protection types for MPLS
   networks can be divided into four categories.

   o  Link Protection: The objective of link protection is to protect an
      LSP from the failure of a given link.  Under link protection, a
      protection or backup LSP (the secondary LSP) follows a path that
      is disjoint from the path of the working or operational LSP (the
      primary LSP) at the particular link where link protection is
      required.  When the protected link fails, traffic on the working
      LSP is switched to the protection LSP at the head-end of the
      failed link.  As a local repair method, link protection can be
      fast.  This form of protection may be most appropriate in
      situations where some network elements along a given path are
      known to be less reliable than others.

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   o  Node Protection: The objective of node protection is to protect an
      LSP from the failure of a given node.  Under node protection, the
      secondary LSP follows a path that is disjoint from the path of the
      primary LSP at the particular node where node protection is
      required.  The secondary LSP is also disjoint from the primary LSP
      at all links attached to the node to be protected.  When the
      protected node fails, traffic on the working LSP is switched over
      to the protection LSP at the upstream LSR directly connected to
      the failed node.  Node protection covers a slightly larger part of
      the network compared to link protection, but is otherwise
      fundamentally the same.

   o  Path Protection: The goal of LSP path protection (or end-to-end
      protection) is to protect an LSP from any failure along its routed
      path.  Under path protection, the path of the protection LSP is
      completely disjoint from the path of the working LSP.  The
      advantage of path protection is that the backup LSP protects the
      working LSP from all possible link and node failures along the
      path, except for failures of ingress or egress LSR.  Additionally,
      path protection may be more efficient in terms of resource usage
      than link or node protection applied at every jop along the path.
      However, path protection may be slower than link and node
      protection because the fault notifications have to be propagated

   o  Segment Protection: An MPLS domain may be partitioned into
      multiple subdomains (protection domains).  Path protection is
      applied to the path of each LSP as it crosses the domain from its
      ingress to the domain to where it egresses the domain.  In cases
      where an LSP traverses multiple protection domains, a protection
      mechanism within a domain only needs to protect the segment of the
      LSP that lies within the domain.  Segment protection will
      generally be faster than end-to-end path protection because
      recovery generally occurs closer to the fault and the notification
      doesn't have to propagate as far.

   See [RFC3469] and [RFC6372] for a more comprehensive discussion of
   MPLS based recovery.

6.5.2.  Protection Options

   Another issue to consider is the concept of protection options.  We
   use notation such as "m:n protection", where m is the number of
   protection LSPs used to protect n working LSPs.  In all cases except
   1+1 protection, the resources associated with the protection LSPs can
   be used to carry preemptable best-effort traffic when the working LSP
   is functioning correctly.

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   o  1:1 protection: One working LSP is protected/restored by one
      protection LSP.

   o  1:n protection: One protection LSP is used to protect/restore n
      working LSPs.  Only one failed LSP can be restored at any time.

   o  n:1 protection: One working LSP is protected/restored by n
      protection LSPs, possibly with load splitting across the
      protection LSPs.  This may be especially useful when it is not
      feasible to find one path for the backup that can satisfy the
      bandwidth requirement of the primary LSP.

   o  1+1 protection: Traffic is sent concurrently on both the working
      LSP and a protection LSP.  The egress LSR selects one of the two
      LSPs based on local policy (usually based on traffic integrity).
      When a fault disrupts the traffic on one LSP, the egress switches
      to receive traffic from the other LSP.  This approach is expensive
      in how it consumes network but recovers from failures most

6.6.  Traffic Engineering in Diffserv Environments

   Increasing requirements to support multiple classes of traffic in the
   Internet, such as best effort and mission critical data, calls for IP
   networks to differentiate traffic according to some criteria and to
   give preferential treatment to certain types of traffic.  Large
   numbers of flows can be aggregated into a few behavior aggregates
   based on some criteria based on common performance requirements in
   terms of packet loss ratio, delay, and jitter, or in terms of common
   fields within the IP packet headers.

   Differentiated Services (Diffserv) [RFC2475] can be used to ensure
   that SLAs defined to differentiate between traffic flows are met.
   Classes of service (CoS) can be supported in a Diffserv environment
   by concatenating per-hop behaviors (PHBs) along the routing path.  A
   PHB is the forwarding behavior that a packet receives at a Diffserv-
   compliant node, and it can be configured at each router.  PHBs are
   delivered using buffer management and packet scheduling mechanisms
   and require that the ingress nodes use traffic classification,
   marking, policing, and shaping.

   Traffic engineering can compliment Diffserv to improve utilization of
   network resources.  Traffic engineering can be operated on an
   aggregated basis across all service classes [RFC3270], or on a per
   service class basis.  The former is used to provide better
   distribution of the traffic load over the network resources (see
   [RFC3270] for detailed mechanisms to support aggregate traffic
   engineering).  The latter case is discussed below since it is

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   specific to the Diffserv environment, with so called Diffserv-aware
   traffic engineering [RFC4124].

   For some Diffserv networks, it may be desirable to control the
   performance of some service classes by enforcing relationships
   between the traffic workload contributed by each service class and
   the amount of network resources allocated or provisioned for that
   service class.  Such relationships between demand and resource
   allocation can be enforced using a combination of, for example:

   o  TE mechanisms on a per service class basis that enforce the
      relationship between the amount of traffic contributed by a given
      service class and the resources allocated to that class.

   o  Mechanisms that dynamically adjust the resources allocated to a
      given service class to relate to the amount of traffic contributed
      by that service class.

   It may also be desirable to limit the performance impact of high
   priority traffic on relatively low priority traffic.  This can be
   achieved, for example, by controlling the percentage of high priority
   traffic that is routed through a given link.  Another way to
   accomplish this is to increase link capacities appropriately so that
   lower priority traffic can still enjoy adequate service quality.
   When the ratio of traffic workload contributed by different service
   classes varies significantly from router to router, it may not be
   enough to rely on conventional IGP routing protocols or on TE
   mechanisms that are not sensitive to different service classes.
   Instead, it may be desirable to perform traffic engineering,
   especially routing control and mapping functions, on a per service
   class basis.  One way to accomplish this in a domain that supports
   both MPLS and Diffserv is to define class specific LSPs and to map
   traffic from each class onto one or more LSPs that correspond to that
   service class.  An LSP corresponding to a given service class can
   then be routed and protected/restored in a class dependent manner,
   according to specific policies.

   Performing traffic engineering on a per class basis may require per-
   class parameters to be distributed.  It is common to have some
   classes share some aggregate constraints (e.g., maximum bandwidth
   requirement) without enforcing the constraint on each individual
   class.  These classes can be grouped into class-types, and per-class-
   type parameters can be distributed to improve scalability.  This also
   allows better bandwidth sharing between classes in the same class-
   type.  A class-type is a set of classes that satisfy the following
   two conditions:

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   o  Classes in the same class-type have common aggregate requirements
      to satisfy required performance levels.

   o  There is no requirement to be enforced at the level of an
      individual class in the class-type.  Note that it is,
      nevertheless, still possible to implement some priority policies
      for classes in the same class-type to permit preferential access
      to the class-type bandwidth through the use of preemption

   See [RFC4124] for detailed requirements on Diffserv-aware traffic

6.7.  Network Controllability

   Offline and online (see Section 5.2) TE considerations are of limited
   utility if the network cannot be controlled effectively to implement
   the results of TE decisions and to achieve the desired network
   performance objectives.

   Capacity augmentation is a coarse-grained solution to TE issues.
   However, it is simple and may be advantageous if bandwidth is
   abundant and cheap.  However, bandwidth is not always abundant and
   cheap, and additional capacity might not always be the best solution.
   Adjustments of administrative weights and other parameters associated
   with routing protocols provide finer-grained control, but this
   approach is difficult to use and imprecise because of the the way the
   routing protocols interact occur across the network.

   Control mechanisms can be manual (e.g., static configuration),
   partially-automated (e.g., scripts), or fully-automated (e.g., policy
   based management systems).  Automated mechanisms are particularly
   useful in large scale networks.  Multi-vendor interoperability can be
   facilitated by standardized management systems (e.g., YANG models) to
   support the control functions required to address TE objectives.

   Network control functions should be secure, reliable, and stable as
   these are often needed to operate correctly in times of network
   impairments (e.g., during network congestion or security attacks).

7.  Inter-Domain Considerations

   Inter-domain TE is concerned with performance optimization for
   traffic that originates in one administrative domain and terminates
   in a different one.

   BGP [RFC4271] is the standard exterior gateway protocol used to
   exchange routing information between autonomous systems (ASes) in the

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   Internet.  BGP includes a sequential decision process that calculates
   the preference for routes to a given destination network.  There are
   two fundamental aspects to inter-domain TE using BGP:

   o  Route Redistribution: Controlling the import and export of routes
      between ASes, and controlling the redistribution of routes between
      BGP and other protocols within an AS.

   o  Best path selection: Selecting the best path when there are
      multiple candidate paths to a given destination network.  This is
      performed by the BGP decision process, selecting preferred exit
      points out of an AS towards specific destination networks taking a
      number of different considerations into account.  The BGP path
      selection process can be influenced by manipulating the attributes
      associated with the process, including NEXT-HOP, WEIGHT, LOCAL-
      IGP METRIC, etc.

