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Asynchronous Management Architecture

Document Type Replaced Internet-Draft (dtn WG)
Authors Edward J. Birrane , Emery Annis , Sarah Heiner
Last updated 2021-10-25
Replaces draft-birrane-dtn-ama
Replaced by draft-ietf-dtn-dtnma
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Stream WG state WG Document
Awaiting Expert Review/Resolution of Issues Raised
Associated WG milestone
Jul 2022
Delay-Tolerant Management Architecture
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Delay-Tolerant Networking                                   E.J. Birrane
Internet-Draft                                                  E. Annis
Intended status: Informational                               S.E. Heiner
Expires: 28 April 2022          Johns Hopkins Applied Physics Laboratory
                                                            October 2021

                  Asynchronous Management Architecture


   This document describes a management architecture suitable for
   deployment in challenged networking environments for the
   configuration, monitoring, and local control of application services.
   Challenged networking environments exhibit interruptions in end-to-
   end connectivity and communications delays that are both long-lived
   and unpredictable.  Even in these challenging conditions, such
   networks must provide some type of end-to-end information transport
   and fault protection while also supporting configuration and
   performance reporting.  This management may need to operate without
   human- or system-in-the-loop synchronous interactivity and without
   the preservation of transport-layer sessions.  In such a context,
   challenged networks must exhibit behavior that is both determinable
   and autonomous while maintaining as much compatibility with non-
   challenged-network operational concepts as possible.

   The architecture described in this document is termed the
   Asynchronous Management Architecture (AMA).  The AMA supported two
   types of asynchronous behavior.  First, the AMA does not presuppose
   any synchronized transport behavior between managed and managing
   devices.  Second, the AMA does not support any query-response
   semantics.  In this way, the AMA allows for operation in extremely
   challenging conditions, to include over uni-directional links and
   cases where delays/disruptions would otherwise prevent operation over
   traditional transport layers, such as when exceeding the Maximum
   Segment Lifetime (MSL) of the Transmission Control Protocol (TCP).

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at

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   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on 4 April 2022.

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

   This document is subject to BCP 78 and the IETF Trust's Legal
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   Please review these documents carefully, as they describe your rights
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   provided without warranty as described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
     1.1.  Scope . . . . . . . . . . . . . . . . . . . . . . . . . .   4
     1.2.  Requirements Language . . . . . . . . . . . . . . . . . .   5
     1.3.  Organization  . . . . . . . . . . . . . . . . . . . . . .   5
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   6
   3.  Motivation  . . . . . . . . . . . . . . . . . . . . . . . . .   8
     3.1.  Challenged Networks . . . . . . . . . . . . . . . . . . .   9
     3.2.  Current Approaches and Their Limitations  . . . . . . . .  10
       3.2.1.  Simple Network Management Protocol (SNMP) . . . . . .  10
       3.2.2.  YANG, NETCONF, and RESTCONF . . . . . . . . . . . . .  11
       3.2.3.  Constrained RESTful Network Management  . . . . . . .  13
   4.  Services Provided by an AMA . . . . . . . . . . . . . . . . .  13
     4.1.  Configuration . . . . . . . . . . . . . . . . . . . . . .  14
     4.2.  Reporting . . . . . . . . . . . . . . . . . . . . . . . .  14
     4.3.  Autonomous Parameterized Procedure Calls  . . . . . . . .  15
     4.4.  Administration  . . . . . . . . . . . . . . . . . . . . .  16
   5.  Desirable Properties of an AMA  . . . . . . . . . . . . . . .  16
     5.1.  Intelligent Push of Information . . . . . . . . . . . . .  16
     5.2.  Minimize Message Size Not Node Processing . . . . . . . .  17
     5.3.  Absolute Data Identification  . . . . . . . . . . . . . .  17
     5.4.  Custom Data Definition  . . . . . . . . . . . . . . . . .  18
     5.5.  Autonomous Operation  . . . . . . . . . . . . . . . . . .  18
   6.  AMA Roles and Responsibilities  . . . . . . . . . . . . . . .  19
     6.1.  Agent Responsibilities  . . . . . . . . . . . . . . . . .  19
     6.2.  Manager Responsibilities  . . . . . . . . . . . . . . . .  20

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   7.  Logical Data Model  . . . . . . . . . . . . . . . . . . . . .  21
     7.1.  Data Representations: Constants, Externally Defined Data,
           and Variables . . . . . . . . . . . . . . . . . . . . . .  21
     7.2.  Data Collections: Reports and Tables  . . . . . . . . . .  22
       7.2.1.  Report Templates and Reports  . . . . . . . . . . . .  22
       7.2.2.  Table Templates and Tables  . . . . . . . . . . . . .  23
     7.3.  Command Execution: Controls and Macros  . . . . . . . . .  23
     7.4.  Autonomy: Time and State-Based Rules  . . . . . . . . . .  24
       7.4.1.  State-Based Rule (SBR)  . . . . . . . . . . . . . . .  24
       7.4.2.  Time-Based Rule (TBR) . . . . . . . . . . . . . . . .  25
     7.5.  Calculations: Expressions, Literals, and Operators  . . .  25
   8.  System Model  . . . . . . . . . . . . . . . . . . . . . . . .  26
     8.1.  Control and Data Flows  . . . . . . . . . . . . . . . . .  26
     8.2.  Control Flow by Role  . . . . . . . . . . . . . . . . . .  27
       8.2.1.  Notation  . . . . . . . . . . . . . . . . . . . . . .  27
       8.2.2.  Serialized Management . . . . . . . . . . . . . . . .  27
       8.2.3.  Multiplexed Management  . . . . . . . . . . . . . . .  28
       8.2.4.  Data Fusion . . . . . . . . . . . . . . . . . . . . .  30
   9.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  31
   10. Security Considerations . . . . . . . . . . . . . . . . . . .  31
   11. Informative References  . . . . . . . . . . . . . . . . . . .  31
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  33

1.  Introduction

   The Asynchronous Management Architecture (AMA) provides a novel
   approach for the configuration, monitoring, and local control of
   application services on a managed device over a challenged network.
   The unique properties of a challenged network are as defined in
   [RFC7228] and include cases where an end-to-end transport path may
   not be feasible at any moment in time and delivery delays may prevent
   timely communications between a network operator and a managed
   device.  These delays may be caused by long signal propagations or
   frequent link disruptions (such as described in [RFC4838]) or by non-
   environmental factors such as quality-of-service prioritizations and
   service-level agreements.

   Importantly, the management approach for a challenged network must be
   one which remains operational in the most restrictive environments in
   which such networks might be instantiated.  The AMA approach should
   be functional in a variety of potential management scenarios, to
   include the following.

   *  Managed devices that are only accessible via a uni-directional
      link, or via a link whose duration is shorter than a single round-
      trip propagation time.

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   *  Links that may be significantly constrained by capacity or
      reliability, but at (predictable or unpredictable) times may offer
      significant throughput.

   *  Multi-hop challenged networks that interconnect two or more
      unchallenged networks such that managed and managing devices exist
      in different networks.

   In these and related scenarios, managed devices need to operate with
   a certain level of local autonomy because managing devices may not be
   available within operationally-relevant timeframes.  Managing devices
   deliver instruction sets that govern the local, autonomous behavior
   of the managed device.  These behaviors include, but are not limited
   to, collecting performance data, state, and error conditions, and
   applying pre-determined responses to pre-determined events.

