Internet DRAFT - draft-finn-detnet-bounded-latency

draft-finn-detnet-bounded-latency







DetNet                                                           N. Finn
Internet-Draft                               Huawei Technologies Co. Ltd
Intended status: Informational                            J-Y. Le Boudec
Expires: December 27, 2019                               E. Mohammadpour
                                                                    EPFL
                                                                J. Zhang
                                             Huawei Technologies Co. Ltd
                                                                B. Varga
                                                               J. Farkas
                                                                Ericsson
                                                           June 25, 2019


                         DetNet Bounded Latency
                  draft-finn-detnet-bounded-latency-04

Abstract

   This document presents a timing model for Deterministic Networking
   (DetNet), so that existing and future standards can achieve the
   DetNet quality of service features of bounded latency and zero
   congestion loss.  It defines requirements for resource reservation
   protocols or servers.  It calls out queuing mechanisms, defined in
   other documents, that can provide the DetNet quality of service.

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
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   This Internet-Draft will expire on December 27, 2019.

Copyright Notice

   Copyright (c) 2019 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
   Provisions Relating to IETF Documents
   (https://trustee.ietf.org/license-info) in effect on the date of
   publication of this document.  Please review these documents
   carefully, as they describe your rights and restrictions with respect
   to this document.  Code Components extracted from this document must
   include Simplified BSD License text as described in Section 4.e of
   the Trust Legal Provisions and are provided without warranty as
   described in the Simplified BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Terminology and Definitions . . . . . . . . . . . . . . . . .   3
   3.  DetNet bounded latency model  . . . . . . . . . . . . . . . .   4
     3.1.  Flow creation . . . . . . . . . . . . . . . . . . . . . .   4
       3.1.1.  Static flow latency calculation . . . . . . . . . . .   4
       3.1.2.  Dynamic flow latency calculation  . . . . . . . . . .   5
     3.2.  Relay node model  . . . . . . . . . . . . . . . . . . . .   6
   4.  Computing End-to-end Latency Bounds . . . . . . . . . . . . .   8
     4.1.  Non-queuing delay bound . . . . . . . . . . . . . . . . .   8
     4.2.  Queuing delay bound . . . . . . . . . . . . . . . . . . .   8
       4.2.1.  Per-flow queuing mechanisms . . . . . . . . . . . . .   9
       4.2.2.  Per-class queuing mechanisms  . . . . . . . . . . . .   9
     4.3.  Ingress considerations  . . . . . . . . . . . . . . . . .  10
     4.4.  Interspersed non-DetNet transit nodes . . . . . . . . . .  11
   5.  Achieving zero congestion loss  . . . . . . . . . . . . . . .  11
     5.1.  A General Formula . . . . . . . . . . . . . . . . . . . .  11
   6.  Queuing techniques  . . . . . . . . . . . . . . . . . . . . .  12
     6.1.  Queuing data model  . . . . . . . . . . . . . . . . . . .  12
     6.2.  Preemption  . . . . . . . . . . . . . . . . . . . . . . .  14
     6.3.  Time-scheduled queuing  . . . . . . . . . . . . . . . . .  15
     6.4.  Credit-Based Shaper with Asynchronous Traffic Shaping . .  16
       6.4.1.  Flow Admission  . . . . . . . . . . . . . . . . . . .  19
     6.5.  IntServ . . . . . . . . . . . . . . . . . . . . . . . . .  20
     6.6.  Cyclic Queuing and Forwarding . . . . . . . . . . . . . .  22
       6.6.1.  CQF timing sequence . . . . . . . . . . . . . . . . .  23
       6.6.2.  CQF latency calculation . . . . . . . . . . . . . . .  24
   7.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  24
     7.1.  Normative References  . . . . . . . . . . . . . . . . . .  24
     7.2.  Informative References  . . . . . . . . . . . . . . . . .  25
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  26

1.  Introduction

   The ability for IETF Deterministic Networking (DetNet) or IEEE 802.1
   Time-Sensitive Networking (TSN, [IEEE8021TSN]) to provide the DetNet
   services of bounded latency and zero congestion loss depends upon A)