   Route-maps provide the flexibility to implement complex BGP policies
   based on pre-configured logical conditions.  They can be used to
   control import and export policies for incoming and outgoing routes,
   control the redistribution of routes between BGP and other protocols,
   and influence the selection of best paths by manipulating the
   attributes associated with the BGP decision process.  Very complex
   logical expressions that implement various types of policies can be
   implemented using a combination of Route-maps, BGP-attributes,
   Access-lists, and Community attributes.

   When considering inter-domain TE with BGP, note that the outbound
   traffic exit point is controllable, whereas the interconnection point
   where inbound traffic is received typically is not.  Therefore, it is
   up to each individual network to implement TE strategies that deal
   with the efficient delivery of outbound traffic from its customers to
   its peering points.  The vast majority of TE policy is based on a
   "closest exit" strategy, which offloads interdomain traffic at the
   nearest outbound peering point towards the destination AS.  Most
   methods of manipulating the point at which inbound traffic enters a
   are either ineffective, or not accepted in the peering community.

   Inter-domain TE with BGP is generally effective, but it is usually
   applied in a trial-and-error fashion because a TE system usually only
   has a view of the available network resources within one domain (an
   AS in this case).  A systematic approach for inter-domain TE requires
   cooperation between the domains.  Further, what may be considered a
   good solution in one domain may not necessarily be a good solution in
   another.  Moreover, it is generally considered inadvisable for one
   domain to permit a control process from another domain to influence
   the routing and management of traffic in its network.

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   MPLS TE-tunnels (LSPs) can add a degree of flexibility in the
   selection of exit points for inter-domain routing by applying rhe
   concept of relative and absolute metrics.  If BGP attributes are
   defined such that the BGP decision process depends on IGP metrics to
   select exit points for inter-domain traffic, then some inter-domain
   traffic destined to a given peer network can be made to prefer a
   specific exit point by establishing a TE-tunnel between the router
   making the selection and the peering point via a TE-tunnel and
   assigning the TE-tunnel a metric which is smaller than the IGP cost
   to all other peering points.

   Similarly to intra-domain TE, inter-domain TE is best accomplished
   when a traffic matrix can be derived to depict the volume of traffic
   from one AS to another.

8.  Overview of Contemporary TE Practices in Operational IP Networks

   This section provides an overview of some traffic engineering
   practices in IP networks.  The focus is on aspects of control of the
   routing function in operational contexts.  The intent here is to
   provide an overview of the commonly used practices: the discussion is
   not intended to be exhaustive.

   Service providers apply many of the traffic engineering mechanisms
   described in this document to optimize the performance of their IP
   networks.  These techniques include capacity planning for long
   timescales; routing control using IGP metrics and MPLS, as well as
   path planning and path control using MPLS and Segment Routing for
   medium timescales; and traffic management mechanisms for short

   Capacity planning is an important component of how a service provider
   plans an effective IP network.  These plans may take the following
   aspects into account: location of and new links or nodes, existing
   and predicted traffic patterns, costs, link capacity, topology,
   routing design, and survivability.

   Performance optimization of operational networks is usually an
   ongoing process in which traffic statistics, performance parameters,
   and fault indicators are continually collected from the network.
   This empirical data is analyzed and used to trigger TE mechanisms.
   Tools that perform what-if analysis can also be used to assist the TE
   process by reviewing scenarios before a new set of configurations are
   implemented in the operational network.

   Real-time intra-domain TE using the IGP is done by increasing the
   OSPF or IS-IS metric of a congested link until enough traffic has
   been diverted away from that link.  This approach has some

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   limitations as discussed in Section 6.2.  Intra-domain TE approaches
   ([RR94] [FT00] [FT01] [WANG]) take traffic matrix, network topology,
   and network performance objectives as input, and produce link metrics
   and load-sharing ratios.  These processes open the possibility for
   intra-domain TE with IGP to be done in a more systematic way.

   Administrators of MPLS-TE networks specify and configure link
   attributes and resource constraints such as maximum reservable
   bandwidth and resource class attributes for the links in the domain.
   A link state IGP that supports TE extensions (IS-IS-TE or OSPF-TE) is
   used to propagate information about network topology and link
   attributes to all routers in the domain.  Network administrators
   specify the LSPs that are to originate at each router.  For each LSP,
   the network administrator specifies the destination node and the
   attributes of the LSP which indicate the requirements that are to be
   satisfied during the path selection process.  The attributes may
   include and explicit path for the LSP to follow, or originating
   router uses a local constraint-based routing process to compute the
   path of the LSP.  RSVP-TE is used as a signaling protocol to
   instantiate the LSPs.  By assigning proper bandwidth values to links
   and LSPs, congestion caused by uneven traffic distribution can be
   avoided or mitigated.

   The bandwidth attributes of an LSP relates to the bandwidth
   requirements of traffic that flows through the LSP.  The traffic
   attribute of an LSP can be modified to accommodate persistent shifts
   in demand (traffic growth or reduction).  If network congestion
   occurs due to some unexpected events, existing LSPs can be rerouted
   to alleviate the situation or network administrator can configure new
   LSPs to divert some traffic to alternative paths.  The reservable
   bandwidth of the congested links can also be reduced to force some
   LSPs to be rerouted to other paths.  A traffic matrix in an MPLS
   domain can also be estimated by monitoring the traffic on LSPs.  Such
   traffic statistics can be used for a variety of purposes including
   network planning and network optimization.

   Network management and planning systems have evolved and taken over a
   lot of the responsibility for determining traffic paths in TE
   networks.  This allows a network-wide view of resources, and
   facilitates coordination of the use of resources for all traffic
   flows in the network.  Initial solutions using a PCE to perform path
   computation on behalf of network routers have given way to an
   approach that follows the SDN architecture.  A stateful PCE is able
   to track all of the LSPs in the network and can redistribute them to
   make better use of the available resources.  Such a PCE can forms
   part of a network orchestrator that uses PCEP or some other
   southbound interface to instruct the signaling protocol or directly
   program the routers.

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   Segment routing leverages a centralized TE controller and either an
   MPLS or IPv6 forwarding plane, but does not need to use a signaling
   protocol or management plane protocol to reserve resources in the
   routers.  All resource reservation is logical within the controller,
   and not distributed to the routers.  Packets are steered through the
   network using segment routing.

   As mentioned in Section 7, there is usually no direct control over
   the distribution of inbound traffic to a domain.  Therefore, the main
   goal of inter-domain TE is to optimize the distribution of outbound
   traffic between multiple inter-domain links.  When operating a global
   network, maintaining the ability to operate the network in a regional
   fashion where desired, while continuing to take advantage of the
   benefits of a global network, also becomes an important objective.

   Inter-domain TE with BGP begins with the placement of multiple
   peering interconnection points that are in close proximity to traffic
   sources/destination, and offer lowest cost paths across the network
   between the peering points and and the sources/destinations.  Some
   location-decision problems that arise in association with inter-
   domain routing are discussed in [AWD5].

   Once the locations of the peering interconnects have been determined
   and implemented, the network operator decides how best to handle the
   routes advertised by the peer, as well as how to propagate the peer's
   routes within their network.  One way to engineer outbound traffic
   flows in a network with many peering interconnects is to create a
   hierarchy of peers.  Generally, the shortest AS paths will be chosen
   to forward traffic but BGP metrics can be used to prefer some peers
   and so favor particular paths.  Preferred peers are those peers
   attached through peering interconnects with the most available
   capacity.  Changes may be needed, for example, to deal with a
   "problem peer" who is difficult to work with on upgrades or is
   charging high prices for connectivity to their network.  In that
   case, the peer may be given a reduced preference.  This type of
   change can affect a large amount of traffic, and is only used after
   other methods have failed to provide the desired results.

   When there are multiple exit points toward a given peer, and only one
   of them is congested, it is not necessary to shift traffic away from
   the peer entirely, but only from the one congested connections.  This
   can be achieved by using passive IGP-metrics, AS-path filtering, or
   prefix filtering.

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9.  Security Considerations

   This document does not introduce new security issues.

   Network security is, of course, an important issue.  In general, TE
   mechanisms are security neutral: they may use tunnels which can
   slightly help protect traffic from inspection and which, in some
   cases, can be secured using encryption; they put traffic onto
   predictable paths within the network that may make it easier to find
   and attack; they increase the complexity or operation and management
   of the network; and they enable traffic to be steered onto more
   secure links or to more secure parts of the network.

   The consequences of attacks on the control and management protocols
   used to operate TE networks can be significant: traffic can be
   hijacked to pass through specific nodes that perform inspection, or
   even to be delivered to the wrong place; traffic can be steered onto
   paths that deliver quality that is below the desired quality; and,
   networks can be congested or have resources on key links consumed.
   Thus, it is important to use adequate protection mechanisms on all
   protocols used to deliver TE.