   The AMA is a novel approach to management that can leverage
   transport, network, and security solutions designed for challenged
   networks, but is not bound to any single solution.  The goal is
   asynchronous communication between the device being managed and the
   manager, at times never expecting a reply, and with knowledge that
   commands and queries may be delivered much later than the initial

   More generally, the AMA approach is designed such that it can be
   deployed in all environments in which the Delay/Disruption-Tolerant
   (DTN) Bundle Protocol (BPv7) [I-D.ietf-dtn-bpbis] may be deployed.

1.1.  Scope

   This document describes the motivation, services, desirable
   properties, roles/responsibilities, logical data model, and system
   model that form the AMA.  These descriptions comprise a concept of
   operations for management in challenged networks with sufficient
   specificity that implementations conformant with this architecture
   will operate successfully in a challenged networking environment.

   The AMA described herein is strictly a framework for application
   management over a challenged network.  The document is not a
   prescriptive standardization of a physical data model or any
   protocol.  Instead, it serves as informative guidance to authors and
   users of such models and protocols.

   The AMA is independent of transport and network layers.  It does not,
   for example, require the use of TCP or UDP.  Similarly, the AMA does
   not pre-suppose the use of IPv4 or IPv6.

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   The AMA is not bound to a particular security solution.  It is
   assumed that any network using this architecture supports those
   services such as naming, addressing, integrity, confidentiality, and
   authentication required to communicate AMA messages.  Therefore, the
   transport of these messages is outside of the scope of the AMA.

   While possible that a challenged network may interface with an
   unchallenged network, this document does not address the concept of
   compatibility with other management approaches.

1.2.  Requirements Language

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   document are to be interpreted as described in [RFC2119].

1.3.  Organization

   The remainder of this document is organized into seven sections that,
   together, describe an AMA suitable for management of challenged
   networks.  The description of each section is as follows.

   *  Terminology - This section identifies those terms critical to
      understanding the proper operation of the AMA.  Whenever possible,
      these terms align in both word selection and meaning with their
      analogs from other management protocols.

   *  Motivation - This section provides an overall motivation for this
      work as providing a novel and useful alternative to other network
      management approaches.

   *  Services - This section identifies and defines the services that
      an AMA will provide to network and mission operators that are
      unique to operating in a challenged environment.

   *  Desirable Properties - This section identifies those properties of
      a challenged network management system required to effectively
      implement needed services.  These properties guide the subsequent
      definition of the system and logical models that comprise the AMA.

   *  Roles and Responsibilities - This section identifies roles in the
      AMA and their associated responsibilities.  It provides the
      context for discussing how services are provided by both managers
      and agents.

   *  Logical Data Model - This section describes the kinds of data,
      procedures, autonomy, and associated hierarchal structure inherent
      to the AMA.

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   *  System Model - This section describes data flows amongst various
      defined AMA roles.  These flows capture how the AMA system works
      to manage devices across a challenged network.

2.  Terminology

   *  Actor - A software service running on either managed or managing
      devices for the purpose of implementing management protocols
      between such devices.  Actors may implement the "Manager" role,
      "Agent" role, or both.

   *  Agent Role (or Agent) - A role associated with a managed device,
      responsible for reporting performance data, accepting/performing
      controls, error handling and validation, and executing any
      autonomous behaviors.  AMA Agents exchange information with AMA
      Managers operating either on the same device or on a remote
      managing device.

   *  Asynchronous Management - Management that does not depend on
      stateful connections or real time delivery of management messages.
      Allows for delivery of management messages and instruction sets
      for autonomous behavior that governs the expected actions, rules
      associated with those actions, and expected reporting procedures.
      Asynchronous management does not depend on underlying transport or
      network protocols for reliability or addressing of source and

   *  Asynchronous Management Model (AMM) - data types and data
      structures needed to manage applications in asynchronous networks.

   *  Externally Defined Data (EDD) - Information made available to an
      AMA Agent by a managed device, but not computed directly by the
      AMA Agent itself.

   *  Variables (VARs) - Typed information that is computed by an AMA
      Agent, typically as a function of EDD values and/or other

   *  Constants (CONST) - A constant represents a typed, immutable value
      that is referred to by a semantic name.  Constants are used in
      situations where substituting a name for a fixed value provides
      useful semantic information.  For example, using the named
      constant PI rather than the literal value 3.14.

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   *  Controls (CTRLs) - Procedures run by an AMA Actor to change the
      behavior, configuration, or state of an application or protocol
      being asynchronously managed.  Controls may also be used to
      request data from an agent and define the rules associated with
      generation and delivery.

   *  Literals (LITs) - A literal represents a typed value without a
      semantic name.  Literals are used in cases where adding a semantic
      name to a fixed value provides no useful semantic information.
      For example, the number 4 is a literal value.

   *  Macros (MACROs) - A named, ordered collection of Controls and/or
      other Macros.

   *  Manager Role (or Manager) - A role associated with a managing
      device responsible for configuring the behavior of, and eventually
      receiving information from, AMA Agents.  AMA Managers interact
      with one or more AMA Agents located on the same device and/or on
      remote devices in the network.

   *  Operator (OP) - The enumeration and specification of a
      mathematical function used to calculate variable values and
      construct expressions to evaluate AMA Agent state.

   *  Report (RPT) - A typed, ordered collection of data values gathered
      by one or more AMA Agents and provided to one or more AMA
      Managers.  Reports only contain typed data values and the identity
      of the Report Template (RPTT) to which they conform.

   *  Report Template (RPTT) - A named, typed, ordered collection of
      data types that represent the structure of a report (RPT).  This
      is the schema for a report, generated by an AMA Manager and
      communicated to one or more AMA Agents.

   *  Rule - A unit of autonomous specification that provides a
      stimulus-response relationship between time or state on an AMA
      Agent and the actions or operations to be run as a result of that
      time or state.  A rule might trigger updating a variable,
      populating a report/table, executing a control, or initiating the
      transmission of a report/table.

   *  State-Based Rule (SBR) - A state-based rule is any rule in which
      the rule stimulus is triggered by the calculable internal state of
      data model associated with the AMA Agent.

   *  Synchronous Management - Management that assumes messages will be
      delivered and acted upon in real or near-real-time.  Synchronous
      management often involves immediate replies of acknowledgment or

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      error status.  Synchronous management is often bound to underlying
      transport protocols and network protocols to ensure reliability or
      source and sender identification.

   *  Table (TBL) - A typed collection of data values organized in a
      tabular way in which columns represent homogeneous types of data
      and rows represent unique sets of data values conforming to column
      types.  Tables only contain typed data values and the identity of
      the Table Template (TBLT) to which they conform.

   *  Table Template (TBLT) - A named, typed, ordered collection of
      columns that comprise the structure for representing tabular data
      values.  This template forms the structure of a table (TBL).

   *  Time-Based Rule (TBR) - A time-based rule is a specialization, and
      simplification, of a state-based rule in which the rule stimulus
      is triggered by the relative time as it is known on the Agent as a
      function of either matched value or frequency.

3.  Motivation

   Early work into the rationale and motivation for specialized
   management for challenged networks was captured in [BIRRANE1],
   [BIRRANE2], and [BIRRANE3].  Some of the properties and feasibility
   of such a management system were adopted from prototyping work done
   in accordance with the DTN Research Group within the IRTF as
   documented in [I-D.irtf-dtnrg-dtnmp].

   The unique nature of challenged networks requires new network
   capabilities to deliver expected network functions.  For example, the
   unique nature of DTNs required the development of the Bundle Protocol
   for transport functions and the Bundle Protocol Security Protocol
   (BPSec) is required to secure bundles in certain types of DTNs.
   Similarly, new management capabilities are needed to implement
   management in challenged environments, such as those defined as DTNs.

