Deterministic Networking Working Group                            P. Liu
Internet-Draft                                              China Mobile
Intended status: Informational                                     Y. Li
Expires: 13 October 2022                                          Huawei
                                                               T. Eckert
                                              Futurewei Technologies USA
                                                                Q. Xiong
                                                         ZTE Corporation
                                                                 J. Ryoo
                                                           11 April 2022

          Requirements for Large-Scale Deterministic Networks


   Aiming at the large-scale deterministic network, this document
   describes the technical and operational requirements when the
   different deterministic levels of applications co-exist and are
   transported over a wide area.  This document also describes the
   corresponding Deterministic Networking (DetNet) data plane
   enhancement requirements.

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 13 October 2022.

Copyright Notice

   Copyright (c) 2022 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

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   This document is subject to BCP 78 and the IETF Trust's Legal
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   license-info) in effect on the date of publication of this document.
   Please review these documents carefully, as they describe your rights
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   provided without warranty as described in the Revised BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  Conventions Used in This Document . . . . . . . . . . . . . .   4
   3.  The Overall Characteristics of Large-Scale Deterministic
           Networks  . . . . . . . . . . . . . . . . . . . . . . . .   4
   4.  Technical Requirements in Large-Scale Deterministic
           Networks  . . . . . . . . . . . . . . . . . . . . . . . .   6
     4.1.  Tolerate Time Asynchrony  . . . . . . . . . . . . . . . .   6
       4.1.1.  Support Asynchronous Clocks Across Domains  . . . . .   6
       4.1.2.  Tolerate Clock Jitter & Wander within a Clock
               Synchronous Domain  . . . . . . . . . . . . . . . . .   7
       4.1.3.  Provide Mechanisms not Requiring Full Time
               Synchronization . . . . . . . . . . . . . . . . . . .   7
       4.1.4.  Support Asynchronization based Methods  . . . . . . .   7
     4.2.  Support Large Single-hop Propagation Latency  . . . . . .   7
     4.3.  Accommodate the Higher Link Speed . . . . . . . . . . . .   8
     4.4.  Be Scalable to Numerous Network Devices and Massive Traffic
           Flows . . . . . . . . . . . . . . . . . . . . . . . . . .   9
     4.5.  Tolerate Failures of Links or Nodes and Topology
           Changes . . . . . . . . . . . . . . . . . . . . . . . . .  10
     4.6.  Support Configuration of Multiple Queueing Mechanisms . .  10
     4.7.  Support Queueing Mechanisms Switchover Crossing
           Multi-domains . . . . . . . . . . . . . . . . . . . . . .  11
   5.  Data Plane Enhancement Requirements . . . . . . . . . . . . .  11
     5.1.  Support Aggregated Flow Identification  . . . . . . . . .  11
     5.2.  Support Queuing Related Information . . . . . . . . . . .  12
     5.3.  Support Redundancy Related Fields . . . . . . . . . . . .  12
     5.4.  Support Explicit Path Selection . . . . . . . . . . . . .  12
   6.  Conclusion  . . . . . . . . . . . . . . . . . . . . . . . . .  12
   7.  Security Considerations . . . . . . . . . . . . . . . . . . .  12
   8.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  13
   9.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  13
   10. Contributors  . . . . . . . . . . . . . . . . . . . . . . . .  13
   11. Normative References  . . . . . . . . . . . . . . . . . . . .  13
   Appendix A.  Examples of Large-Scale Deterministic Network
           Trials  . . . . . . . . . . . . . . . . . . . . . . . . .  15
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  16

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1.  Introduction

   Packet networks are evolving from bandwidth-guaranteed Quality of
   Service (QoS) to latency-guaranteed QoS that guarantees bounded
   latency and definite latency.  Bounded latency and definite latency
   can be further understood as in-time delivery, in which a packet
   arrives without exceeding a predetermined time, and on-time delivery,
   in which a packet arrives at a predetermined time, respectively.  In
   addition, network survivability, which typically guarantees traffic
   recovery within 50 ms in the event of a network failure, is evolving
   to a level that guarantees lossless recovery.  In order to realize
   the evolution of QoS and network survivability of these networks,
   Time-Sensitive Networking (TSN) technology and Deterministic
   Networking (DetNet) technology are considered to be essential.