   Certain aspects of a network may be deduced from the details of the
   TE paths that are used.  For example, the link connectivity of the
   network, and the quality and load on individual links may be assumed
   from knowing the paths of traffic and the requirements they place on
   the network (for example, by seeing the control messages or through
   path- trace techniques).  Such knowledge can be used to launch
   targeted attacks (for example, taking down critical links) or can
   reveal commercially sensitive information (for example, whether a
   network is close to capacity).  Network operators may, therefore,
   choose techniques that mask or hide information from within the

10.  IANA Considerations

   This draft makes no requests for IANA action.

11.  Acknowledgments

   Much of the text in this document is derived from RFC 3272.  The
   authors of this document would like to express their gratitude to all
   involved in that work.  Although the source text has been edited in
   the production of this document, the original authors should be
   considered as Contributors to this work.  They were:

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      Daniel O. Awduche
      Movaz Networks

      Angela Chiu
      Celion Networks

      Anwar Elwalid
      Lucent Technologies

      Indra Widjaja
      Bell Labs, Lucent Technologies

      XiPeng Xiao
      Redback Networks

   The acknowledgements in RFC3272 were as below.  All people who helped
   in the production of that document also need to be thanked for the
   carry-over into this new document.

      The authors would like to thank Jim Boyle for inputs on the
      recommendations section, Francois Le Faucheur for inputs on
      Diffserv aspects, Blaine Christian for inputs on measurement,
      Gerald Ash for inputs on routing in telephone networks and for
      text on event-dependent TE methods, Steven Wright for inputs
      on network controllability, and Jonathan Aufderheide for
      inputs on inter-domain TE with BGP.  Special thanks to
      Randy Bush for proposing the TE taxonomy based on "tactical versus
      strategic" methods.  The subsection describing an "Overview of
      ITU Activities Related to Traffic Engineering" was adapted from
      a contribution by Waisum Lai.  Useful feedback and pointers to
      relevant materials were provided by J. Noel Chiappa.
      Additional comments were provided by Glenn Grotefeld during
      the working last call process.  Finally, the authors would like
      to thank Ed Kern, the TEWG co-chair, for his comments and

   The early versions of this document were produced by the TEAS Working
   Group's RFC3272bis Design Team.  The full list of members of this
   team is:

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       Acee Lindem
       Adrian Farrel
       Aijun Wang
       Daniele Ceccarelli
       Dieter Beller
       Jeff Tantsura
       Julien Meuric
       Liu Hua
       Loa Andersson
       Luis Miguel Contreras
       Martin Horneffer
       Tarek Saad
       Xufeng Liu

   The production of this document includes a fix to the original text
   resulting from an Errata Report by Jean-Michel Grimaldi.

   The author of this document would also like to thank Dhurv Dhody for
   review comments.

12.  Contributors

   The following people contributed substantive text to this document:

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       Gert Grammel

       Loa Andersson

       Xufeng Liu

       Lou Berger

       Jeff Tantsura

       Daniel King

       Boris Hassanov

       Kiran Makhijani

       Dhruv Dhody

13.  Informative References

   [AJ19]     Adekitan, A., Abolade, J., and O. Shobayo, "Data mining
              approach for predicting the daily Internet data traffic of
              a smart university", Article Journal of Big Data, 2019,
              Volume 6, Number 1, Page 1, 1998.

   [ASH2]     Ash, J., "Dynamic Routing in Telecommunications Networks",
              Book McGraw Hill, 1998.

   [AWD2]     Awduche, D., "MPLS and Traffic Engineering in IP
              Networks", Article IEEE Communications Magazine, December

   [AWD5]     Awduche, D., "An Approach to Optimal Peering Between
              Autonomous Systems in the Internet", Paper International
              Conference on Computer Communications and Networks
              (ICCCN'98), October 1998.

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   [FLJA93]   Floyd, S. and V. Jacobson, "Random Early Detection
              Gateways for Congestion Avoidance", Article IEEE/ACM
              Transactions on Networking, Vol. 1, p. 387-413, November

   [FLOY94]   Floyd, S., "TCP and Explicit Congestion Notification",
              Article ACM Computer Communication Review, V. 24, No. 5,
              p. 10-23, October 1994.

   [FT00]     Fortz, B. and M. Thorup, "Internet Traffic Engineering by
              Optimizing OSPF Weights", Article IEEE INFOCOM 2000, March

   [FT01]     Fortz, B. and M. Thorup, "Optimizing OSPF/IS-IS Weights in
              a Changing World", n.d.,

   [HUSS87]   Hurley, B., Seidl, C., and W. Sewel, "A Survey of Dynamic
              Routing Methods for Circuit-Switched Traffic",
              Article IEEE Communication Magazine, September 1987.

              WU, Q., Yang, Y., Lee, Y., Dhody, D., Randriamasy, S., and
              L. Contreras, "ALTO Performance Cost Metrics", draft-ietf-
              alto-performance-metrics-14 (work in progress), January

              Malhotra, N., Sajassi, A., Rabadan, J., Drake, J.,
              Lingala, A., and S. Thoria, "Weighted Multi-Path
              Procedures for EVPN All-Active Multi-Homing", draft-ietf-
              bess-evpn-unequal-lb-07 (work in progress), October 2020.

              Varga, B., Farkas, J., Malis, A., and S. Bryant, "DetNet
              Data Plane: IP over IEEE 802.1 Time Sensitive Networking
              (TSN)", draft-ietf-detnet-ip-over-tsn-05 (work in
              progress), December 2020.

              Previdi, S., Filsfils, C., Talaulikar, K., Mattes, P.,
              Rosen, E., Jain, D., and S. Lin, "Advertising Segment
              Routing Policies in BGP", draft-ietf-idr-segment-routing-
              te-policy-11 (work in progress), November 2020.

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              Psenak, P., Hegde, S., Filsfils, C., Talaulikar, K., and
              A. Gulko, "IGP Flexible Algorithm", draft-ietf-lsr-flex-
              algo-13 (work in progress), October 2020.

              Britto, W., Hegde, S., Kaneriya, P., Shetty, R., Bonica,
              R., and P. Psenak, "IGP Flexible Algorithms (Flex-
              Algorithm) In IP Networks", draft-ietf-lsr-ip-flexalgo-00
              (work in progress), December 2020.

              Iyengar, J. and M. Thomson, "QUIC: A UDP-Based Multiplexed
              and Secure Transport", draft-ietf-quic-transport-34 (work
              in progress), January 2021.

              Filsfils, C., Talaulikar, K., Voyer, D., Bogdanov, A., and
              P. Mattes, "Segment Routing Policy Architecture", draft-
              ietf-spring-segment-routing-policy-09 (work in progress),
              November 2020.

              Dong, J., Bryant, S., Li, Z., Miyasaka, T., and Y. Lee, "A
              Framework for Enhanced Virtual Private Networks (VPN+)
              Service", draft-ietf-teas-enhanced-vpn-06 (work in
              progress), July 2020.

              Ash, G., "Traffic Engineering & QoS Methods for IP-, ATM-,
              & Based Multiservice Networks", draft-ietf-tewg-qos-
              routing-04 (work in progress), October 2001.

              Clemm, A., Ciavaglia, L., Granville, L., and J. Tantsura,
              "Intent-Based Networking - Concepts and Definitions",
              draft-irtf-nmrg-ibn-concepts-definitions-02 (work in
              progress), September 2020.

              Rokui, R., Homma, S., Makhijani, K., Contreras, L., and J.
              Tantsura, "Definition of IETF Network Slices", draft-nsdt-
              teas-ietf-network-slice-definition-02 (work in progress),
              December 2020.

              "Terms and Definitions of Traffic Engineering",
              Recommendation ITU-T Recommendation E.600, March 1993.

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              "Reference Connections for Traffic Engineering",
              Recommendation ITU-T Recommendation E.701, October 1993.

              "Framework for Service Quality Agreement",
              Recommendation ITU-T Recommendation E.801, October 1996.

   [MA]       Ma, Q., "Quality of Service Routing in Integrated Services
              Networks", Ph.D. PhD Dissertation, CMU-CS-98-138, CMU,

   [MATE]     Elwalid, A., Jin, C., Low, S., and I. Widjaja, "MATE -
              MPLS Adaptive Traffic Engineering",
              Proceedings INFOCOM'01, April 2001.

   [MCQ80]    McQuillan, J., Richer, I., and E. Rosen, "The New Routing
              Algorithm for the ARPANET", Transaction IEEE Transactions
              on Communications, vol. 28, no. 5, p. 711-719, May 1980.

   [MR99]     Mitra, D. and K. Ramakrishnan, "A Case Study of
              Multiservice, Multipriority Traffic Engineering Design for
              Data Networks", Proceedings Globecom'99, December 1999.