   The AMA provides a method of configuring AMA Agents with local,
   autonomous management functions, such as rules-based execution of
   procedures and generation of reports, to achieve expected behavior
   when managed devices exist over a challenged network.  It further
   allows for dynamic instantiation and population of Variables and
   reports through local operations defined by the manager, as well as
   custom formatting of tables and reports to be sent back.  This gives
   the AMA significant flexibility to operate over challenged networks,
   both providing new degrees of freedom over existing configuration
   based data models used in synchronous networks and allowing for more
   concise formatting over constrained networks.  This architecture
   makes very few assumptions on the nature of the network and allow for

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   continuous operation through periods of connectivity and lack of
   connectivity.  The AMA deviates from synchronous management
   approaches because it never requires periods of bi-directional
   connectivity, and provides the manager flexibility to describe agent
   behavior that was unpredicted at the time of the data model creation.

   To understand the unique motivations for the architecture, this
   section discusses motivating characteristics of challenged networks,
   current network management approaches, and how they might behave in a
   challenged environment.

3.1.  Challenged Networks

   A challenged network is one that "has serious trouble maintaining
   what an application would today expect of the end-to-end IP model"
   ([RFC7228]).  This includes cases where there is never simultaneous
   end-to-end connectivity, when such connectivity is interrupted at
   planned or unplanned intervals, or when delays exceed those that
   could be accommodated by IP-based transport.  Links in such networks
   are often unavailable due to attenuations, propagation delays,
   mobility, occultation, and other limitations imposed by energy and
   mass considerations.

   Challenged networks exhibit the following properties that impact the
   way in which the function of network management is considered.

   *  No end-to-end path is guaranteed to exist at any given time
      between any two nodes.

   *  Round-trip communications between any two nodes within any given
      time window may be impossible.

   *  Latencies on the order of seconds, hours, or days must be

   *  Links may be uni-directional.

   *  Bi-directional links may have asymmetric data rates.

   One way in which constrained networks differ from challenged networks
   is the way in which the topology and, otherwise, roles and
   responsibilities of the network may evolve over time.  From the time
   at which data is generated on a source node to the time at which the
   data is received at a destination node, the topology of the network
   may have changed.  In certain circumstances, the physical node
   receiving messages for a given node identifier may also have changed.

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   When this topological change impacts the transport of messages, then
   transports must wait for the incremental connectivity necessary to
   advance messages along their expected route.  Therefore, these
   networks cannot guarantee that there exist timely data exchange
   between managing and managed devices.  For example, the Bundle
   Protocol transport protocol for use in DTNs implements this type of
   store-and-forward operation.

   When topological change impacts the semantic roles and
   responsibilities of nodes in the network, then local configuration
   and autonomy at nodes must be present to determine time-variant
   changes.  For example, the BPSec protocol does not encode security
   destinations and, instead, requires nodes in a network to identify as
   verifiers or acceptors when receiving secured messages.

   When applied to network management, the semantic roles of Agent and
   Manager may also change with the changing topology of the network.
   Individual nodes must implement desirable behavior without reliance
   on a single oracle of configuration or other coordinating function
   such as an operator-in-the-loop.  This implies that there MUST NOT be
   a defined relationship between a particular manager and agent in a

3.2.  Current Approaches and Their Limitations

   Network management solutions have been prevalent for many years in
   both local-area and wide-area networks.  These range from the
   simplistic ability to configure settings of operational devices or
   report on state and operational conditions; to the more more complex
   modeling of an entire managed device setting, state, and behavior,
   pushing and receiving large sets of configuration data between the
   manager and the agent.  Autonomy has more recently been applied to
   network management but is focused more on well resourced,
   unchallenged networks where devices self-configure, self-heal, and
   self-optimize with other nodes within their vicinity.  This section
   describes some of the well known standardized protocols for network
   management as well as various proposed solutions and aims to
   differentiate their purpose with the needs of challenged network
   management solutions.

3.2.1.  Simple Network Management Protocol (SNMP)

   Historically, network management tools in unchallenged networks
   provide mechanisms for communicating locally-collected data from
   devices to operators and managing applications, typically using a
   "pull" mechanism where data must be explicitly requested by a Manager
   in order to be transmitted by an Agent.  A legacy method for
   management in unchallenged networks today is the Simple Network

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   Management Protocol (SNMP) [RFC3416].  SNMP utilizes a request/
   response model to set and retrieve data values such as host
   identifiers, link utilizations, error rates, and counters between
   application software on Agents and Managers.  Data may be directly
   sampled or consolidated into representative statistics.
   Additionally, SNMP supports a model for asynchronous notification
   messages, called traps, based on predefined triggering events.  Thus,
   Managers can query Agents for status information, send new
   configurations, and be informed when specific events have occurred.
   Traps and queryable data are defined in one or more Managed
   Information Bases (MIBs) which define the information for a
   particular data standard, protocol, device, or application.

   While there is a large installation base for SNMP there are several
   aspects of the protocol that make in inappropriate for use in a
   challenged networking environment.  SNMP relies on sessions with low
   round-trip latency to support its "pull" model.  Complex management
   can be achieved but only through craftful orchestration using a
   series of real-time manager generated query and response logic not
   possible in challenged networks.  The SNMP trap model provides some
   Agent-side processing, however because the processing has very low
   fidelity and traps are typically "fire and forget."  Adaptive
   modifications to SNMP to support challenged networks and more complex
   application-level management, would alter the basic function of the
   protocol (data models, control flows, and syntax) so as to be
   functionally incompatible with existing SNMP installations.
   Therefore, this approach is not suitable for an asynchronous network
   management system.


   Yet Another Next Generation (YANG) [RFC6020] is a data modeling
   language used to model configuration and state data of managed
   devices and applications.  The YANG model defines a schema for
   organizing and accessing a device's configuration or operational
   information.  Once a model is developed, it is loaded to both the
   client (manager) and server (agent) and serves as a contract between
   the two.  A YANG model can be complex, describing many containers of
   managed elements, each with many configuration or operational state
   data nodes.  It can further define lists of like elements.  YANG
   allows for the definition of parameterized Remote Procedure Calls
   (RPCs) to be executed on managed nodes as well as the definition of
   asynchronous notifications within the model.

   YANG by itself serves no purpose other than to organize data and
   describe the allowed configuration parameters on the managed device.
   The Network Configuration Protocol (NETCONF) [RFC6241] and the
   RESTCONF protocol [RFC8040] provide the mechanisms to install,

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   manipulate, and delete the configuration of network devices, using
   the YANG modules.  NETCONF is a stateful, XML-based protocol that
   provides the RPC syntax to retrieve, edit, copy, or delete any data
   nodes or exposed functionality on the server.  NETCONF connections
   are required to provide authentication, data integrity,
   confidentiality, and replay protection through secure transport
   protocols such as SSH or TLS.  RESTCONF is a stateless RESTful
   protocol based on HTTP that uses JSON encoding to GET, POST, PUT,
   PATCH, or DELETE data nodes within the YANG modules similar to
   NETCONF.  RESTCONF, while stateless, still requires secure transport
   such as TLS.  Both NETCONF and RESTCONF place no specific functional
   requirements or constraints on the capabilities of the server, which
   makes it a very flexible tool for configuring a homogeneous network
   of devices, however they are limiting in challenged networks due to
   their requirements of underlying transport and dependence on the YANG
   data models.

   NETCONF places specific constraints on any underlying transport
   protocol: a long-lived, reliable, low-latency sequenced data delivery
   session.  No data is transferred without first establishing this bi-
   directional NETCONF session.  RESTCONF relaxes this constraint
   however is limited to requesting or configuring individual data
   elements or entire containers within the YANG data model.  It is
   therefore quite verbose and limited by the structure previously
   defined in the YANG module and any autonomous behavior depends on
   client slide orchestration similar to SNMP.