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   configuring and allocating network resources for the exclusive use of
   DetNet/TSN flows; B) identifying, in the data plane, the resources to
   be utilized by any given packet, and C) the detailed behavior of
   those resources, especially transmission queue selection, so that
   latency bounds can be reliably assured.  Thus, DetNet is an example
   of an IntServ Guaranteed Quality of Service [RFC2212]

   As explained in [I-D.ietf-detnet-architecture], DetNet flows are
   characterized by 1) a maximum bandwidth, guaranteed either by the
   transmitter or by strict input metering; and 2) a requirement for a
   guaranteed worst-case end-to-end latency.  That latency guarantee, in
   turn, provides the opportunity for the network to supply enough
   buffer space to guarantee zero congestion loss.

   To be of use to the applications identified in [RFC8578], it must be
   possible to calculate, before the transmission of a DetNet flow
   commences, both the worst-case end-to-end network latency, and the
   amount of buffer space required at each hop to ensure against
   congestion loss.

   This document references specific queuing mechanisms, defined in
   other documents, that can be used to control packet transmission at
   each output port and achieve the DetNet qualities of service.  This
   document presents a timing model for sources, destinations, and the
   DetNet transit nodes that relay packets that is applicable to all of
   those referenced queuing mechanisms.

   Using the model presented in this document, it should be possible for
   an implementor, user, or standards development organization to select
   a particular set of queuing mechanisms for each device in a DetNet
   network, and to select a resource reservation algorithm for that
   network, so that those elements can work together to provide the
   DetNet service.

   This document does not specify any resource reservation protocol or
   server.  It does not describe all of the requirements for that
   protocol or server.  It does describe requirements for such resource
   reservation methods, and for queuing mechanisms that, if met, will
   enable them to work together.

2.  Terminology and Definitions

   This document uses the terms defined in
   [I-D.ietf-detnet-architecture].







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3.  DetNet bounded latency model

3.1.  Flow creation

   This document assumes that following paradigm is used for
   provisioning DetNet flows:

   1.  Perform any configuration required by the DetNet transit nodes in
       the network for the classes of service to be offered, including
       one or more classes of DetNet service.  This configuration is
       done beforehand, and not tied to any particular flow.

   2.  Characterize the new DetNet flow, particularly in terms of
       required bandwidth.

   3.  Establish the path that the DetNet flow will take through the
       network from the source to the destination(s).  This can be a
       point-to-point or a point-to-multipoint path.

   4.  Select one of the DetNet classes of service for the DetNet flow.

   5.  Compute the worst-case end-to-end latency for the DetNet flow,
       using one of the methods, below (Section 3.1.1, Section 3.1.2).
       In the process, determine whether sufficient resources are
       available for that flow to guarantee the required latency and to
       provide zero congestion loss.

   6.  Assuming that the resources are available, commit those resources
       to the flow.  This may or may not require adjusting the
       parameters that control the filtering and/or queuing mechanisms
       at each hop along the flow's path.

   This paradigm can be implemented using peer-to-peer protocols or
   using a central server.  In some situations, a lack of resources can
   require backtracking and recursing through this list.

   Issues such as un-provisioning a DetNet flow in favor of another when
   resources are scarce are not considered, here.  Also not addressed is
   the question of how to choose the path to be taken by a DetNet flow.

3.1.1.  Static flow latency calculation

   The static problem:
           Given a network and a set of DetNet flows, compute an end-to-
           end latency bound (if computable) for each flow, and compute
           the resources, particularly buffer space, required in each
           DetNet transit node to achieve zero congestion loss.




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   In this calculation, all of the DetNet flows are known before the
   calculation commences.  This problem is of interest to relatively
   static networks, or static parts of larger networks.  It gives the
   best possible worst-case behavior.  The calculations can be extended
   to provide global optimizations, such as altering the path of one
   DetNet flow in order to make resources available to another DetNet
   flow with tighter constraints.

   The static flow calculation is not limited only to static networks;
   the entire calculation for all flows can be repeated each time a new
   DetNet flow is created or deleted.  If some already-established flow
   would be pushed beyond its latency requirements by the new flow, then
   the new flow can be refused, or some other suitable action taken.