   [RFC0791]  Postel, J., "Internet Protocol", STD 5, RFC 791,
              DOI 10.17487/RFC0791, September 1981,

   [RFC1102]  Clark, D., "Policy routing in Internet protocols",
              RFC 1102, DOI 10.17487/RFC1102, May 1989,

   [RFC1104]  Braun, H., "Models of policy based routing", RFC 1104,
              DOI 10.17487/RFC1104, June 1989,

   [RFC1992]  Castineyra, I., Chiappa, N., and M. Steenstrup, "The
              Nimrod Routing Architecture", RFC 1992,
              DOI 10.17487/RFC1992, August 1996,

   [RFC2205]  Braden, R., Ed., Zhang, L., Berson, S., Herzog, S., and S.
              Jamin, "Resource ReSerVation Protocol (RSVP) -- Version 1
              Functional Specification", RFC 2205, DOI 10.17487/RFC2205,
              September 1997, <>.

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   [RFC2328]  Moy, J., "OSPF Version 2", STD 54, RFC 2328,
              DOI 10.17487/RFC2328, April 1998,

   [RFC2330]  Paxson, V., Almes, G., Mahdavi, J., and M. Mathis,
              "Framework for IP Performance Metrics", RFC 2330,
              DOI 10.17487/RFC2330, May 1998,

   [RFC2386]  Crawley, E., Nair, R., Rajagopalan, B., and H. Sandick, "A
              Framework for QoS-based Routing in the Internet",
              RFC 2386, DOI 10.17487/RFC2386, August 1998,

   [RFC2474]  Nichols, K., Blake, S., Baker, F., and D. Black,
              "Definition of the Differentiated Services Field (DS
              Field) in the IPv4 and IPv6 Headers", RFC 2474,
              DOI 10.17487/RFC2474, December 1998,

   [RFC2475]  Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z.,
              and W. Weiss, "An Architecture for Differentiated
              Services", RFC 2475, DOI 10.17487/RFC2475, December 1998,

   [RFC2597]  Heinanen, J., Baker, F., Weiss, W., and J. Wroclawski,
              "Assured Forwarding PHB Group", RFC 2597,
              DOI 10.17487/RFC2597, June 1999,

   [RFC2678]  Mahdavi, J. and V. Paxson, "IPPM Metrics for Measuring
              Connectivity", RFC 2678, DOI 10.17487/RFC2678, September
              1999, <>.

   [RFC2702]  Awduche, D., Malcolm, J., Agogbua, J., O'Dell, M., and J.
              McManus, "Requirements for Traffic Engineering Over MPLS",
              RFC 2702, DOI 10.17487/RFC2702, September 1999,

   [RFC2722]  Brownlee, N., Mills, C., and G. Ruth, "Traffic Flow
              Measurement: Architecture", RFC 2722,
              DOI 10.17487/RFC2722, October 1999,

   [RFC2753]  Yavatkar, R., Pendarakis, D., and R. Guerin, "A Framework
              for Policy-based Admission Control", RFC 2753,
              DOI 10.17487/RFC2753, January 2000,

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   [RFC2961]  Berger, L., Gan, D., Swallow, G., Pan, P., Tommasi, F.,
              and S. Molendini, "RSVP Refresh Overhead Reduction
              Extensions", RFC 2961, DOI 10.17487/RFC2961, April 2001,

   [RFC2998]  Bernet, Y., Ford, P., Yavatkar, R., Baker, F., Zhang, L.,
              Speer, M., Braden, R., Davie, B., Wroclawski, J., and E.
              Felstaine, "A Framework for Integrated Services Operation
              over Diffserv Networks", RFC 2998, DOI 10.17487/RFC2998,
              November 2000, <>.

   [RFC3031]  Rosen, E., Viswanathan, A., and R. Callon, "Multiprotocol
              Label Switching Architecture", RFC 3031,
              DOI 10.17487/RFC3031, January 2001,

   [RFC3086]  Nichols, K. and B. Carpenter, "Definition of
              Differentiated Services Per Domain Behaviors and Rules for
              their Specification", RFC 3086, DOI 10.17487/RFC3086,
              April 2001, <>.

   [RFC3124]  Balakrishnan, H. and S. Seshan, "The Congestion Manager",
              RFC 3124, DOI 10.17487/RFC3124, June 2001,

   [RFC3209]  Awduche, D., Berger, L., Gan, D., Li, T., Srinivasan, V.,
              and G. Swallow, "RSVP-TE: Extensions to RSVP for LSP
              Tunnels", RFC 3209, DOI 10.17487/RFC3209, December 2001,

   [RFC3270]  Le Faucheur, F., Wu, L., Davie, B., Davari, S., Vaananen,
              P., Krishnan, R., Cheval, P., and J. Heinanen, "Multi-
              Protocol Label Switching (MPLS) Support of Differentiated
              Services", RFC 3270, DOI 10.17487/RFC3270, May 2002,

   [RFC3272]  Awduche, D., Chiu, A., Elwalid, A., Widjaja, I., and X.
              Xiao, "Overview and Principles of Internet Traffic
              Engineering", RFC 3272, DOI 10.17487/RFC3272, May 2002,

   [RFC3469]  Sharma, V., Ed. and F. Hellstrand, Ed., "Framework for
              Multi-Protocol Label Switching (MPLS)-based Recovery",
              RFC 3469, DOI 10.17487/RFC3469, February 2003,

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   [RFC3630]  Katz, D., Kompella, K., and D. Yeung, "Traffic Engineering
              (TE) Extensions to OSPF Version 2", RFC 3630,
              DOI 10.17487/RFC3630, September 2003,

   [RFC3945]  Mannie, E., Ed., "Generalized Multi-Protocol Label
              Switching (GMPLS) Architecture", RFC 3945,
              DOI 10.17487/RFC3945, October 2004,

   [RFC4090]  Pan, P., Ed., Swallow, G., Ed., and A. Atlas, Ed., "Fast
              Reroute Extensions to RSVP-TE for LSP Tunnels", RFC 4090,
              DOI 10.17487/RFC4090, May 2005,

   [RFC4124]  Le Faucheur, F., Ed., "Protocol Extensions for Support of
              Diffserv-aware MPLS Traffic Engineering", RFC 4124,
              DOI 10.17487/RFC4124, June 2005,

   [RFC4203]  Kompella, K., Ed. and Y. Rekhter, Ed., "OSPF Extensions in
              Support of Generalized Multi-Protocol Label Switching
              (GMPLS)", RFC 4203, DOI 10.17487/RFC4203, October 2005,

   [RFC4271]  Rekhter, Y., Ed., Li, T., Ed., and S. Hares, Ed., "A
              Border Gateway Protocol 4 (BGP-4)", RFC 4271,
              DOI 10.17487/RFC4271, January 2006,

   [RFC4594]  Babiarz, J., Chan, K., and F. Baker, "Configuration
              Guidelines for DiffServ Service Classes", RFC 4594,
              DOI 10.17487/RFC4594, August 2006,

   [RFC4655]  Farrel, A., Vasseur, J., and J. Ash, "A Path Computation
              Element (PCE)-Based Architecture", RFC 4655,
              DOI 10.17487/RFC4655, August 2006,

   [RFC4872]  Lang, J., Ed., Rekhter, Y., Ed., and D. Papadimitriou,
              Ed., "RSVP-TE Extensions in Support of End-to-End
              Generalized Multi-Protocol Label Switching (GMPLS)
              Recovery", RFC 4872, DOI 10.17487/RFC4872, May 2007,

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   [RFC4873]  Berger, L., Bryskin, I., Papadimitriou, D., and A. Farrel,
              "GMPLS Segment Recovery", RFC 4873, DOI 10.17487/RFC4873,
              May 2007, <>.

   [RFC5250]  Berger, L., Bryskin, I., Zinin, A., and R. Coltun, "The
              OSPF Opaque LSA Option", RFC 5250, DOI 10.17487/RFC5250,
              July 2008, <>.

   [RFC5305]  Li, T. and H. Smit, "IS-IS Extensions for Traffic
              Engineering", RFC 5305, DOI 10.17487/RFC5305, October
              2008, <>.

   [RFC5329]  Ishiguro, K., Manral, V., Davey, A., and A. Lindem, Ed.,
              "Traffic Engineering Extensions to OSPF Version 3",
              RFC 5329, DOI 10.17487/RFC5329, September 2008,

   [RFC5331]  Aggarwal, R., Rekhter, Y., and E. Rosen, "MPLS Upstream
              Label Assignment and Context-Specific Label Space",
              RFC 5331, DOI 10.17487/RFC5331, August 2008,

   [RFC5394]  Bryskin, I., Papadimitriou, D., Berger, L., and J. Ash,
              "Policy-Enabled Path Computation Framework", RFC 5394,
              DOI 10.17487/RFC5394, December 2008,

   [RFC5440]  Vasseur, JP., Ed. and JL. Le Roux, Ed., "Path Computation
              Element (PCE) Communication Protocol (PCEP)", RFC 5440,
              DOI 10.17487/RFC5440, March 2009,

   [RFC5541]  Le Roux, JL., Vasseur, JP., and Y. Lee, "Encoding of
              Objective Functions in the Path Computation Element
              Communication Protocol (PCEP)", RFC 5541,
              DOI 10.17487/RFC5541, June 2009,

   [RFC5557]  Lee, Y., Le Roux, JL., King, D., and E. Oki, "Path
              Computation Element Communication Protocol (PCEP)
              Requirements and Protocol Extensions in Support of Global
              Concurrent Optimization", RFC 5557, DOI 10.17487/RFC5557,
              July 2009, <>.