   TSN is a set of standards developed by the IEEE 802.1 TSN Task Group
   (TG) [IEEE802.1TSN] and specifies mechanisms and protocols necessary
   to realize highly available IEEE 802.1 networks with bounded latency
   to carry time-sensitive, real-time application traffic.

   DetNet, of which architecture is defined in RFC 8655 [RFC8655],
   provides a capability to carry specified unicast or multicast data
   flows for real-time applications with extremely low data loss rates
   and bounded latency within a network domain.  The overall framework
   for DetNet data plane is provided in [RFC8938], and various documents
   on different data plane technologies and their interworking
   technologies to extend the service range of data that TSN intends to
   deliver to the IP (Internet Protocol) and MPLS (Multi-Protocol Label
   Switching) networks have been standardized.

   Since TSN and DetNet were proposed, application use cases have always
   been one of the hottest topics.  As documented in RFC 8578 [RFC8578],
   the scope of networks addressed by the current DetNet is limited to
   networks that can be centrally controlled, i.e., an "enterprise" (aka
   "corporate") network, excluding "the open Internet," explicitly.
   After years of development, TSN has been used in several industries,
   and has enough public awareness of the industry for its scope.
   DetNet also has done a lot of work and the standards are mature, and
   people become concerned about how to meet deterministic service
   demand in large-scale networks.  The current DetNet is limited to a
   single administrative domain network, and there are technical
   elements necessary for application to a large-scale network spanning
   multiple domains.

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   This document describes requirements for large-scale deterministic
   networks where different deterministic levels of applications co-
   exist and large-scale deterministic networking across multiple
   administrative domains is possible.  This document also describes the
   requirements for enhancing the DetNet data plane defined prior to
   this document.

2.  Conventions Used in This Document

   The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
   "OPTIONAL" in this document are to be interpreted as described in BCP
   14 [RFC2119][RFC8174] when, and only when, they appear in all
   capitals, as shown here.

   While [RFC2119] and [RFC8174] describe interpretations of these key
   words in terms of protocol specifications and implementations, they
   are used in this document to describe technical and operational
   requirements to realize large-scale deterministic networks.

3.  The Overall Characteristics of Large-Scale Deterministic Networks

   When deterministic network services are introduced, network providers
   always face the problem of how to match application needs to the
   technology, so more works are needed for network service providers to
   successfully sell DetNet type services to customers.  The providers
   are in need of the following:

   Service level objective definitions, considering absolute or relative
   latency and jitter bounds, flows types and physical network scale

   Suitable queuing mechanisms, considering more options for queuing
   mechanisms for different service level, and

   Deployment strategies, considering how to integrate into existing
   networks, service, and control plane.

   [RFC8578]provides various use cases and their requirements in the
   areas of industry, electricity, buildings, etc.  Some of them clearly
   specify the requirements for latency and jitter, while some others do
   not for the jitter.  Different types of users have different demands,
   just as a network provider provides different network services for
   personal business or enterprise business.

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   One kind has critical SLA requirement, such as remote control or
   cloud Programmable Logic Controller (PLC) of manufacturing and
   differential protection of electricity.  If these services exceed the
   boundaries of latency and jitter, it will bring property losses and
   security risks, so they cannot tolerate with any non-deterministic
   situation and can pay more on the network service.

   Another kind has relatively losse levels of SLA requirement, such as
   cloud gaming, cloud VR and online meeting for "consumer" networks.
   The users of these applications hope to have a better network
   experience, but they can tolerate it to a certain extent.  If the
   network quality is not good sometime, they might be willing to spend
   more money for high-quality network services.  In some aspects,
   because such services have no industry barriers and can tolerate
   exceeding the upper boundary of latency within a small probability,
   they have relatively lower requirements for the network and may be
   easier to deploy.

   Different application demands are actually related to cost.  For
   strict deterministic services, strict technologies need to be used,
   and all network devices may need to be upgraded.  For non-strict
   deterministic services, it may only be necessary to upgrade some
   network devices (maybe edge nodes) or share corresponding network
   resources.  From the perspective of deployment, it is helpful if
   there is a clear classification of application demands, including
   latency, jitter, reliability, etc.  In this way, the corresponding
   technology to implement could be chosen, taking into account both
   performance and cost, but how to make choice is not within the scope
   of this document.