   This calculation may be more difficult to perform than that of the
   dynamic calculation (Section 3.1.2), because the flows passing
   through one port on a DetNet transit node affect each others'
   latency.  The effects can even be circular, from Flow A to B to C and
   back to A.  On the other hand, the static calculation can often
   accommodate queuing methods, such as transmission selection by strict
   priority, that are unsuitable for the dynamic calculation.

3.1.2.  Dynamic flow latency calculation

   The dynamic problem:
           Given a network whose maximum capacity for DetNet flows is
           bounded by a set of static configuration parameters applied
           to the DetNet transit nodes, and given just one DetNet flow,
           compute the worst-case end-to-end latency that can be
           experienced by that flow, no matter what other DetNet flows
           (within the network's configured parameters) might be created
           or deleted in the future.  Also, compute the resources,
           particularly buffer space, required in each DetNet transit
           node to achieve zero congestion loss.

   This calculation is dynamic, in the sense that flows can be added or
   deleted at any time, with a minimum of computation effort, and
   without affecting the guarantees already given to other flows.

   The choice of queuing methods is critical to the applicability of the
   dynamic calculation.  Some queuing methods (e.g.  CQF, Section 6.6)
   make it easy to configure bounds on the network's capacity, and to
   make independent calculations for each flow.  Other queuing methods
   (e.g., transmission selection by strict priority), make this
   calculation impossible, because the worst case for one flow cannot be
   computed without complete knowledge of all other flows.  Other
   queuing methods (e.g. the credit-based shaper defined in [IEEE8021Q]
   section 8.6.8.2) can be used for dynamic flow creation, but yield



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   poorer latency and buffer space guarantees than when that same
   queuing method is used for static flow creation (Section 3.1.1).

3.2.  Relay node model

   A model for the operation of a DetNet transit node is required, in
   order to define the latency and buffer calculations.  In Figure 1 we
   see a breakdown of the per-hop latency experienced by a packet
   passing through a DetNet transit node, in terms that are suitable for
   computing both hop-by-hop latency and per-hop buffer requirements.

         DetNet transit node A            DetNet transit node B
      +-------------------------+       +------------------------+
      |              Queuing    |       |              Queuing   |
      |   Regulator subsystem   |       |   Regulator subsystem  |
      |   +-+-+-+-+ +-+-+-+-+   |       |   +-+-+-+-+ +-+-+-+-+  |
   -->+   | | | | | | | | | +   +------>+   | | | | | | | | | +  +--->
      |   +-+-+-+-+ +-+-+-+-+   |       |   +-+-+-+-+ +-+-+-+-+  |
      |                         |       |                        |
      +-------------------------+       +------------------------+
      |<->|<------>|<------->|<->|<---->|<->|<------>|<------>|<->|<--
   2,3  4      5        6      1    2,3   4      5        6     1   2,3
                   1: Output delay       4: Processing delay
                   2: Link delay         5: Regulation delay
                   3: Preemption delay   6: Queuing delay.

                 Figure 1: Timing model for DetNet or TSN

   In Figure 1, we see two DetNet transit nodes (typically, bridges or
   routers), with a wired link between them.  In this model, the only
   queues we deal with explicitly are attached to the output port; other
   queues are modeled as variations in the other delay times.  (E.g., an
   input queue could be modeled as either a variation in the link delay
   [2] or the processing delay [4].)  There are six delays that a packet
   can experience from hop to hop.

   1.  Output delay
      The time taken from the selection of a packet for output from a
      queue to the transmission of the first bit of the packet on the
      physical link.  If the queue is directly attached to the physical
      port, output delay can be a constant.  But, in many
      implementations, the queuing mechanism in a forwarding ASIC is
      separated from a multi-port MAC/PHY, in a second ASIC, by a
      multiplexed connection.  This causes variations in the output
      delay that are hard for the forwarding node to predict or control.