   [RFC5664]  Halevy, B., Welch, B., and J. Zelenka, "Object-Based
              Parallel NFS (pNFS) Operations", RFC 5664,
              DOI 10.17487/RFC5664, January 2010,

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   [RFC5693]  Seedorf, J. and E. Burger, "Application-Layer Traffic
              Optimization (ALTO) Problem Statement", RFC 5693,
              DOI 10.17487/RFC5693, October 2009,

   [RFC6107]  Shiomoto, K., Ed. and A. Farrel, Ed., "Procedures for
              Dynamically Signaled Hierarchical Label Switched Paths",
              RFC 6107, DOI 10.17487/RFC6107, February 2011,

   [RFC6119]  Harrison, J., Berger, J., and M. Bartlett, "IPv6 Traffic
              Engineering in IS-IS", RFC 6119, DOI 10.17487/RFC6119,
              February 2011, <>.

   [RFC6241]  Enns, R., Ed., Bjorklund, M., Ed., Schoenwaelder, J., Ed.,
              and A. Bierman, Ed., "Network Configuration Protocol
              (NETCONF)", RFC 6241, DOI 10.17487/RFC6241, June 2011,

   [RFC6372]  Sprecher, N., Ed. and A. Farrel, Ed., "MPLS Transport
              Profile (MPLS-TP) Survivability Framework", RFC 6372,
              DOI 10.17487/RFC6372, September 2011,

   [RFC6374]  Frost, D. and S. Bryant, "Packet Loss and Delay
              Measurement for MPLS Networks", RFC 6374,
              DOI 10.17487/RFC6374, September 2011,

   [RFC6805]  King, D., Ed. and A. Farrel, Ed., "The Application of the
              Path Computation Element Architecture to the Determination
              of a Sequence of Domains in MPLS and GMPLS", RFC 6805,
              DOI 10.17487/RFC6805, November 2012,

   [RFC7149]  Boucadair, M. and C. Jacquenet, "Software-Defined
              Networking: A Perspective from within a Service Provider
              Environment", RFC 7149, DOI 10.17487/RFC7149, March 2014,

   [RFC7285]  Alimi, R., Ed., Penno, R., Ed., Yang, Y., Ed., Kiesel, S.,
              Previdi, S., Roome, W., Shalunov, S., and R. Woundy,
              "Application-Layer Traffic Optimization (ALTO) Protocol",
              RFC 7285, DOI 10.17487/RFC7285, September 2014,

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   [RFC7390]  Rahman, A., Ed. and E. Dijk, Ed., "Group Communication for
              the Constrained Application Protocol (CoAP)", RFC 7390,
              DOI 10.17487/RFC7390, October 2014,

   [RFC7426]  Haleplidis, E., Ed., Pentikousis, K., Ed., Denazis, S.,
              Hadi Salim, J., Meyer, D., and O. Koufopavlou, "Software-
              Defined Networking (SDN): Layers and Architecture
              Terminology", RFC 7426, DOI 10.17487/RFC7426, January
              2015, <>.

   [RFC7471]  Giacalone, S., Ward, D., Drake, J., Atlas, A., and S.
              Previdi, "OSPF Traffic Engineering (TE) Metric
              Extensions", RFC 7471, DOI 10.17487/RFC7471, March 2015,

   [RFC7491]  King, D. and A. Farrel, "A PCE-Based Architecture for
              Application-Based Network Operations", RFC 7491,
              DOI 10.17487/RFC7491, March 2015,

   [RFC7575]  Behringer, M., Pritikin, M., Bjarnason, S., Clemm, A.,
              Carpenter, B., Jiang, S., and L. Ciavaglia, "Autonomic
              Networking: Definitions and Design Goals", RFC 7575,
              DOI 10.17487/RFC7575, June 2015,

   [RFC7679]  Almes, G., Kalidindi, S., Zekauskas, M., and A. Morton,
              Ed., "A One-Way Delay Metric for IP Performance Metrics
              (IPPM)", STD 81, RFC 7679, DOI 10.17487/RFC7679, January
              2016, <>.

   [RFC7680]  Almes, G., Kalidindi, S., Zekauskas, M., and A. Morton,
              Ed., "A One-Way Loss Metric for IP Performance Metrics
              (IPPM)", STD 82, RFC 7680, DOI 10.17487/RFC7680, January
              2016, <>.

   [RFC7752]  Gredler, H., Ed., Medved, J., Previdi, S., Farrel, A., and
              S. Ray, "North-Bound Distribution of Link-State and
              Traffic Engineering (TE) Information Using BGP", RFC 7752,
              DOI 10.17487/RFC7752, March 2016,

   [RFC7923]  Voit, E., Clemm, A., and A. Gonzalez Prieto, "Requirements
              for Subscription to YANG Datastores", RFC 7923,
              DOI 10.17487/RFC7923, June 2016,

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   [RFC7926]  Farrel, A., Ed., Drake, J., Bitar, N., Swallow, G.,
              Ceccarelli, D., and X. Zhang, "Problem Statement and
              Architecture for Information Exchange between
              Interconnected Traffic-Engineered Networks", BCP 206,
              RFC 7926, DOI 10.17487/RFC7926, July 2016,

   [RFC7950]  Bjorklund, M., Ed., "The YANG 1.1 Data Modeling Language",
              RFC 7950, DOI 10.17487/RFC7950, August 2016,

   [RFC8040]  Bierman, A., Bjorklund, M., and K. Watsen, "RESTCONF
              Protocol", RFC 8040, DOI 10.17487/RFC8040, January 2017,

   [RFC8051]  Zhang, X., Ed. and I. Minei, Ed., "Applicability of a
              Stateful Path Computation Element (PCE)", RFC 8051,
              DOI 10.17487/RFC8051, January 2017,

   [RFC8189]  Randriamasy, S., Roome, W., and N. Schwan, "Multi-Cost
              Application-Layer Traffic Optimization (ALTO)", RFC 8189,
              DOI 10.17487/RFC8189, October 2017,

   [RFC8231]  Crabbe, E., Minei, I., Medved, J., and R. Varga, "Path
              Computation Element Communication Protocol (PCEP)
              Extensions for Stateful PCE", RFC 8231,
              DOI 10.17487/RFC8231, September 2017,

   [RFC8259]  Bray, T., Ed., "The JavaScript Object Notation (JSON) Data
              Interchange Format", STD 90, RFC 8259,
              DOI 10.17487/RFC8259, December 2017,

   [RFC8281]  Crabbe, E., Minei, I., Sivabalan, S., and R. Varga, "Path
              Computation Element Communication Protocol (PCEP)
              Extensions for PCE-Initiated LSP Setup in a Stateful PCE
              Model", RFC 8281, DOI 10.17487/RFC8281, December 2017,

   [RFC8283]  Farrel, A., Ed., Zhao, Q., Ed., Li, Z., and C. Zhou, "An
              Architecture for Use of PCE and the PCE Communication
              Protocol (PCEP) in a Network with Central Control",
              RFC 8283, DOI 10.17487/RFC8283, December 2017,

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   [RFC8402]  Filsfils, C., Ed., Previdi, S., Ed., Ginsberg, L.,
              Decraene, B., Litkowski, S., and R. Shakir, "Segment
              Routing Architecture", RFC 8402, DOI 10.17487/RFC8402,
              July 2018, <>.

   [RFC8453]  Ceccarelli, D., Ed. and Y. Lee, Ed., "Framework for
              Abstraction and Control of TE Networks (ACTN)", RFC 8453,
              DOI 10.17487/RFC8453, August 2018,

   [RFC8570]  Ginsberg, L., Ed., Previdi, S., Ed., Giacalone, S., Ward,
              D., Drake, J., and Q. Wu, "IS-IS Traffic Engineering (TE)
              Metric Extensions", RFC 8570, DOI 10.17487/RFC8570, March
              2019, <>.

   [RFC8571]  Ginsberg, L., Ed., Previdi, S., Wu, Q., Tantsura, J., and
              C. Filsfils, "BGP - Link State (BGP-LS) Advertisement of
              IGP Traffic Engineering Performance Metric Extensions",
              RFC 8571, DOI 10.17487/RFC8571, March 2019,

   [RFC8655]  Finn, N., Thubert, P., Varga, B., and J. Farkas,
              "Deterministic Networking Architecture", RFC 8655,
              DOI 10.17487/RFC8655, October 2019,

   [RFC8661]  Bashandy, A., Ed., Filsfils, C., Ed., Previdi, S.,
              Decraene, B., and S. Litkowski, "Segment Routing MPLS
              Interworking with LDP", RFC 8661, DOI 10.17487/RFC8661,
              December 2019, <>.