                    Critical latency requirements:

        |      <->| Industrial, tight jitter, hard latency limit
        |<------->| Industrial, hard latency limit
        |<-------------.....>  Relatively lower latency requirements
        |<-------------........................>   Best effort

      Figure 1: Figure 1: Different levels of application requirements

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4.  Technical Requirements in Large-Scale Deterministic Networks

   Due to the different kinds of application requirements in large-scale
   networks, the corresponding technical requirements should be

4.1.  Tolerate Time Asynchrony

4.1.1.  Support Asynchronous Clocks Across Domains

   A large-scale network may span over multiple networks with one or
   more administrative domains.  One of DetNet's objectives is to stitch
   TSN islands together.  All devices inside a TSN domain are time-
   synchronized, and most of TSN technologies rely on precise time
   different TSN islands may have different clocks which are not
   synchronized as shown in Figure 2, where the time difference of two
   TSN domains is D.  DetNet needs to connect these two TSN domains
   together and provide end-to-end deterministic latency service.  The
   mechanism adopted by a large-scale deterministic network MUST support
   the interaction across time domains, so that time domains are
   synchronized.  This can be done, for example, by putting extra buffer
   space at the ingress of a new domain, increasing the dead time as a
   guard band, or using some timing compensation mechanism.  This
   document does not intend to list all the potential ways.

   +--------------+                             +--------------+
   |              |      DetNet Connection      |              |
   | TSN Domain I +-----------------------------+ TSN Domain II|
   |              |                             |              |
   +--------------+                             +--------------+
                    |        |        |        |        |
    Clock of TSN    +--------+--------+--------+--------+
    Domain I        =
                    =       |        |        |        |        |
    Clock of TSN    =       +--------+--------+--------+--------+
    Domain II       =       =
                    =       =

        Figure 2: Figure 2: Clock asynchrony between two TSN islands

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4.1.2.  Tolerate Clock Jitter & Wander within a Clock Synchronous Domain

   Within a single time synchronization domain, different clock accuracy
   is expected, for example the crystal oscillator in Ethernet is
   specified at 100 ppm[Fast-Ethernet-MII-clock], Synchronous Ethernet
   (SyncE) can achieve 50 ppb[G.8262], and more precise time
   synchronization[G.8273] is expected in 5G mobile backhaul.  The
   clocks experience different jitter and wander.  It may cause
   different level of asymmetry of the path.  The large-scale networks
   SHOULD be able to recover or absorb such time variance within a
   domain and across multiple domains.

4.1.3.  Provide Mechanisms not Requiring Full Time Synchronization

   Some networks like mobile backhaul use frequency synchronization,
   such as SyncE, instead of the strict time synchronization.  It is
   usually hard to achieve the full time synchronization in large-scale
   networks when considering the size of the network topology.  It is
   desired that the same deterministic performance in term of the
   bounded latency and jitter SHOULD be achieved when full time
   synchronization is not available, that is to say, when only partial
   synchronization (SyncE is one of the examples) is in use.

4.1.4.  Support Asynchronization based Methods

   There are a large number of traffic flows in a large-scale network
   and some of them are acyclic.  Asynchronization based methods can
   meet the requirements of those traffic flows.  Moreover, The
   mechanisms not requiring the time and/or frequency synchronization
   eliminate the hardware cost and difficulty at the network
   nodes.[IEEE802.1Qcr] conceptually uses per-flow based asynchronous
   shaper to achieve bounded latency.  The formula proof shows its
   effectiveness.  It can naturally tolerate the time variance, but it
   exhibits the concerns of per-flow state buffer management as shown
   in[I-D.eckert-detnet-bounded-latency-problems]When it is in use, the
   requirement in Section 4.3 SHOULD be carefully met.

4.2.  Support Large Single-hop Propagation Latency

   In a large-scale network, a single hop distance is enough to generate
   large latency.  The speed of optical transmission in fiber is 200 km/
   ms.  Thus, the propagation delay of a single hop can be in the order
   of a few milliseconds.  It is much greater than that of a LAN, and
   introduces impacts on queuing mechanisms, such as cyclic or time
   aware scheduling method.