   2.  Link delay




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      The time taken from the transmission of the first bit of the
      packet to the reception of the last bit, assuming that the
      transmission is not suspended by a preemption event.  This delay
      has two components, the first-bit-out to first-bit-in delay and
      the first-bit-in to last-bit-in delay that varies with packet
      size.  The former is typically measured by the Precision Time
      Protocol and is constant (see [I-D.ietf-detnet-architecture]).
      However, a virtual "link" could exhibit a variable link delay.

   3.  Preemption delay
      If the packet is interrupted in order to transmit another packet
      or packets, (e.g.  [IEEE8023] clause 99 frame preemption) an
      arbitrary delay can result.

   4.  Processing delay
      This delay covers the time from the reception of the last bit of
      the packet to the time the packet is enqueued in the regulator
      (Queuing subsystem, if there is no regulation).  This delay can be
      variable, and depends on the details of the operation of the
      forwarding node.

   5.  Regulator delay
      This is the time spent from the insertion of the last bit of a
      packet into a regulation queue until the time the packet is
      declared eligible according to its regulation constraints.  We
      assume that this time can be calculated based on the details of
      regulation policy.  If there is no regulation, this time is zero.

   6.  Queuing subsystem delay
      This is the time spent for a packet from being declared eligible
      until being selected for output on the next link.  We assume that
      this time is calculable based on the details of the queuing
      mechanism.  If there is no regulation, this time is from the
      insertion of the packet into a queue until it is selected for
      output on the next link.

   Not shown in Figure 1 are the other output queues that we presume are
   also attached to that same output port as the queue shown, and
   against which this shown queue competes for transmission
   opportunities.

   The initial and final measurement point in this analysis (that is,
   the definition of a "hop") is the point at which a packet is selected
   for output.  In general, any queue selection method that is suitable
   for use in a DetNet network includes a detailed specification as to
   exactly when packets are selected for transmission.  Any variations
   in any of the delay times 1-4 result in a need for additional buffers
   in the queue.  If all delays 1-4 are constant, then any variation in



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   the time at which packets are inserted into a queue depends entirely
   on the timing of packet selection in the previous node.  If the
   delays 1-4 are not constant, then additional buffers are required in
   the queue to absorb these variations.  Thus:

   o  Variations in output delay (1) require buffers to absorb that
      variation in the next hop, so the output delay variations of the
      previous hop (on each input port) must be known in order to
      calculate the buffer space required on this hop.

   o  Variations in processing delay (4) require additional output
      buffers in the queues of that same DetNet transit node.  Depending
      on the details of the queueing subsystem delay (6) calculations,
      these variations need not be visible outside the DetNet transit
      node.

4.  Computing End-to-end Latency Bounds

4.1.  Non-queuing delay bound

   End-to-end latency bounds can be computed using the delay model in
   Section 3.2.  Here it is important to be aware that for several
   queuing mechanisms, the worst-case end-to-end delay is less than the
   sum of the per-hop worst-case delays.  An end-to-end latency bound
   for one DetNet flow can be computed as

      end_to_end_latency_bound = non_queuing_latency + queuing_latency

   The two terms in the above formula are computed as follows.  First,
   at the h-th hop along the path of this DetNet flow, obtain an upper
   bound per-hop_non_queuing_latency[h] on the sum of delays 1,2,3,4 of
   Figure 1.  These upper-bounds are expected to depend on the specific
   technology of the DetNet transit node at the h-th hop but not on the
   T-SPEC of this DetNet flow.  Then set non_queuing_latency = the sum
   of per-hop_non_queuing_latency[h] over all hops h.

4.2.  Queuing delay bound

   Second, compute queuing_latency as an upper bound to the sum of the
   queuing delays along the path.  The value of queuing_latency depends
   on the T-SPEC of this flow and possibly of other flows in the
   network, as well as the specifics of the queuing mechanisms deployed
   along the path of this flow.

   For several queuing mechanisms, queuing_latency is less than the sum
   of upper bounds on the queuing delays (5,6) at every hop.  This
   occurs with (1) per-flow queuing, and (2) per-class queuing with




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   regulators, as explained in Section 4.2.1, Section 4.2.2, and
   Section 6.