   [RFC8664]  Sivabalan, S., Filsfils, C., Tantsura, J., Henderickx, W.,
              and J. Hardwick, "Path Computation Element Communication
              Protocol (PCEP) Extensions for Segment Routing", RFC 8664,
              DOI 10.17487/RFC8664, December 2019,

   [RFC8685]  Zhang, F., Zhao, Q., Gonzalez de Dios, O., Casellas, R.,
              and D. King, "Path Computation Element Communication
              Protocol (PCEP) Extensions for the Hierarchical Path
              Computation Element (H-PCE) Architecture", RFC 8685,
              DOI 10.17487/RFC8685, December 2019,

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   [RFC8795]  Liu, X., Bryskin, I., Beeram, V., Saad, T., Shah, H., and
              O. Gonzalez de Dios, "YANG Data Model for Traffic
              Engineering (TE) Topologies", RFC 8795,
              DOI 10.17487/RFC8795, August 2020,

   [RFC8896]  Randriamasy, S., Yang, R., Wu, Q., Deng, L., and N.
              Schwan, "Application-Layer Traffic Optimization (ALTO)
              Cost Calendar", RFC 8896, DOI 10.17487/RFC8896, November
              2020, <>.

   [RFC8938]  Varga, B., Ed., Farkas, J., Berger, L., Malis, A., and S.
              Bryant, "Deterministic Networking (DetNet) Data Plane
              Framework", RFC 8938, DOI 10.17487/RFC8938, November 2020,

   [RFC8955]  Loibl, C., Hares, S., Raszuk, R., McPherson, D., and M.
              Bacher, "Dissemination of Flow Specification Rules",
              RFC 8955, DOI 10.17487/RFC8955, December 2020,

   [RR94]     Rodrigues, M. and K. Ramakrishnan, "Optimal Routing in
              Shortest Path Networks", Proceedings ITS'94, Rio de
              Janeiro, Brazil, 1994.

   [SLDC98]   Suter, B., Lakshman, T., Stiliadis, D., and A. Choudhury,
              "Design Considerations for Supporting TCP with Per-flow
              Queueing", Proceedings INFOCOM'98, p. 299-306, 1998.

   [WANG]     Wang, Y., Wang, Z., and L. Zhang, "Internet traffic
              engineering without full mesh overlaying",
              Proceedings INFOCOM'2001, April 2001.

   [XIAO]     Xiao, X., Hannan, A., Bailey, B., and L. Ni, "Traffic
              Engineering with MPLS in the Internet", Article IEEE
              Network Magazine, March 2000.

   [YARE95]   Yang, C. and A. Reddy, "A Taxonomy for Congestion Control
              Algorithms in Packet Switching Networks", Article IEEE
              Network Magazine, p. 34-45, 1995.

Appendix A.  Historic Overview

A.1.  Traffic Engineering in Classical Telephone Networks

   This subsection presents a brief overview of traffic engineering in
   telephone networks which often relates to the way user traffic is
   steered from an originating node to the terminating node.  This

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   subsection presents a brief overview of this topic.  A detailed
   description of the various routing strategies applied in telephone
   networks is included in the book by G.  Ash [ASH2].

   The early telephone network relied on static hierarchical routing,
   whereby routing patterns remained fixed independent of the state of
   the network or time of day.  The hierarchy was intended to
   accommodate overflow traffic, improve network reliability via
   alternate routes, and prevent call looping by employing strict
   hierarchical rules.  The network was typically over-provisioned since
   a given fixed route had to be dimensioned so that it could carry user
   traffic during a busy hour of any busy day.  Hierarchical routing in
   the telephony network was found to be too rigid upon the advent of
   digital switches and stored program control which were able to manage
   more complicated traffic engineering rules.

   Dynamic routing was introduced to alleviate the routing inflexibility
   in the static hierarchical routing so that the network would operate
   more efficiently.  This resulted in significant economic gains
   [HUSS87].  Dynamic routing typically reduces the overall loss
   probability by 10 to 20 percent (compared to static hierarchical
   routing).  Dynamic routing can also improve network resilience by
   recalculating routes on a per-call basis and periodically updating

   There are three main types of dynamic routing in the telephone
   network.  They are time-dependent routing, state-dependent routing
   (SDR), and event dependent routing (EDR).

   In time-dependent routing, regular variations in traffic loads (such
   as time of day or day of week) are exploited in pre-planned routing
   tables.  In state-dependent routing, routing tables are updated
   online according to the current state of the network (e.g., traffic
   demand, utilization, etc.).  In event dependent routing, routing
   changes are triggers by events (such as call setups encountering
   congested or blocked links) whereupon new paths are searched out
   using learning models.  EDR methods are real-time adaptive, but they
   do not require global state information as does SDR.  Examples of EDR
   schemes include the dynamic alternate routing (DAR) from BT, the
   state-and-time dependent routing (STR) from NTT, and the success-to-
   the-top (STT) routing from AT&T.

   Dynamic non-hierarchical routing (DNHR) is an example of dynamic
   routing that was introduced in the AT&T toll network in the 1980's to
   respond to time-dependent information such as regular load variations
   as a function of time.  Time-dependent information in terms of load
   may be divided into three timescales: hourly, weekly, and yearly.
   Correspondingly, three algorithms are defined to pre-plan the routing

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   tables.  The network design algorithm operates over a year-long
   interval while the demand servicing algorithm operates on a weekly
   basis to fine tune link sizes and routing tables to correct forecast
   errors on the yearly basis.  At the smallest timescale, the routing
   algorithm is used to make limited adjustments based on daily traffic
   variations.  Network design and demand servicing are computed using
   offline calculations.  Typically, the calculations require extensive
   searches on possible routes.  On the other hand, routing may need
   online calculations to handle crankback.  DNHR adopts a "two-link"
   approach whereby a path can consist of two links at most.  The
   routing algorithm presents an ordered list of route choices between
   an originating switch and a terminating switch.  If a call overflows,
   a via switch (a tandem exchange between the originating switch and
   the terminating switch) would send a crankback signal to the
   originating switch.  This switch would then select the next route,
   and so on, until there are no alternative routes available in which
   the call is blocked.

A.2.  Evolution of Traffic Engineering in Packet Networks

   This subsection reviews related prior work that was intended to
   improve the performance of data networks.  Indeed, optimization of
   the performance of data networks started in the early days of the
   ARPANET.  Other early commercial networks such as SNA also recognized
   the importance of performance optimization and service

   In terms of traffic management, the Internet has been a best effort
   service environment until recently.  In particular, very limited
   traffic management capabilities existed in IP networks to provide
   differentiated queue management and scheduling services to packets
   belonging to different classes.

   In terms of routing control, the Internet has employed distributed
   protocols for intra-domain routing.  These protocols are highly
   scalable and resilient.  However, they are based on simple algorithms
   for path selection which have very limited functionality to allow
   flexible control of the path selection process.

   In the following subsections, the evolution of practical traffic
   engineering mechanisms in IP networks and its predecessors are

A.2.1.  Adaptive Routing in the ARPANET

   The early ARPANET recognized the importance of adaptive routing where
   routing decisions were based on the current state of the network
   [MCQ80].  Early minimum delay routing approaches forwarded each

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   packet to its destination along a path for which the total estimated
   transit time was the smallest.  Each node maintained a table of
   network delays, representing the estimated delay that a packet would
   experience along a given path toward its destination.  The minimum
   delay table was periodically transmitted by a node to its neighbors.
   The shortest path, in terms of hop count, was also propagated to give
   the connectivity information.

   One drawback to this approach is that dynamic link metrics tend to
   create "traffic magnets" causing congestion to be shifted from one
   location of a network to another location, resulting in oscillation
   and network instability.

A.2.2.  Dynamic Routing in the Internet

   The Internet evolved from the ARPANET and adopted dynamic routing
   algorithms with distributed control to determine the paths that
   packets should take en-route to their destinations.  The routing
   algorithms are adaptations of shortest path algorithms where costs
   are based on link metrics.  The link metric can be based on static or
   dynamic quantities.  The link metric based on static quantities may
   be assigned administratively according to local criteria.  The link
   metric based on dynamic quantities may be a function of a network
   congestion measure such as delay or packet loss.