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   For a cyclic based method, suppose a large-scale network wants to
   keep using the simple cycle mapping relationship, however the link
   distance between two nodes is longer.  Moreover, a downstream node
   may have many upstream nodes each with different link propagation
   delays (e.g., 9 us, 10 us, 11 us, 15 us and 20 us).  In order to
   absorb the longest link propagation delay, the length of cycle must
   be set to at least 20 us.  However, since packet's arrival time
   varies within the receiving cycle, larger cycle length means larger
   delay variance.

               Upstream Node X  |sending cycle  |            |
                                =  "\           =            =
                                =  " \          =            =
                                =  "  \         =            =
                                =  "   \        =            =
                                =  "    V       =            =
              Downstream Node Y |receiving cycle|            |
                                =  "    "       =     \      =
                                =  "    "       =      V resent out
                                =  "    "       =            =
                   Time Line   -=--"----"-------=------------=----->
                   (in us)      0  |    |   10           20
                                   v    v
                             Transmission Latency

       Figure 3: Figure 3: The influence of transmission latency on a
                               cyclic method

4.3.  Accommodate the Higher Link Speed

   A large-scale network normally uses higher speed links, especially
   for its backbone.  Current deterministic mechanisms used in a local
   network is usually deployed in link speed of 10 Mbps or 1 Gbps, or
   possibly 10 Gbps.  The data rate of 10G, 100G, 400G and even higher
   is commonly used in wide area networks.  With the increasing of the
   data rate, the network scheduling cycle can be reduced if the same
   amount of the data is required to be sent each cycle for each
   application.  Or more data can be sent if the network cycle time
   remains the same.  For the former, it requires the more precise time
   control (e.g. cycle in the order of a few microseconds or sub-
   microseconds) for the input stream gate and the timed output buffer.
   For the latter, more buffer space is required which imposes more
   complex buffer or queue management and larger memory consumption.

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   Another aspect to consider is the aggregation of the flows.  In the
   large-scale network, the number of flows can be hundreds or tens of
   thousands.  They can be aggregated into a small number of
   deterministic path or tunnels.  It is practical to have a few flow-
   based or aggregated-flow based status in the local network.  But in
   higher speed and larger scale networks, it is hardly feasible.
   If[IEEE802.1Qcr]is in use, it requires more buffers comparing to the
   other full/partial time synchronized mechanisms.  Therefore, it
   requires optimizations to support higher link speeds.

4.4.  Be Scalable to Numerous Network Devices and Massive Traffic Flows

   Comparing to a LAN, a large-scale network may have more network
   devices and traffic flows, and there is a greater possibility of
   adding or removing network devices and traffic flows.  The
   deterministic latency forwarding mechanisms MUST scale to networks of
   significant size with numerous network devices and a massive traffic

   The increase or decrease of network devices in large-scale networks
   is more frequent than that in LANs.  The change of the number of
   devices may affect the implementation and adjustment of deterministic
   network mechanism, such as the topology discovery, queuing mechanism
   and packet replication and elimination.  A simple use case to
   understand is ultra-low-latency (public) 5G transport networks, which
   would require DetNet extend to every 5G base station.  For some
   network operators, their networks may need to connect to ~100 K base
   stations (serving multiple mobile networks operators), and this
   number will only increase with 5G.

   It is almost impossible to identify individual IP flows at the DetNet
   data plane because of the large overhead and resource reservation for
   a massive number of flows.  DetNet allows the leverage of the flow
   aggregation.  With the large scaling of the network, proper provision
   at the control plane to accommodate such higher aggregation is
   required.  Individual flows may join and exit the aggregated flow
   rapidly which causes the dynamic in identification of the aggregated
   DetNet flow.  The wildcards and value ranges used in the
   identification may have to change in order to ensure the aggregated
   flows have compatible deterministic characteristics.

   The micro-burst will happen more often due to the massive traffic
   flows, so some methods to decrease it are
   needed.[I-D.du-detnet-layer3-low-latency]introduces a reference
   method requiring a scalable buffer to adjust the speed of sending the
   packets, so as to keep a uniform transmission rate, and it also
   support the flow aggregation.