   For other queuing mechanisms the only available value of
   queuing_latency is the sum of the per-hop queuing delay bounds.  In
   such cases, the computation of per-hop queuing delay bounds must
   account for the fact that the T-SPEC of a DetNet flow is no longer
   satisfied at the ingress of a hop, since burstiness increases as one
   flow traverses one DetNet transit node.

4.2.1.  Per-flow queuing mechanisms

   With such mechanisms, each flow uses a separate queue inside every
   node.  The service for each queue is abstracted with a guaranteed
   rate and a delay.  For every flow the per-node delay bound as well as
   end-to-end delay bound can be computed from the traffic specification
   of this flow at its source and from the values of rates and latencies
   at all nodes along its path.  Details of calculation for IntServ are
   described in Section 6.5.

4.2.2.  Per-class queuing mechanisms

   With such mechanisms, the flows that have the same class share the
   same queue.  A practical example is the credit-based shaper defined
   in section 8.6.8.2 of [IEEE8021Q].  One key issue in this context is
   how to deal with the burstiness cascade: individual flows that share
   a resource dedicated to a class may see their burstiness increase,
   which may in turn cause increased burstiness to other flows
   downstream of this resource.  Computing latency upper bounds for such
   cases is difficult, and in some conditions impossible
   [charny2000delay][bennett2002delay].  Also, when bounds are obtained,
   they depend on the complete configuration, and must be recomputed
   when one flow is added.  (The dynamic calculation, Section 3.1.2.)

   A solution to deal with this issue is to reshape the flows at every
   hop.  This can be done with per-flow regulators (e.g. leaky bucket
   shapers), but this requires per-flow queuing and defeats the purpose
   of per-class queuing.  An alternative is the interleaved regulator,
   which reshapes individual flows without per-flow queuing
   ([Specht2016UBS], [IEEE8021Qcr]).  With an interleaved regulator, the
   packet at the head of the queue is regulated based on its (flow)
   regulation constraints; it is released at the earliest time at which
   this is possible without violating the constraint.  One key feature
   of per-flow or interleaved regulator is that, it does not increase
   worst-case latency bounds [le_boudec_theory_2018].  Specifically,
   when an interleaved regulator is appended to a FIFO subsystem, it
   does not increase the worst-case delay of the latter.




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   Figure 2 shows an example of a network with 5 nodes, per-class
   queuing mechanism and interleaved regulators as in Figure 1.  An end-
   to-end delay bound for flow f, traversing nodes 1 to 5, is calculated
   as follows:

      end_to_end_latency_bound_of_flow_f = C12 + C23 + C34 + S4

   In the above formula, Cij is a bound on the aggregate response time
   of queuing subsystem in node i and interleaved regulator of node j,
   and S4 is a bound on the response time of the queuing subsystem in
   node 4 for flow f.  In fact, using the delay definitions in
   Section 3.2, Cij is a bound on sum of the delays 1,2,3,6 of node i
   and 4,5 of node j.  Similarly, S4 is a bound on sum of the delays
   1,2,3,6 of node 4.  A practical example of queuing model and delay
   calculation is presented Section 6.4.

                               f
                     ----------------------------->
                   +---+   +---+   +---+   +---+   +---+
                   | 1 |---| 2 |---| 3 |---| 4 |---| 5 |
                   +---+   +---+   +---+   +---+   +---+
                      \__C12_/\__C23_/\__C34_/\_S4_/

             Figure 2: End-to-end latency computation example

   REMARK: The end-to-end delay bound calculation provided here gives a
   much better upper bound in comparison with end-to-end delay bound
   computation by adding the delay bounds of each node in the path of a
   flow [TSNwithATS].

4.3.  Ingress considerations

   A sender can be a DetNet node which uses exactly the same queuing
   methods as its adjacent DetNet transit node, so that the latency and
   buffer calculations at the first hop are indistinguishable from those
   at a later hop within the DetNet domain.  On the other hand, the
   sender may be DetNet unaware, in which case some conditioning of the
   flow may be necessary at the ingress DetNet transit node.

   This ingress conditioning typically consists of a FIFO with an output
   regulator that is compatible with the queuing employed by the DetNet
   transit node on its output port(s).  For some queuing methods, simply
   requires added extra buffer space in the queuing subsystem.  Ingress
   conditioning requirements for different queuing methods are mentioned
   in the sections, below, describing those queuing methods.