   As previously noted, YANG allows for the definition of RPCs within
   the model and notification elements for asynchronous messaging.  The
   RPCs provide both the definition of input and output parameters
   however are strictly allowed in NETCONF and RESTCONF to be sent as
   sequential procedures.  Even if multiple procedures are sent, the
   server is required to execute them and reply in the order they were
   received.  There is also no flexibility for the state-based execution
   of those procedures on the server.  The RPCs are executed as soon as
   they are received, ultimately limiting the degrees of autonomy of the
   server.  YANG notifications are quite promising for asynchronous
   network management, defined as both subscriptions to YANG
   notifications [RFC8639] and YANG PUSH notifications [RFC8641].
   Notification containers must first be defined within the YANG module
   declaring the containers or data nodes of interest.  The events can
   be filtered according to XPATH filtering defined in [RFC8639]
   Section 6, however generation of events are streamed and generally
   limited to the external changing state of a data node.  YANG PUSH
   allows for both periodic and on-change event notification but
   supports no rules-based triggering.  While the YANG data model offers
   many great features, the features today are simply limiting for the
   autonomous behavior required by challenged network management.

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   YANG is additionally limiting for challenged networks because of its
   non-hierarchal schema.  While the YANG model flexibility is great for
   the management of nodes and applications of any type in an
   unchallenged network, it becomes a burden in challenged networks
   where concise encoding is necessary.  All the data nodes within a
   YANG model are referenced by verbose string based path of the module,
   sub-module, container, and any data nodes such as lists, leaf-lists,
   or leafs.  Recent efforts are underway which allow for CBOR encoding
   of YANG models [I-D.ietf-core-yang-cbor] and addressing of data nodes
   through integer value YANG Schema Item iDentifiers (SIDs)
   [I-D.ietf-core-sid], however these lack any formal hierarchal
   structure.  All mapping of SIDs to YANG modules and data nodes is
   preformed manually which limits the portability of models and further
   increases the size of any encoding scheme.

3.2.3.  Constrained RESTful Network Management

   Due to the advent and ubiquity of the Internet of Things (IoT), the
   Constrained Application Protocol (CoAP) [RFC7252] has been recently
   developed for communicating with nodes and applications in
   constrained networks.  CoAP is merely the messaging framework
   designed to limit message size and fragmentation, operating over IP
   networks.  Because constrained networks could experience interruption
   similar to those in DTNs, the protocol provides for application layer
   store-and-forward as well as proxy delivery of messages, but is bound
   to UDP transport.  An approach to network management has been
   authored that uses CoAP for transport and YANG as the data model, and
   is defined as CORECONF [I-D.ietf-core-comi].  This proposed protocol
   makes use of the YANG to CBOR encoding including the use of SIDs to
   limit message size, however is currently bound to UDP/IP transport of
   CoAP and further defines security requirements including DTLS or
   OSCORE.  This explicit binding to transport and security protocols is
   limiting when applied to novel DTN approaches designed for challenged

4.  Services Provided by an AMA

   This section identifies the services that an AMA would provide for
   management of challenged network resources.  These services include
   configuration, reporting, parameterized control, and administration.

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4.1.  Configuration

   Configuration services update Agent data associated with managed
   applications and protocols.  Some configuration data might be defined
   in the context of an application or protocol, such that any network
   using that application or protocol would understand that data.  Other
   configuration data may be defined tactically for use in a specific
   network deployment and not available to other networks even if they
   use the same applications or protocols.

   New configurations received by an Agent must be validated to ensure
   that they do not conflict with other configurations or would
   otherwise prevent the Agent from effectively working with other
   Actors in its region.  With no guarantee of round-trip data exchange,
   Agents cannot rely on remote Managers to correct erroneous or stale
   configurations from harming the flow of data through a challenged

   Examples of configuration service behavior include the following.

   *  Creating a new datum as a function of other well-known data:

      C = A + B.

   *  Creating a new report as a unique, ordered collection of known

      RPT = {A, B, C}.

   *  Storing predefined, parameterized responses to potential future

      IF (X > 3) THEN RUN CMD(PARM).

4.2.  Reporting

   Reporting services populate report templates with values collected or
   computed by an Agent.  The resultant reports are sent to one or more
   Managers by the Agent.  The term "reporting" is used in place of the
   term "monitoring", as monitoring implies a timeliness and regularity
   that cannot be guaranteed by a challenged network.  Reports sent by
   an Agent provide best-effort information to receiving Managers.

   Since a Manager is not actively "monitoring" an Agent, the Agent must
   make its own determination on when to send what Reports based on its
   own local time and state information.  Agents should produce Reports
   of varying fidelity and with varying frequency based on thresholds
   and other information set as part of configuration services.

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   Examples of reporting service behavior include the following.

   *  Generate Report R1 every hour (time-based production).

   *  Generate Report R2 when X > 3 (state-based production).

4.3.  Autonomous Parameterized Procedure Calls

   Similar to an RPC call, some mechanism MUST exist which allows a
   procedure to be run on an Agent in order to affect its behavior or
   otherwise change its internal state.  Since there is no guarantee
   that a Manager will be in contact with an Agent at any given time,
   the decisions of whether and when a procedure should be run MUST be
   made locally and autonomously by the Agent.  Two types of automation
   triggers are identified in the AMA: triggers based on the internal
   state of the Agent and triggers based on an Agent's notion of time.
   As such, the autonomous execution of procedures can be viewed as a
   stimulus-response system, where the stimulus is the positive
   evaluation of a state or time based predicate and the response is the
   function to be executed.

   The autonomous nature of procedure execution by an Agent implies that
   the full suite of information necessary to run a procedure may not be
   known by a Manager in advance.  To address this situation, a
   parameterization mechanism MUST be available so that required data
   can be provided at the time of execution on the Agent rather than at
   the time of definition/configuration by the Manager.

   Autonomous, parameterized procedure calls provide a powerful
   mechanism for Managers to "manage" an Agent asynchronously during
   periods of no communication by pre-configuring responses to events
   that may be encountered by the Agent at a future time.

   Examples of potential behavior include the following.

   *  Updating local routing information based on instantaneous link

   *  Managing storage on the device to enforce quotas.

   *  Applying or modifying local security policy.

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4.4.  Administration

   Administration services enforce the potentially complex mapping of
   configuration, reporting, and control services amongst Agents and
   Managers in the network.  Fine-grained access controls that specify
   which Managers may apply which services to which Agents may be
   necessary in networks that either deal with multiple administrative
   entities or overlay networks that cross administrative boundaries.
   Whitelists, blacklists, key-based infrastructures, or other schemes
   may be used for this purpose.

   Examples of administration service behavior include the following.

   *  Agent A1 only Sends reports for Protocol P1 to Manager M1.

   *  Agent A2 only accepts a configurations for Application Y from
      Managers M2 and M3.

   *  Agent A3 accepts services from any Manager providing the proper
      authentication token.

   Note that the administrative enforcement of access control is
   different from security services provided by the networking stack
   carrying such messages.

5.  Desirable Properties of an AMA

   This section describes those design properties that are desirable
   when defining an architecture that must operate across challenged
   links in a network.  These properties ensure that network management
   capabilities are retained even as delays and disruptions in the
   network scale.  Ultimately, these properties are the driving design
   principles for the AMA.