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4.5.  Tolerate Failures of Links or Nodes and Topology Changes

   Network link failures are more common in large-scale networks.  Path
   switching or re-convergence of routing will cause high latency of
   packet loss and retransmission, which is usually in seconds before
   the network becomes stable again.  It is necessary to support certain
   mechanisms to adapt to failures of links or nodes and topology

   The change of path or topology poses a higher challenge to packet
   replication and elimination.  The full disjoint paths when
   implementing the Packet Replication, Elimination, and Ordering
   Functions (PREOF) gives a better chance of survival when one of the
   nodes or links in the path fails.  At the same time, it brings the
   challenges of finding paths with similar distance and/or number of
   hops so that there is enough buffer space to absorb the latency
   difference caused by different paths when the scale is large.

4.6.  Support Configuration of Multiple Queueing Mechanisms

   It is required to provide diversified deterministic service for
   various applications in a large-scale network and to support the
   corresponding diversified queueing mechanisms (possibly at multiple
   DetNet QoS levels).  Different queueing mechanisms can provide
   different levels of latency, jitter and other guarantees, and there
   may be situations where a network device provides multiple queueing
   mechanisms at the same time.  For example, a network aggregation
   device may use the mechanisms specified in [IEEE802.1Qbv] and
   [IEEE802.1Qcr], and other mechanisms to forward traffic to different
   paths at the same time.  By providing a variety of queueing
   mechanisms to meet diversified deterministic service Requirements,
   compared with LAN environment, this demand is particularly prominent
   in large-scale networks.  There are usually eight traffic classes in
   TSN enabled networks.  The different queueing mechanisms can be
   employed to the queues of one or more of those traffic class.  In
   practice, there may be more than eight queues or sub-queues to
   support more complicated queueing mechanisms.

   Accordingly, the configuration for multiple queueing mechanisms is
   complicated in large-scale deterministic networks and MUST support
   the unified or simplified scheduling and management of multiple queue
   mechanisms.  For example, in the distributed scenario where there is
   no controller, flooding the related information of the queue
   mechanism, including the types and related algorithms, queue
   forwarding capability, etc.  In the centralized scenario, the
   queueing mechanisms and other information could be reported to the
   controller to build a deterministic network resource topology pool
   for path calculation.

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4.7.  Support Queueing Mechanisms Switchover Crossing Multi-domains

   In large-scale deterministic networks, it may across multiple network
   domains and adopt a variety of different queueing mechanisms within
   each domain.  It is required to support the inter-domain
   deterministic mechanism at the inter-domain boundary nodes such as
   the priority redefinition and rescheduling of queues to achieve the
   end-to-end latency, bounded jitter and packet loss ratio.

   Moreover, changing from one queueing mechanism to another may
   generate additional end-to-end latency and/or jitter which should be
   taken into consideration.  For example, when a flow is forwarded
   across multiple network domains based on different queueing
   mechanisms, such as a time synchronous Qbv mechanism[IEEE802.1Qbv]
   and an asynchronous Qcr mechanism [IEEE802.1Qcr], a collaboration
   mechanism crossing multi-domains MUST be considered, such as
   increasing the buffer of inter-domain devices to provide enough
   adjustment space for the flow to cross different queueing mechanisms,
   so as to provide end-to-end deterministic services across multiple
   network domains.

5.  Data Plane Enhancement Requirements

   According to[RFC8938], the DetNet data plane can provide or carry two
   metadata in MPLS and IP data planes: Flow-ID and sequence number.
   The Flow-ID could be used for identification of the DetNet flow or
   aggregate flow, and the sequence number could be used for PREOF for
   each DetNet flow.  The Flow-ID is used by both the service and
   forwarding sub-layers, but the sequence number is only used by the
   service layer.  Metadata can also be used for OAM indications and
   instrumentation of DetNet data plane operation.

   Generally speaking, more data plane metadata and related processing
   SHOULD be supported in the large-scale networks.  Native IPv6 data
   plane should be supported.  This section lists the data plane
   enhancement requirements based on but not limited to the technical
   requirements in Section 4.