   It was apparent early that static link metric assignment was
   inadequate because it can easily lead to unfavorable scenarios in
   which some links become congested while others remain lightly loaded.
   One of the many reasons for the inadequacy of static link metrics is
   that link metric assignment was often done without considering the
   traffic matrix in the network.  Also, the routing protocols did not
   take traffic attributes and capacity constraints into account when
   making routing decisions.  This results in traffic concentration
   being localized in subsets of the network infrastructure and
   potentially causing congestion.  Even if link metrics are assigned in
   accordance with the traffic matrix, unbalanced loads in the network
   can still occur due to a number factors including:

   o  Resources may not be deployed in the most optimal locations from a
      routing perspective.

   o  Forecasting errors in traffic volume and/or traffic distribution.

   o  Dynamics in traffic matrix due to the temporal nature of traffic
      patterns, BGP policy change from peers, etc.

   The inadequacy of the legacy Internet interior gateway routing system
   is one of the factors motivating the interest in path oriented

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   technology with explicit routing and constraint-based routing
   capability such as MPLS.

A.2.3.  ToS Routing

   Type-of-Service (ToS) routing involves different routes going to the
   same destination with selection dependent upon the ToS field of an IP
   packet [RFC2474].  The ToS classes may be classified as low delay and
   high throughput.  Each link is associated with multiple link costs
   and each link cost is used to compute routes for a particular ToS.  A
   separate shortest path tree is computed for each ToS.  The shortest
   path algorithm must be run for each ToS resulting in very expensive
   computation.  Classical ToS-based routing is now outdated as the IP
   header field has been replaced by a Diffserv field.  Effective
   traffic engineering is difficult to perform in classical ToS-based
   routing because each class still relies exclusively on shortest path
   routing which results in localization of traffic concentration within
   the network.

A.2.4.  Equal Cost Multi-Path

   Equal Cost Multi-Path (ECMP) is another technique that attempts to
   address the deficiency in the Shortest Path First (SPF) interior
   gateway routing systems [RFC2328].  In the classical SPF algorithm,
   if two or more shortest paths exist to a given destination, the
   algorithm will choose one of them.  The algorithm is modified
   slightly in ECMP so that if two or more equal cost shortest paths
   exist between two nodes, the traffic between the nodes is distributed
   among the multiple equal-cost paths.  Traffic distribution across the
   equal-cost paths is usually performed in one of two ways: (1) packet-
   based in a round-robin fashion, or (2) flow-based using hashing on
   source and destination IP addresses and possibly other fields of the
   IP header.  The first approach can easily cause out- of-order packets
   while the second approach is dependent upon the number and
   distribution of flows.  Flow-based load sharing may be unpredictable
   in an enterprise network where the number of flows is relatively
   small and less heterogeneous (for example, hashing may not be
   uniform), but it is generally effective in core public networks where
   the number of flows is large and heterogeneous.

   In ECMP, link costs are static and bandwidth constraints are not
   considered, so ECMP attempts to distribute the traffic as equally as
   possible among the equal-cost paths independent of the congestion
   status of each path.  As a result, given two equal-cost paths, it is
   possible that one of the paths will be more congested than the other.
   Another drawback of ECMP is that load sharing cannot be achieved on
   multiple paths which have non-identical costs.

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A.2.5.  Nimrod

   Nimrod was a routing system developed to provide heterogeneous
   service specific routing in the Internet, while taking multiple
   constraints into account [RFC1992].  Essentially, Nimrod was a link
   state routing protocol to support path oriented packet forwarding.
   It used the concept of maps to represent network connectivity and
   services at multiple levels of abstraction.  Mechanisms allowed
   restriction of the distribution of routing information.

   Even though Nimrod did not enjoy deployment in the public Internet, a
   number of key concepts incorporated into the Nimrod architecture,
   such as explicit routing which allows selection of paths at
   originating nodes, are beginning to find applications in some recent
   constraint-based routing initiatives.

A.3.  Development of Internet Traffic Engineering

A.3.1.  Overlay Model

   In the overlay model, a virtual-circuit network, such as Synchronous
   Optical Network / Synchronous Digital Hierarchy (SONET/SDH), Optical
   Transport Network (OTN), or Wavelength Division Multiplexing (WDM),
   provides virtual-circuit connectivity between routers that are
   located at the edges of a virtual-circuit cloud.  In this mode, two
   routers that are connected through a virtual circuit see a direct
   adjacency between themselves independent of the physical route taken
   by the virtual circuit through the ATM, frame relay, or WDM network.
   Thus, the overlay model essentially decouples the logical topology
   that routers see from the physical topology that the ATM, frame
   relay, or WDM network manages.  The overlay model based on ATM or
   frame relay enables a network administrator or an automaton to employ
   traffic engineering concepts to perform path optimization by re-
   configuring or rearranging the virtual circuits so that a virtual
   circuit on a congested or sub-optimal physical link can be re-routed
   to a less congested or more optimal one.  In the overlay model,
   traffic engineering is also employed to establish relationships
   between the traffic management parameters (e.g., Peak Cell Rate,
   Sustained Cell Rate, and Maximum Burst Size for ATM) of the virtual-
   circuit technology and the actual traffic that traverses each
   circuit.  These relationships can be established based upon known or
   projected traffic profiles, and some other factors.

Appendix B.  Overview of Traffic Engineering Related Work in Other SDOs

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B.1.  Overview of ITU Activities Related to Traffic Engineering

   This section provides an overview of prior work within the ITU-T
   pertaining to traffic engineering in traditional telecommunications

   ITU-T Recommendations E.600 [ITU-E600], E.701 [ITU-E701], and E.801
   [ITU-E801] address traffic engineering issues in traditional
   telecommunications networks.  Recommendation E.600 provides a
   vocabulary for describing traffic engineering concepts, while E.701
   defines reference connections, Grade of Service (GoS), and traffic
   parameters for ISDN.  Recommendation E.701 uses the concept of a
   reference connection to identify representative cases of different
   types of connections without describing the specifics of their actual
   realizations by different physical means.  As defined in
   Recommendation E.600, "a connection is an association of resources
   providing means for communication between two or more devices in, or
   attached to, a telecommunication network."  Also, E.600 defines "a
   resource as any set of physically or conceptually identifiable
   entities within a telecommunication network, the use of which can be
   unambiguously determined" [ITU-E600].  There can be different types
   of connections as the number and types of resources in a connection
   may vary.

   Typically, different network segments are involved in the path of a
   connection.  For example, a connection may be local, national, or
   international.  The purposes of reference connections are to clarify
   and specify traffic performance issues at various interfaces between
   different network domains.  Each domain may consist of one or more
   service provider networks.

   Reference connections provide a basis to define grade of service
   (GoS) parameters related to traffic engineering within the ITU-T
   framework.  As defined in E.600, "GoS refers to a number of traffic
   engineering variables which are used to provide a measure of the
   adequacy of a group of resources under specified conditions."  These
   GoS variables may be probability of loss, dial tone, delay, etc.
   They are essential for network internal design and operation as well
   as for component performance specification.

   GoS is different from quality of service (QoS) in the ITU framework.
   QoS is the performance perceivable by a telecommunication service
   user and expresses the user's degree of satisfaction of the service.
   QoS parameters focus on performance aspects observable at the service
   access points and network interfaces, rather than their causes within
   the network.  GoS, on the other hand, is a set of network oriented
   measures which characterize the adequacy of a group of resources
   under specified conditions.  For a network to be effective in serving

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   its users, the values of both GoS and QoS parameters must be related,
   with GoS parameters typically making a major contribution to the QoS.

   Recommendation E.600 stipulates that a set of GoS parameters must be
   selected and defined on an end-to-end basis for each major service
   category provided by a network to assist the network provider with
   improving efficiency and effectiveness of the network.  Based on a
   selected set of reference connections, suitable target values are
   assigned to the selected GoS parameters under normal and high load
   conditions.  These end-to-end GoS target values are then apportioned
   to individual resource components of the reference connections for
   dimensioning purposes.

Appendix C.  Summary of Changes Since RFC 3272

   The changes to this document since RFC 3272 are substantial and not
   easily summarized as section-by-section changes.  The material in the
   document has been moved around considerably, some of it removed, and
   new text added.

   The approach taken here is to list the table of content of both the
   previous RFC and this document saying, respectively, where the text
   has been place and where the text came from.

C.1.  RFC 3272

   1.0 Introduction:  Edited in place in Section 1.

      1.1 What is Internet Traffic Engineering?:  Edited in place in
         Section 1.1.

      1.2 Scope:  Moved to Section 1.3.

      1.3 Terminology:  Moved to Section 1.4 with some obsolete terms
         removed and a little editing.

   2.0 Background:  Retained as Section 2 with some text removed.

      2.1 Context of Internet Traffic Engineering:  Retained as
         Section 2.1.

      2.2 Network Context:  Rewritten as Section 2.2.

      2.3 Problem Context:  Rewritten as Section 2.3.

         2.3.1 Congestion and its Ramifications:  Retained as
            Section 2.3.1.

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      2.4 Solution Context:  Edited as Section 2.4.