5.1.  Intelligent Push of Information

   Pull management mechanisms require that a Manager send a query to an
   Agent and then wait for the response to that query.  This practice
   implies a control-session between entities and increases the overall
   message traffic in the network.  Challenged networks cannot guarantee
   that the round-trip data-exchange will occur in a timely fashion.  In
   extreme cases, networks may be comprised of solely uni-directional
   links which drastically increases the amount of time needed for a
   round-trip data exchange.  Therefore, pull mechanisms must be avoided
   in favor of push mechanisms.

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   Push mechanisms, in this context, refer to the ability of Agents to
   leverage rule-based criteria to determine when and what information
   should be sent to managers.  This could be based solely off logic
   applied to existing VARs or EDDs, or based off operations applied to
   data elements.  Such mechanisms do not require round-trip
   communications as Managers do not request each reporting instance;
   Managers need only request once, in advance, that information be
   produced in accordance with a predetermined schedule or in response
   to a predefined state on the Agent.  In this way information is
   "pushed" from Agents to Managers and the push is "intelligent"
   because it is based on some internal evaluation performed by the

5.2.  Minimize Message Size Not Node Processing

   Protocol designers must balance message size versus message
   processing time at sending and receiving nodes.  Verbose
   representations of data simplify node processing whereas compact
   representations require additional activities to generate/parse the
   compacted message.  There is no asynchronous management advantage to
   minimizing node processing time in a challenged network.  However,
   there is a significant advantage to smaller message sizes in such
   networks.  Compact messages require smaller periods of viable
   transmission for communication, incur less re-transmission cost, and
   consume less resources when persistently stored en-route in the
   network.  An Asynchronous Management Protocol (AMP) should minimize
   PDUs whenever practical, to include packing and unpacking binary
   data, variable-length fields, and pre-configured data definitions.

5.3.  Absolute Data Identification

   Elements within the management system must be uniquely identifiable
   so that they can be individually manipulated.  Identification schemes
   that are relative to system configuration make data exchange between
   Agents and Managers difficult as system configurations may change
   faster than nodes can communicate.

   Consider the following common technique for approximating an
   associative array lookup.  A manager wishing to do an associative
   lookup for some key K1 will (1) query a list of array keys from the
   agent, (2) find the key that matches K1 and infer the index of K1
   from the returned key list, and (3) query the discovered index on the
   agent to retrieve the desired data.

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   Ignoring the inefficiency of two pull requests, this mechanism fails
   when the Agent changes its key-index mapping between the first and
   second query.  Rather than constructing an artificial mapping from K1
   to an index, an AMP must provide an absolute mechanism to lookup the
   value K1 without an abstraction between the Agent and Manager.

5.4.  Custom Data Definition

   Custom definition of new data from existing data (such as through
   data fusion, averaging, sampling, or other mechanisms) provides the
   ability to communicate desired information in as compact a form as
   possible.  Specifically, an Agent should not be required to transmit
   a large data set for a Manager that only wishes to calculate a
   smaller, inferred data set.  These new defined data elements could be
   calculated and used both as parameters for local stimulus-response
   rules-based criteria or simply serve to populate custom reports and
   tables.  Since the identification of custom data sets is likely to
   occur in the context of a specific network deployment, AMPs must
   provide a mechanism for their definition.

   Aggregation of controls and custom formatting of reports and tables
   are is equally important.  Custom reporting provides the flexibility
   allowing the manager to define the desired format of all information
   to be sent over the challenged network from the agents, serving to
   both save link capacity and increase the value of returned
   information.  Aggregation of controls allows a manager to specify a
   set of controls to execute, specifying both the order and criteria of
   execution.  This aggregate set of controls can be sent as a single
   command rather than a series of sequential operands.  In this case it
   is additionally possible to use outputs of one command to serve as an
   input to the next at the agent.

5.5.  Autonomous Operation

   AMA network functions must be achievable using only knowledge local
   to the Agent.  Rather than directly controlling an Agent, a Manager
   configures an engine of the Agent to take its own action under the
   appropriate conditions in accordance with the Agent's notion of local
   state and time.

   Such an engine may be used for simple automation of predefined tasks
   or to support semi-autonomous behavior in determining when to run
   tasks and how to configure or parameterize tasks when they are run.
   Wholly autonomous operations MAY be supported where required.
   Generally, autonomous operations should provide the following

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   *  Distributed Operation - The concept of pre-configuration allows
      the Agent to operate without regular contact with Managers in the
      system.  The initial configuration (and periodic update) of the
      system remains difficult in a challenged network, but an initial
      synchronization on stimuli and responses drastically reduces needs
      for centralized operations.

   *  Deterministic Behavior - Such behavior is necessary in critical
      operational systems where the actions of a platform must be well
      understood even in the absence of an operator in the loop.
      Depending on the types of stimuli and responses, these systems may
      be considered to be maintaining simple automation or semi-
      autonomous behavior.  In either case, this preserves the ability
      of a frequently-out-of-contact Manager to predict the state of an
      Agent with more reliability than cases where Agents implement
      independent and fully autonomous systems.

   *  Engine-Based Behavior - Several operational systems are unable to
      deploy "mobile code" based solutions due to network bandwidth,
      memory or processor loading, or security concerns.  Engine-based
      approaches provide configurable behavior without incurring these
      types of concerns associated with mobile code.

6.  AMA Roles and Responsibilities

   By definition, Agents reside on managed devices and Managers reside
   on managing devices.  There is however no pre-supposed architecture
   that connects managers and agents and therefore a single device could
   assume both roles.  This section describes the responsibilities
   associated with each role and how these roles participate in network

6.1.  Agent Responsibilities

   Application Support
           Agents MUST collect all data, execute all procedures,
           populate all reports and run operations required by each
           application which the Agent manages.  Agents MUST report
           supported applications so that Managers in a network
           understands what information is understood by what Agent.

   Local Data Collection
           Agents MUST collect from local firmware (or other on-board
           mechanisms) and report all data defined for the management of
           applications for which they have been configured.

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   Autonomous Control
           Agents MUST determine, as previously prescribed by a manager,
           whether a procedure should be invoked.

   User Data Definition
           Agents MUST provide mechanisms for operators in the network
           to use configuration services to create customized data
           definitions in the context of a specific network or network
           use-case.  Agents MUST allow for the creation, listing, and
           removal of such definitions in accordance with whatever
           security models are deployed within the particular network.

           Where applicable, Agents MUST verify the validity of these
           definitions when they are configured and respond in a way
           consistent with the logging/error-handling policies of the
           Agent and the network.

   Autonomous Reporting
           Agents MUST determine, without real-time Manager
           intervention, whether and when to populate and transmit a
           given report targeted to one or more Managers in the network.

   Consolidate Messages
           Agents SHOULD produce as few messages as possible when
           sending information.  For example, rather than sending
           multiple messages, each with one report to a Manager, an
           Agent SHOULD prefer to send a single message containing
           multiple reports.

6.2.  Manager Responsibilities

   Agent Capabilities Mapping
           Managers MUST understand what applications are managed by the
           various Agents with which they communicate.  Managers should
           not attempt to request, invoke, or refer to application
           information for applications not managed by an Agent.

   Data Collection
           Managers MUST receive information from Agents by
           asynchronously configuring the production of reports and then
           waiting for, and collecting, responses from Agents over time.
           Managers MAY try to detect conditions where Agent information
           has not been received within operationally relevant time
           spans and react in accordance with network policy.

   Custom Definitions
           Managers should provide the ability to define custom data
           definitions.  Any custom definitions MUST be transmitted to

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           appropriate Agents and these definitions MUST be remembered
           to interpret the reporting of these custom values from Agents
           in the future.

   Data Translation
           Managers should provide some interface to other network
           management protocols.  Managers MAY accomplish this by
           accumulating a repository of push-data from high-latency
           parts of the network from which data may be pulled by low-
           latency parts of the network.