5.1.  Support Aggregated Flow Identification

   Current IPv6 aggregated flow identification is generally based on 5
   or 6 tuples, IP prefixes, or wildcards as indicated in [RFC8938].
   However, in large-scale deterministic networks the number of
   individual flows is huge, and they may randomly join and leave the
   aggregated flow at each hop.  Such behaviours lead to the difficulty
   in identifying aggregated flows by relying on the prefixes or

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   In addition, flow identification is also used to quickly push a
   packet to a suitable queue.  In a large-scale network, there are mix
   of flows requiring deterministic latency service and normal
   forwarding service.  Explicit flow identification makes it easier to
   quickly distinguish the DetNet flows without requiring the longest
   match rule on multiple tuples in IP data plane.  Therefore, explicit
   aggregated flow identification SHOULD be supported.

5.2.  Support Queuing Related Information

   According to Section 4.1, a large-scale network should support
   synchronized or asynchronized queuing mechanisms.  Different queueing
   mechanisms require different metadata to be defined to help
   regulation and queue management.  For instance, the data plane MUST
   support the identification of cycle for cyclic queuing or the timing
   related information for time based queuing.

5.3.  Support Redundancy Related Fields

   Sequence number is the only metadata currently defined for redundancy
   feature of Detnet.  MPLS data plane uses Detnet-over-MPLS label stack
   to carry it.  At the same time, native IPv6 data plane should be able
   to carry this information too.  If specific IP encapsulation or
   tunnel is in use, this meta data should be defined explicitly for
   that data plane.

5.4.  Support Explicit Path Selection

   Explicit route at the control plane and/or management is required so
   that the "best" path can be selected to meet the latency requirement
   for DetNet flows.  At the data planes, MPLS label stack can be used
   for this purpose.  IP data plane enhancement is required to support
   the explicit path selection based on IP source routing or SRv6.

6.  Conclusion

   This document specifies the technical requirements when ensuring the
   deterministic features in the large-scale networks, and the
   corresponding data plane enhancement requirements to support the
   them.  Some of the proposed queueing mechanisms and trials are cited
   and the authors of the document think those proposals give reasonably
   sound insights to enhancement the current queueing mechanisms to meet
   the deterministic requirements of the large-scale networks.

7.  Security Considerations

   There are no IANA actions required by this document.

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8.  IANA Considerations

   This section will be described later.

9.  Acknowledgements

   The authors would like to thank Yaakov Stein for helpful suggestions.
   The authors also would like to thank Liang Geng, Peter Willis,
   Shunsuke Homma and Li Qiang for their previous works.

10.  Contributors

   The following people have substantially contributed to this document:

           Zongpeng Du
           China Mobile

11.  Normative References

              "Fast Ethernet MII clock".

   [G.8262]   International Telecommunication Union, "Timing
              characteristics of a synchronous equipment slave clock",
              ITU-T Recommendation G.8262, November 2018.

   [G.8273]   International Telecommunication Union, "Framework of phase
              and time clocks", ITU-T Recommendation G.8273, March 2018.

              Liu, B. and J. Dang, "A Queuing Mechanism with Multiple
              Cyclic Buffers", Work in Progress, Internet-Draft, draft-
              dang-queuing-with-multiple-cyclic-buffers-00, 22 February
              2021, <

              Du, Z. and P. Liu, "Micro-burst Decreasing in Layer3
              Network for Low-Latency Traffic", Work in Progress,
              Internet-Draft, draft-du-detnet-layer3-low-latency-04, 25
              October 2021, <

              Eckert, T. and S. Bryant, "Problems with existing DetNet
              bounded latency queuing mechanisms", Work in Progress,
              Internet-Draft, draft-eckert-detnet-bounded-latency-

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              problems-00, 12 July 2021,

              Geng, L., Willis, P., Homma, S., and L. Qiang,
              "Requirements of Layer 3 Deterministic Latency Service",
              Work in Progress, Internet-Draft, draft-geng-detnet-
              requirements-bounded-latency-03, 7 July 2019,

              Qiang, L., Geng, X., Liu, B., Eckert, T., Geng, L., and G.
              Li, "Large-Scale Deterministic IP Network", Work in
              Progress, Internet-Draft, draft-qiang-detnet-large-scale-
              detnet-05, 2 September 2019,