         2.4.1 Combating the Congestion Problem:  Reformatted as
            Section 2.4.1.

      2.5 Implementation and Operational Context:  Retained as
         Section 2.5.

   3.0 Traffic Engineering Process Model:  Retained as Section 3.

      3.1 Components of the Traffic Engineering Process Model:  Retained
         as Section 3.1.

      3.2 Measurement:  Merged into Section 3.1.

      3.3 Modeling, Analysis, and Simulation:  Merged into Section 3.1.

      3.4 Optimization:  Merged into Section 3.1.

   4.0 Historical Review and Recent Developments:  Retained as
      Section 4, but the very historic aspects moved to Appendix A.

      4.1 Traffic Engineering in Classical Telephone Networks:  Moved to
         Appendix A.1.

      4.2 Evolution of Traffic Engineering in the Internet:  Moved to Ap
         pendix A.2.

         4.2.1 Adaptive Routing in ARPANET:  Moved to Appendix A.2.1.

         4.2.2 Dynamic Routing in the Internet:  Moved to
            Appendix A.2.2.

         4.2.3 ToS Routing:  Moved to Appendix A.2.3.

         4.2.4 Equal Cost Multi-Path:  Moved to Appendix A.2.4.

         4.2.5 Nimrod:  Moved to Appendix A.2.5.

      4.3 Overlay Model:  Moved to Appendix A.3.1.

      4.4 Constraint-Based Routing:  Retained as Section 4.1.1, but
         moved into Section 4.1.

      4.5 Overview of Other IETF Projects Related to Traffic
      Retained as Section 4.1 with many new subsections.

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      4.5.1 Integrated Services:  Retained as Section 4.1.2.

      4.5.2 RSVP:  Retained as Section 4.1.3 with some edits.

      4.5.3 Differentiated Services:  Retained as Section 4.1.4.

      4.5.4 MPLS:  Retained as Section 4.1.6.

      4.5.5 IP Performance Metrics:  Retained as Section 4.1.8.

      4.5.6 Flow Measurement:  Retained as Section 4.1.9 with some

      4.5.7 Endpoint Congestion Management:  Retained as Section 4.1.10.

   4.6 Overview of ITU Activities Related to Traffic Engineering:  Moved
      to Appendix B.1.

   4.7 Content Distribution:  Retained as Section 4.2.

   5.0 Taxonomy of Traffic Engineering Systems:  Retained as Section 5.

      5.1 Time-Dependent Versus State-Dependent:  Retained as
         Section 5.1.

      5.2 Offline Versus Online:  Retained as Section 5.2.

      5.3 Centralized Versus Distributed:  Retained as Section 5.3 with

      5.4 Local Versus Global:  Retained as Section 5.4.

      5.5 Prescriptive Versus Descriptive:  Retained as Section 5.5 with

      5.6 Open-Loop Versus Closed-Loop:  Retained as Section 5.6.

      5.7 Tactical vs Strategic:  Retained as Section 5.7.

   6.0 Recommendations for Internet Traffic Engineering:  Retained as
      Section 6.

      6.1 Generic Non-functional Recommendations:  Retained as
         Section 6.1.

      6.2 Routing Recommendations:  Retained as Section 6.2 with edits.

      6.3 Traffic Mapping Recommendations:  Retained as Section 6.3.

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      6.4 Measurement Recommendations:  Retained as Section 6.4.

      6.5 Network Survivability:  Retained as Section 6.5.

         6.5.1 Survivability in MPLS Based Networks:  Retained as
            Section 6.5.1.

         6.5.2 Protection Option:  Retained as Section 6.5.2.

      6.6 Traffic Engineering in Diffserv Environments:  Retained as
         Section 6.6 with edits.

      6.7 Network Controllability:  Retained as Section 6.7.

   7.0 Inter-Domain Considerations:  Retained as Section 7.

   8.0 Overview of Contemporary TE Practices in Operational IP Networks:

      Retained as Section 8.

   9.0 Conclusion:  Removed.

   10.0 Security Considerations:  Retained as Section 9 with
      considerable new text.

C.2.  This Document

   o  Section 1: Based on Section 1 of RFC 3272.

      *  Section 1.1: Based on Section 1.1 of RFC 3272.

      *  Section 1.2: New for this document.

      *  Section 1.3: Based on Section 1.2 of RFC 3272.

      *  Section 1.4: Based on Section 1.3 of RFC 3272.

   o  Section 2: Based on Section 2. of RFC 3272.

      *  Section 2.1: Based on Section 2.1 of RFC 3272.

      *  Section 2.2: Based on Section 2.2 of RFC 3272.

      *  Section 2.3: Based on Section 2.3 of RFC 3272.

         +  Section 2.3.1: Based on Section 2.3.1 of RFC 3272.

      *  Section 2.4: Based on Section 2.4 of RFC 3272.

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         +  Section 2.4.1: Based on Section 2.4.1 of RFC 327

      *  Section 2.5: Based on Section 2.5 of RFC 3272.

   o  Section 3: Based on Section 3 of RFC 3272.

      *  Section 3.1: Based on Sections 3.1, 3.2, 3.3, and 3.4 of RFC

   o  Section 4: Based on Section 4 of RFC 3272.

      *  Section 4.1: Based on Section 4.5 of RFC 3272.

         +  Section 4.1.1: Based on Section 4.4 of RFC 3272.

            -  Section New for this document.

         +  Section 4.1.2: Based on Section 4.5.1 of RFC 3272.

         +  Section 4.1.3: Based on Section 4.5.2 of RFC 3272.

         +  Section 4.1.4: Based on Section 4.5.3 of RFC 3272.

         +  Section 4.1.5: New for this document.

         +  Section 4.1.6: Based on Section 4.5.4 of RFC 3272.

         +  Section 4.1.7: New for this document.

         +  Section 4.1.8: Based on Section 4.5.5 of RFC 3272.

         +  Section 4.1.9: Based on Section 4.5.6 of RFC 3272.

         +  Section 4.1.10: Based on Section 4.5.7 of RFC 3272.

         +  Section 4.1.11: New for this document.

         +  Section 4.1.12: New for this document.

         +  Section 4.1.13: New for this document.

         +  Section 4.1.14: New for this document.

         +  Section 4.1.15: New for this document.

         +  Section 4.1.16: New for this document.

            -  Section New for this document.

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            -  Section New for this document.

         +  Section 4.1.17: New for this document.

         +  Section 4.1.18: New for this document.

         +  Section 4.1.19: New for this document.

         +  Section 4.1.20: New for this document.

         +  Section 4.1.21: New for this document.

      *  Section 4.2: Based on Section 4.7 of RFC 3272.

   o  Section 5: Based on Section 5 of RFC 3272.

      *  Section 5.1: Based on Section 5.1 of RFC 3272.

      *  Section 5.2: Based on Section 5.2 of RFC 3272.

      *  Section 5.3: Based on Section 5.3 of RFC 3272.

         +  Section 5.3.1: New for this document.

         +  Section 5.3.2: New for this document.

      *  Section 5.4: Based on Section 5.4 of RFC 3272.

      *  Section 5.5: Based on Section 5.5 of RFC 3272.

         +  Section 5.5.1: New for this document.

      *  Section 5.6: Based on Section 5.6 of RFC 3272.

      *  Section 5.7: Based on Section 5.7 of RFC 3272.

   o  Section 6: Based on Section 6 of RFC 3272.

      *  Section 6.1: Based on Section 6.1 of RFC 3272.

      *  Section 6.2: Based on Section 6.2 of RFC 3272.

      *  Section 6.3: Based on Section 6.3 of RFC 3272.

      *  Section 6.4: Based on Section 6.4 of RFC 3272.

      *  Section 6.5: Based on Section 6.5 of RFC 3272.

         +  Section 6.5.1: Based on Section 6.5.1 of RFC 3272.

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         +  Section 6.5.2: Based on Section 6.5.2 of RFC 3272.

      *  Section 6.6: Based on Section 6.6. of RFC 3272.

      *  Section 6.7: Based on Section 6.7 of RFC 3272.

   o  Section 7: Based on Section 7 of RFC 3272.

   o  Section 8: Based on Section 8 of RFC 3272.

   o  Section 9: Based on Section 10 of RFC 3272.

   o  Appendix A: New for this document.

      *  Appendix A.1: Based on Section 4.1 of RFC 3272.

      *  Appendix A.2: Based on Section 4.2 of RFC 3272.

         +  Appendix A.2.1: Based on Section 4.2.1 of RFC 3272.

         +  Appendix A.2.2: Based on Section 4.2.2 of RFC 3272.

         +  Appendix A.2.3: Based on Section 4.2.3 of RFC 3272.

         +  Appendix A.2.4: Based on Section 4.2.4 of RFC 3272.

         +  Appendix A.2.5: Based on Section 4.2.5 of RFC 3272.

      *  Appendix A.3: New for this document.

         +  Appendix A.3.1: Based on Section 4.3 of RFC 3272.

   o  Appendix B: New for this document.

      *  Appendix B.1: Based on Section 4.7 of RFC 3272.

Author's Address

   Adrian Farrel (editor)
   Old Dog Consulting


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