   Data Fusion
           Managers MAY support the fusion of data from multiple Agents
           with the purpose of transmitting fused data results to other
           Managers within the network.  Managers MAY receive fused
           reports from other Managers pursuant to appropriate security
           and administrative configurations.

7.  Logical Data Model

   The AMA logical data model captures the types of information that
   should be collected and exchanged to implement necessary roles and
   responsibilities.  The data model presented in this section does not
   presuppose a specific mapping to a physical data model or encoding
   technique; it is included to provide a way to logically reason about
   the types of data that should be exchanged in an asynchronously
   managed network.

   The elements of the AMA logical data model are described as follows.

7.1.  Data Representations: Constants, Externally Defined Data, and

   There are three fundamental representations of data in the AMA: (1)
   data whose values do not change as a function of time or state, (2)
   data whose values change as determined by sampling/calculation
   external to the network management system, and (3) data whose values
   are calculated internal to the network management system.

   Data whose values do not change as a function of time or state are
   defined as Constants (CONST).  CONST values are strongly typed, named
   values that cannot be modified once they have been defined.

   Data sampled/calculated external to the network management system are
   defined as Externally Defined Data" (EDD).  EDD values represent the
   most useful information in the management system as they are provided
   by the applications or protocols being managed on the Agent.  It is
   RECOMMENDED that EDD values be strongly typed to avoid issues with

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   interpreting the data value.  It is also RECOMMENDED that the
   timeliness/staleness of the data value be considered when using the
   data in the context of autonomous action on the Agent.

   Data that is calculated internal to the network management system is
   defined as a Variable (VAR).  VARs allow the creation of new data
   values for use in the network management system.  New value
   definitions are useful for storing user-defined information, storing
   the results of complex calculations for easier re-use, and providing
   a mechanism for combining information from multiple external sources.
   It is RECOMMENDED that VARs be strongly typed to avoid issues with
   interpreting the data value.  In cases where a VAR definition relies
   on other VAR definitions, mechanisms to prevent circular references
   MUST be included in any actual data model or implementation.

7.2.  Data Collections: Reports and Tables

   Individual data values may be exchanged amongst Agents and Managers
   in the AMA.  However, data are typically most useful to a Manager
   when received as part of a set of information.  Ordered collections
   of data values can be produced by Agents and sent to Managers as a
   way of efficiently communicating Agent status.  Within the AMA, the
   structure of the ordered collection is treated separately from the
   values that populate such a structure.

   The AMA provides two ways of defining collections of data: reports
   and tables.  Reports are ordered sets of data values, whereas Tables
   are special types of reports whose entries have a regular, tabular

7.2.1.  Report Templates and Reports

   The typed, ordered structure of a data collection is defined as a
   Report Template (RPTT).  A particular set of data values provided in
   compliance with such a template is called a Report (RPT).

   Separating the structure and content of a report reduces the overall
   size of RPTs in cases where reporting structures are well known and
   unchanging.  RPTTs can be synchronized between an Agent and a Manager
   so that RPTs themselves do not incur the overhead of carrying self-
   describing data.  RPTTs may include EDD values, VARs, and also other
   RPTTs.  In cases where a RPTT includes another RPTTs, mechanisms to
   prevent circular references MUST be included in any actual data model
   or implementation.

   Protocols and applications managed in the AMA may define common
   RPTTs.  Additionally, users within a network may define their own
   RPTTs that are useful in the context of a particular deployment.

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   Unlike tables, reports do not exploit assumptions on the underlying
   structure of their data.  Therefore, unlike tables, operators can
   define new reports at any time as part of the runtime configuration
   of the network.

7.2.2.  Table Templates and Tables

   Tables optimize the communication of multiple sets of data in
   situations where each data set has the same syntactic structure and
   with the same semantic meaning.  Unlike reports, the regularity of
   tabular data representations allow for the addition of new rows
   without changing the structure of the table.  Attempting to add a new
   data set at the end of a report would require alterations to the
   report template.

   The typed, ordered structure of a table is defined as a
   Table Template (TBLT).  A particular instance of values populating
   the table template is called a Table (TBL).

   TBLTs describes the "columns" that define the table schema.  A TBL
   represents the instance of a specific TBLT that holds actual data
   values.  These data values represent the "rows" of the table.

   The prescriptive nature of the TBLT allows for the possibility of
   advanced filtering which may reduce traffic between Agents and
   Managers.  However, the unique structure of each TBLT may make them
   difficult or impossible to change dynamically in a network.

7.3.  Command Execution: Controls and Macros

   Low-latency, high-availability approaches to network management use
   mechanisms such as (or similar to) RPCs to cause some action to be
   performed on an Agent.  The AMA enables similar capabilities without
   requiring that the Manager be in the processing loop of the Agent.
   Command execution in the AMA happens through the use of controls and

   A Control (CTRL) represents a parameterized, predefined procedure
   that can be run on an Agent.  While conceptually similar to a "remote
   procedure call", CTRLs differ in that they do not provide numeric
   return codes.  The concept of a return code when running a procedure
   implies a synchronous relationship between the caller of the
   procedure and the procedure being called, which is disallowed in an
   asynchronous management system.  Instead, CTRLs may create reports
   which describe the status and other summarizations of their
   operation, and these reports may be sent to the Manager(s) calling
   the CTRL.

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   Parameters can be provided when running a command from a Manager,
   pre-configured as part of a response to a time-based or state-based
   rule on the Agent, or auto-generated as needed on the Agent.  The
   success or failure of a control MAY be inferred by reports generated
   for that purpose.

   NOTE: The AMA term control is derived in part from the concept of
   Command and Control (C2) where control implies the operational
   instructions that must be undertaken to implement (or maintain) a
   commanded objective.  An asynchronous management function controls an
   Agent to allow it to fulfill its commanded purpose in a variety of
   operational scenarios.  For example, attempting to maintain a safe
   internal thermal environment for a spacecraft is considered "thermal
   control" (not "thermal commanding") even though thermal control
   involves "commanding" heaters, louvers, radiators, and other
   temperature-affecting components.

   Often, a series of controls must be executed in sequence to achieve a
   particular outcome.  A Macro (MACRO) represents an ordered collection
   of controls (or other macros).  In cases where a MACRO includes
   another MACRO, mechanisms to prevent circular references and maximum
   nesting levels MUST be included in any actual data model or

7.4.  Autonomy: Time and State-Based Rules

   The AMA data model contains EDDs and VARs that capture the state of
   applications on an Agent.  The model also contains controls and
   macros to perform actions on an Agent.  A mechanism is needed to
   relate these two capabilities: to perform an action on the Agent in
   response to the state of the Agent.  This mechanism in the AMA is the
   "rule" and can be activated based on Agent internal state (state-
   based rule) or based on the Agent's notion of relative time (time-
   based rule).

7.4.1.  State-Based Rule (SBR)

   State-Based Rules (SBRs) perform actions based on the Agent's
   internal state, as identified by EDD and VAR values.  An SBR
   represents a stimulus-response pairing in the following form: IF
   predicate THEN response The predicate is a logical expression that
   evaluates to true if the rule stimulus is present and evaluates to
   false otherwise.  The response may be any control or macro known to
   the Agent.

   An example of an SBR could be to turn off a heater if some internal
   temperature is greater than a threshold: IF (current_temp >
   maximum_temp) THEN turn_heater_off

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   Rules may construct their stimuli from the full set of values known
   to the network management system.  Similarly, responses may be
   constructed from the full set of controls and macros that can be run
   on the Agent.  By allowing rules to evaluate the variety of all known
   data and run the variety of all known controls, multiple applications
   can be monitored and managed by one (or few) Agent instances.