              IEEE, "IEEE Standard for Local and metropolitan area
              networks -- Virtual Bridged Local Area Networks -
              Amendment 12: Forwarding and Queuing Enhancements for
              Time-Sensitive Streams", IEEE 802.1Qav-2009,
              DOI 10.1109/IEEESTD.2010.8684664, 5 January 2010,

              IEEE, "IEEE Standard for Local and metropolitan area
              networks -- Bridges and Bridged Networks - Amendment 25:
              Enhancements for Scheduled Traffic", IEEE 802.1Qbv-2015,
              DOI 10.1109/IEEESTD.2016.8613095, 18 March 2016,

              IEEE, "IEEE Standard for Local and metropolitan area
              networks -- Bridges and Bridged Networks - Amendment 29:
              Cyclic Queuing and Forwarding", IEEE 802.1Qch-2017,
              DOI 10.1109/IEEESTD.2017.7961303, 28 June 2017,

              IEEE, "IEEE Standard for Local and Metropolitan Area
              Networks -- Bridges and Bridged Networks - Amendment 34:
              Asynchronous Traffic Shaping", IEEE 802.1Qcr-2020,
              DOI 10.1109/IEEESTD.2020.9253013, 6 November 2020,

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              IEEE Standards Association, "IEEE 802.1 Time-Sensitive
              Networking Task Group",

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

   [RFC8174]  Leiba, B., "Ambiguity of Uppercase vs Lowercase in RFC
              2119 Key Words", BCP 14, RFC 8174, DOI 10.17487/RFC8174,
              May 2017, <>.

   [RFC8578]  Grossman, E., Ed., "Deterministic Networking Use Cases",
              RFC 8578, DOI 10.17487/RFC8578, May 2019,

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

   [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,

Appendix A.  Examples of Large-Scale Deterministic Network Trials

   Some trials have been carried out to verify the concept of large-
   scale deterministic networks.

   In order to verify the deterministic technology of large-scale
   networks, a trial of Deterministic IP on China Environment for
   Network Innovations (CENI), which is a network built for new network
   technology trial, was deployed.  A network with a distance of 3,000
   km over 13 hops was tested, and the jitter was controlled within

   In order to verify the remote control on Deterministic IP, which
   required that the latency should be controlled within 4 ms and jitter
   should be controlled within 20 us.  A trial cooperated with Baosteel
   spanned 600 km was deployed.  Baosteel is a Chinese steel company and
   put forward this demand.  Both of the first and second trials are
   based on a frequency synchronization solution.  The mechanism details
   could be found in . [I-D.dang-queuing-with-multiple-cyclic-buffers][I

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   In order to realize multi flows synchronization on an inter-
   provincial network in an exhibition, Emergen proposed the requirement
   that two flows of video and virtual reality (VR) were sent from
   province A, and arrived at province B together, so people can see the
   synchronization of video collected by camera and the VR model.  This
   requirement was proposed to facilitate the virtual industry product
   deployment.  Due to time and other problems, it was realized by the
   edge network device for a relatively lower levels of service level
   agreement (SLA).

   Teaming up with a smart factory operator, network operators,
   equipment companies, and universities, ETRI demonstrated an ultra-low
   latency, high-reliability 5G wired and wireless network-based remote
   industrial Internet of Things (IIoT) service by connecting a control
   center and a smart factory through three different operators'
   networks at a distance of 280 km.  In this trail, it was demonstrated
   that real-time remote smart manufacturing service is possible by
   making round-trip delay below 3 ms within a smart factory and below
   10 ms between remote 5G industrial devices.  In the future, the team
   plans to examine feasibility of large-scale deterministic networking
   by connecting smart factories in Gyeongsan, South Korea and Oulu,

   These trials show that both operators and enterprise users begin to
   put forward requirements for the certainty of large-scale networks,
   but the implementation technologies are not exactly the same.

Authors' Addresses

   Peng Liu
   China Mobile

   Yizhou Li

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   Toerless Eckert
   Futurewei Technologies USA
   Santa Clara,  95014
   United States of America

   Quan Xiong
   ZTE Corporation

   Jeong-dong Ryoo
   South Korea

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