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4.4.  Interspersed non-DetNet transit nodes

   It is sometimes desirable to build a network that has both DetNet
   aware transit nodes and DetNet non-aware transit nodes, and for a
   DetNet flow to traverse an island of non-DetNet transit nodes, while
   still allowing the network to offer latency and congestion loss
   guarantees.  This is possible under certain conditions.

   In general, when passing through a non-DetNet island, the island
   causes delay variation in excess of what would be caused by DetNet
   nodes.  That is, the DetNet flow is "lumpier" after traversing the
   non-DetNet island.  DetNet guarantees for latency and buffer
   requirements can still be calculated and met if and only if the
   following are true:

   1.  The latency variation across the non-DetNet island must be
       bounded and calculable.

   2.  An ingress conditioning function (Section 4.3) may be required at
       the re-entry to the DetNet-aware domain.  This will, at least,
       require some extra buffering to accommodate the additional delay
       variation, and thus further increases the worst-case latency.

   The ingress conditioning is exactly the same problem as that of a
   sender at the edge of the DetNet domain.  The requirement for bounds
   on the latency variation across the non-DetNet island is typically
   the most difficult to achieve.  Without such a bound, it is obvious
   that DetNet cannot deliver its guarantees, so a non-DetNet island
   that cannot offer bounded latency variation cannot be used to carry a
   DetNet flow.

5.  Achieving zero congestion loss

   When the input rate to an output queue exceeds the output rate for a
   sufficient length of time, the queue must overflow.  This is
   congestion loss, and this is what deterministic networking seeks to
   avoid.

5.1.  A General Formula

   To avoid congestion losses, an upper bound on the backlog present in
   the regulator and queuing subsystem of Figure 1 must be computed
   during resource reservation.  This bound depends on the set of flows
   that use these queues, the details of the specific queuing mechanism
   and an upper bound on the processing delay (4).  The queue must
   contain the packet in transmission plus all other packets that are
   waiting to be selected for output.




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   A conservative backlog bound, that applies to all systems, can be
   derived as follows.

   The backlog bound is counted in data units (bytes, or words of
   multiple bytes) that are relevant for buffer allocation.  For every
   class we need one buffer space for the packet in transmission, plus
   space for the packets that are waiting to be selected for output.
   Excluding transmission and preemption times, the packets are waiting
   in the queue since reception of the last bit, for a duration equal to
   the processing delay (4) plus the queuing delays (5,6).

   Let

   o  nb_classes be the number of classes of traffic that may use this
      output port

   o  total_in_rate be the sum of the line rates of all input ports that
      send traffic of any class to this output port.  The value of
      total_in_rate is in data units (e.g. bytes) per second.

   o  nb_input_ports be the number input ports that send traffic of any
      class to this output port

   o  max_packet_length be the maximum packet size for packets of any
      class that may be sent to this output port.  This is counted in
      data units.

   o  max_delay45 be an upper bound, in seconds, on the sum of the
      processing delay (4) and the queuing delays (5,6) for a packet of
      any class at this output port.

   Then a bound on the backlog of traffic of all classes in the queue at
   this output port is

      backlog_bound = ( nb_classes + nb_input_ports ) *
      max_packet_length + total_in_rate* max_delay45

6.  Queuing techniques

6.1.  Queuing data model

   Sophisticated queuing mechanisms are available in Layer 3 (L3, see,
   e.g., [RFC7806] for an overview).  In general, we assume that "Layer
   3" queues, shapers, meters, etc., are precisely the "regulators"
   shown in Figure 1.  The "queuing subsystems" in this figure are not
   the province solely of bridges; they are an essential part of any
   DetNet transit node.  As illustrated by numerous implementation
   examples, some of the "Layer 3" mechanisms described in documents



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   such as [RFC7806] are often integrated, in an implementation, with
   the "Layer 2" mechanisms also implemented in the same node.  An
   integrated model is needed in order to successfully predict the
   interactions among the different queuing mechanisms needed in a
   network carrying both DetNet flows and non-DetNet flows.