7.4.2.  Time-Based Rule (TBR)

   Time-Based Rules (TBR) perform actions based on the Agent's notion of
   the passage of time.  A possible TBR construct would be to perform
   some action at 1Hz on the Agent.

   A TBR is a specialization of an SBR as the Agent's notion of time is
   a type of Agent state.  For example, a TBR to perform an action every
   24 hours could be expressed using some type of predicate of the form:
   IF (((current_time - base_time) % 24_hours) == 0) THEN ...  However,
   time-based events are popular enough that special semantics for
   expressing them would likely significantly reduce the computations
   necessary to represent time functions in a SBR.

7.5.  Calculations: Expressions, Literals, and Operators

   Actions such as computing a VAR value or describing a rule predicate
   require some mechanism for calculating the value of mathematical
   expressions.  In addition to the aforementioned AMA logical data
   objects, Literals, Operators, and Expressions are used to perform
   these calculations.

   A Literal (LIT) represents a strongly typed datum whose identity is
   equivalent to its value.  An example of a LIT value is "4" - its
   identifier (4) is the same as its value (4).  Literals differ from
   constants in that constants have an identifier separate from their
   value.  For example, the constant PI may refer to a value of 3.14.
   However, the literal 3.14159 always refers to the value 3.14159.

   An Operator (OP) represents a mathematical operation in an
   expression.  OPs should support multiple operands based on the
   operation supported.  A common set of OPs SHOULD be defined for any
   Agent and systems MAY choose to allow individual applications to
   define new OPs to assist in the generation of new VAR values and
   predicates for managing that application.  OPs may be simple binary
   operations such as "A + B" or more complex functions such as sin(A)
   or avg(A,B,C,D).  Additionally, OPs may be typed.  For example,
   addition of integers may be defined separately from addition of real

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   An Expression (EXPR) is a combination of operators and operands used
   to construct a numerical value from a series of other elements of the
   AMA logical model.  Operands include any AMA logical data model
   object that can be interpreted as a value, such as EDD, VAR, CONST,
   and LIT values.  Operators perform some function on operands to
   generate new values.

8.  System Model

   This section describes the notional data flows and control flows that
   illustrate how Managers and Agents within an AMA cooperate to perform
   network management services.

8.1.  Control and Data Flows

   The AMA identifies three significant data flows: control flows from
   Managers to Agents, reports flows from Agents to Managers, and fusion
   reports from Managers to other Managers.  These data flows are
   illustrated in Figure 1.

   AMA Control and Data Flows

       +---------+       +------------------------+      +---------+
       | Node A  |       |         Node B         |      |  Node C |
       |         |       |                        |      |         |
       |+-------+|       |+-------+      +-------+|      |+-------+|
       ||       ||=====>>||Manager|====>>|       ||====>>||       ||
       ||       ||<<=====||   B   |<<====|Agent B||<<====||       ||
       ||       ||       |+--++---+      +-------+|      ||Manager||
       || Agent ||       +---||-------------------+      ||   C   ||
       ||   A   ||           ||                          ||       ||
       ||       ||<<=========||==========================||       ||
       ||       ||===========++========================>>||       ||
       |+-------+|                                       |+-------+|
       +---------+                                       +---------+

                                  Figure 1

   In this data flow, the Agent on node A receives Controls from
   Managers on nodes B and C, and replies with Report Entries back to
   these Managers.  Similarly, the Agent on node B interacts with the
   local Manager on node B and the remote Manager on node C.  Finally,
   the Manager on node B may fuse Report Entries received from Agents at
   nodes A and B and send these fused Report Entries back to the Manager
   on node C.  From this figure it is clear that there exist many-to-
   many relationships amongst Managers, amongst Agents, and between
   Agents and Managers.  Note that Agents and Managers are roles, not

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   necessarily different software applications.  Node A may represent a
   single software application fulfilling only the Agent role, whereas
   node B may have a single software application fulfilling both the
   Agent and Manager roles.  The specifics of how these roles are
   realized is an implementation matter.

8.2.  Control Flow by Role

   This section describes three common configurations of Agents and
   Managers and the flow of messages between them.  These configurations
   involve local and remote management and data fusion.

8.2.1.  Notation

   The notation outlined in Table 1 describes the types of control
   messages exchanged between Agents and Managers.

      |    Term    |             Definition            |  Example  |
      |    EDD#    |          EDD definition.          |    EDD1   |
      |     V#     |        Variable definition.       | V1 = EDD1 |
      |            |                                   |   + V0.   |
      | DEF([ACL], | Define ID from expression.  Allow |  DEF([*], |
      |  ID,EXPR)  |  managers in access control list  |  V1, EDD1 |
      |            |     (ACL) to request this ID.     |  + EDD2)  |
      | PROD(P,ID) | Produce ID according to predicate |  PROD(1s, |
      |            |  P.  P may be a time period (1s)  |   EDD1)   |
      |            |   or an expression (EDD1 > 10).   |           |
      |  RPT(ID)   |     A report identified by ID.    | RPT(EDD1) |

                           Table 1: Terminology

8.2.2.  Serialized Management

   This is a nominal configuration of network management where a Manager
   interacts with a set of Agents.  The control flows for this are
   outlined in Figure 2.

   Serialized Management Control Flow

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         +----------+            +---------+           +---------+
         |  Manager |            | Agent A |           | Agent B |
         +----+-----+            +----+----+           +----+----+
              |                       |                     |
              |-----PROD(1s, EDD1)--->|                     | (1)
              |----------------------------PROD(1s, EDD1)-->|
              |                       |                     |
              |                       |                     |
              |<-------RPT(EDD1)------|                     | (2)
              |                       |                     |
              |                       |                     |
              |<-------RPT(EDD1)------|                     |
              |                       |                     |
              |                       |                     |
              |<-------RPT(EDD1)------|                     |
              |                       |                     |

                                  Figure 2

   In a simple network, a Manager interacts with multiple Agents.

   In this figure, the Manager configures Agents A and B to produce EDD1
   every second in (1).  Upon receiving and configuring this message,
   Agents A and B then build a Report Entry containing EDD1 and send
   those reports back to the Manager in (2).  This behavior then repeats
   this action every 1s without requiring other inputs from the Manager.

8.2.3.  Multiplexed Management

   Networks spanning multiple administrative domains may require
   multiple Managers (for example, one per domain).  When a Manager
   defines custom Reports/Variables to an Agent, that definition may be
   tagged with an Access Control List (ACL) to limit what other Managers
   will be privy to this information.  Managers in such networks should
   synchronize with those other Managers granted access to their custom
   data definitions.  When Agents generate messages, they MUST only send
   messages to Managers according to these ACLs, if present.  The
   control flows in this scenario are outlined in Figure 3.

   Multiplexed Management Control Flow

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        +-----------+            +-------+            +-----------+
        | Manager A |            | Agent |            | Manager B |
        +-----+-----+            +---+---+            +-----+-----+
              |                      |                      |
              |---DEF(A,V1,EDD1*2)-->|<-DEF(B, V2, EDD2*2)--| (1)
              |                      |                      |
              |---PROD(1s, V1)------>|<---PROD(1s, V2)------| (2)
              |                      |                      |
              |<--------RPT(V1)------|                      | (3)
              |                      |--------RPT(V2)------>|
              |<--------RPT(V1)------|                      |
              |                      |--------RPT(V2)------>|
              |                      |                      |
              |                      |<---PROD(1s, V1)------| (4)
              |                      |                      |
              |                      |---ERR(V1 no perm.)-->|
              |                      |                      |
              |--DEF(*,V3,EDD3*3)--->|                      | (5)
              |                      |                      |
              |---PROD(1s, V3)------>|                      | (6)
              |                      |                      |
              |                      |<----PROD(1s, V3)-----|
              |                      |                      |
              |<--------RPT(V3)------|--------RPT(V3)------>| (7)
              |<--------RPT(V1)------|                      |
              |                      |--------RPT(V2)------>|
              |<-------RPT(V1)-------|                      |
              |                      |--------RPT(V2)------>|

                                  Figure 3

   Complex networks require multiple Managers interfacing with Agents.

   In more complex networks, any Manager may choose to define custom
   Reports and Variables, and Agents may need to accept such definitions
   from multiple Managers.  Variable definitions may include an ACL that
   describes who may query and otherwise understand these definitions.
   In (1), Manager A defines V1 only for A while Manager B defines V2
   only for B.  Managers may, then, request the production of Report
   Entries containing these definitions, as shown in (2).  Agents
   produce different data for different Managers in accordance with
   configured production rules, as shown in (3).  If a Manager requests
   the production of a custom definition for which the Manager has no
   permissions, a response consistent with the configured logging policy
   on the Agent should be implemented, as shown in (4).  Alternatively,
   as shown in (5), a Manager may define custom data with no access
   restrictions, allowing all other Managers to request and use this

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   definition.  This allows all Managers to request the production of
   Report Entries containing this definition, shown in (6) and have all
   Managers receive this and other data going forward, as shown in (7).

8.2.4.  Data Fusion

   Data fusion reduces the number and size of messages in the network
   which can lead to more efficient utilization of networking resources.
   The AMA supports fusion of NM reports by co-locating Agents and
   Managers on nodes and offloading fusion activities to the Manager.
   This process is illustrated in Figure 4.

   Data Fusion Control Flow

   +-----------+        +-----------+      +---------+      +---------+
   | Manager A |        | Manager B |      | Agent B |      | Agent C |
   +---+-------+        +-----+-----+      +----+----+      +----+----+
       |                      |                 |                |
       |-DEF(A,V0,EDD1+EDD2)->|                 |                | (1)
       |-PROD(EDD1&EDD2,V0)-->|                 |                |
       |                      |                 |                |
       |                      |--PROD(1s,EDD1)->|                | (2)
       |                      |------------------PROD(1s, EDD2)->|
       |                      |                 |                |
       |                      |<---RPT(EDD1)----|                | (3)
       |                      |<------------------RPT(EDD2)------|
       |                      |                 |                |
       |<-----RPT(A,V0)-------|                 |                | (4)
       |                      |                 |                |

                                  Figure 4

   Data fusion occurs amongst Managers in the network.

   In this example, Manager A requires the production of a Variable V0,
   from node B, as shown in (1).  The Manager role understands what data
   is available from what agents in the subnetwork local to B,
   understanding that EDD1 is available locally and EDD2 is available
   remotely.  Production messages are produced in (2) and data collected
   in (3).  This allows the Manager at node B to fuse the collected
   Report Entries into V0 and return it in (4).  While a trivial
   example, the mechanism of associating fusion with the Manager
   function rather than the Agent function scales with fusion
   complexity, though it is important to reiterate that Agent and
   Manager designations are roles, not individual software components.
   There may be a single software application running on node B
   implementing both Manager B and Agent B roles.

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9.  IANA Considerations

   This protocol has no fields registered by IANA.

10.  Security Considerations

   Security within an AMA MUST exist in two layers: transport layer
   security and access control.

   Transport-layer security addresses the questions of authentication,
   integrity, and confidentiality associated with the transport of
   messages between and amongst Managers and Agents in the AMA.  This
   security is applied before any particular Actor in the system
   receives data and, therefore, is outside of the scope of this

   Finer grain application security is done via ACLs which are defined
   via configuration messages and implementation specific.

11.  Informative References

   [BIRRANE1] Birrane, E.B. and R.C. Cole, "Management of Disruption-
              Tolerant Networks: A Systems Engineering Approach", 2010.

   [BIRRANE2] Birrane, E.B., Burleigh, S.B., and V.C. Cerf, "Defining
              Tolerance: Impacts of Delay and Disruption when Managing
              Challenged Networks", 2011.

   [BIRRANE3] Birrane, E.B. and H.K. Kruse, "Delay-Tolerant Network
              Management: The Definition and Exchange of Infrastructure
              Information in High Delay Environments", 2011.

              Veillette, M., Stok, P. V. D., Pelov, A., Bierman, A., and
              I. Petrov, "CoAP Management Interface (CORECONF)", Work in
              Progress, Internet-Draft, draft-ietf-core-comi-11, 17
              January 2021, <

              Veillette, M., Pelov, A., Petrov, I., and C. Bormann,
              "YANG Schema Item iDentifier (YANG SID)", Work in
              Progress, Internet-Draft, draft-ietf-core-sid-16, 24 June
              2021, <

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              Veillette, M., Petrov, I., Pelov, A., and C. Bormann,
              "CBOR Encoding of Data Modeled with YANG", Work in
              Progress, Internet-Draft, draft-ietf-core-yang-cbor-16, 24
              June 2021, <

              Burleigh, S., Fall, K., and E. J. Birrane, "Bundle
              Protocol Version 7", Work in Progress, Internet-Draft,
              draft-ietf-dtn-bpbis-31, 25 January 2021,

              Birrane, E. J. and V. Ramachandran, "Delay Tolerant
              Network Management Protocol", Work in Progress, Internet-
              Draft, draft-irtf-dtnrg-dtnmp-01, 31 December 2014,

   [RFC2119]  Bradner, S., "Key words for use in RFCs to Indicate
              Requirement Levels", BCP 14, RFC 2119,
              DOI 10.17487/RFC2119, March 1997,

   [RFC3416]  Presuhn, R., Ed., "Version 2 of the Protocol Operations
              for the Simple Network Management Protocol (SNMP)",
              STD 62, RFC 3416, DOI 10.17487/RFC3416, December 2002,

   [RFC4838]  Cerf, V., Burleigh, S., Hooke, A., Torgerson, L., Durst,
              R., Scott, K., Fall, K., and H. Weiss, "Delay-Tolerant
              Networking Architecture", RFC 4838, DOI 10.17487/RFC4838,
              April 2007, <>.

   [RFC6020]  Bjorklund, M., Ed., "YANG - A Data Modeling Language for
              the Network Configuration Protocol (NETCONF)", RFC 6020,
              DOI 10.17487/RFC6020, October 2010,

   [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,

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   [RFC7228]  Bormann, C., Ersue, M., and A. Keranen, "Terminology for
              Constrained-Node Networks", RFC 7228,
              DOI 10.17487/RFC7228, May 2014,

   [RFC7252]  Shelby, Z., Hartke, K., and C. Bormann, "The Constrained
              Application Protocol (CoAP)", RFC 7252,
              DOI 10.17487/RFC7252, June 2014,

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

   [RFC8639]  Voit, E., Clemm, A., Gonzalez Prieto, A., Nilsen-Nygaard,
              E., and A. Tripathy, "Subscription to YANG Notifications",
              RFC 8639, DOI 10.17487/RFC8639, September 2019,

   [RFC8641]  Clemm, A. and E. Voit, "Subscription to YANG Notifications
              for Datastore Updates", RFC 8641, DOI 10.17487/RFC8641,
              September 2019, <>.

Authors' Addresses

   Edward J. Birrane
   Johns Hopkins Applied Physics Laboratory


   Emery Annis
   Johns Hopkins Applied Physics Laboratory


   Sarah E. Heiner
   Johns Hopkins Applied Physics Laboratory


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