   Figure 3 shows the general model for the flow of packets through the
   queues of a DetNet transit node.  Packets are assigned to a class of
   service.  The classes of service are mapped to some number of
   regulator queues.  Only DetNet/TSN packets pass through regulators.
   Queues compete for the selection of packets to be passed to queues in
   the queuing subsystem.  Packets again are selected for output from
   the queuing subsystem.

                                    |
   +--------------------------------V----------------------------------+
   |                    Class of Service Assignment                    |
   +--+------+----------+---------+-----------+-----+-------+-------+--+
      |      |          |         |           |     |       |       |
   +--V-+ +--V-+     +--V--+   +--V--+     +--V--+  |       |       |
   |Flow| |Flow|     |Flow |   |Flow |     |Flow |  |       |       |
   |  0 | |  1 | ... |  i  |   | i+1 | ... |  n  |  |       |       |
   | reg| | reg|     | reg |   | reg |     | reg |  |       |       |
   +--+-+ +--+-+     +--+--+   +--+--+     +--+--+  |       |       |
      |      |          |         |           |     |       |       |
   +--V------V----------V--+   +--V-----------V--+  |       |       |
   |  Trans.  selection    |   | Trans. select.  |  |       |       |
   +----------+------------+   +-----+-----------+  |       |       |
              |                      |              |       |       |
           +--V--+                +--V--+        +--V--+ +--V--+ +--V--+
           | out |                | out |        | out | | out | | out |
           |queue|                |queue|        |queue| |queue| |queue|
           |  1  |                |  2  |        |  3  | |  4  | |  5  |
           +--+--+                +--+--+        +--+--+ +--+--+ +--+--+
              |                      |              |       |       |
   +----------V----------------------V--------------V-------V-------V--+
   |                      Transmission selection                       |
   +----------+----------------------+--------------+-------+-------+--+
              |                      |              |       |       |
              V                      V              V       V       V
        DetNet/TSN queue       DetNet/TSN queue    non-DetNet/TSN queues

              Figure 3: IEEE 802.1Q Queuing Model: Data flow

   Some relevant mechanisms are hidden in this figure, and are performed
   in the queue boxes:

   o  Discarding packets because a queue is full.



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   o  Discarding packets marked "yellow" by a metering function, in
      preference to discarding "green" packets.

   Ideally, neither of these actions are performed on DetNet packets.
   Full queues for DetNet packets should occur only when a flow is
   misbehaving, and the DetNet QoS does not include "yellow" service for
   packets in excess of committed rate.

   The Class of Service Assignment function can be quite complex, even
   in a bridge [IEEE8021Q], since the introduction of per-stream
   filtering and policing ([IEEE8021Q] clause 8.6.5.1).  In addition to
   the Layer 2 priority expressed in the 802.1Q VLAN tag, a DetNet
   transit node can utilize any of the following information to assign a
   packet to a particular class of service (queue):

   o  Input port.

   o  Selector based on a rotating schedule that starts at regular,
      time-synchronized intervals and has nanosecond precision.

   o  MAC addresses, VLAN ID, IP addresses, Layer 4 port numbers, DSCP.
      ([I-D.ietf-detnet-ip], [I-D.ietf-detnet-mpls]) (Work items are
      expected to add MPC and other indicators.)

   o  The Class of Service Assignment function can contain metering and
      policing functions.

   o  MPLS and/or pseudowire ([RFC6658]) labels.

   The "Transmission selection" function decides which queue is to
   transfer its oldest packet to the output port when a transmission
   opportunity arises.

6.2.  Preemption

   In [IEEE8021Q] and [IEEE8023], the transmission of a frame can be
   interrupted by one or more "express" frames, and then the interrupted
   frame can continue transmission.  This frame preemption is modeled as
   consisting of two MAC/PHY stacks, one for packets that can be
   interrupted, and one for packets that can interrupt the interruptible
   packets.  The Class of Service (queue) determines which packets are
   which.  Only one layer of preemption is supported -- a transmitter
   cannot have more than one interrupted frame in progress.  DetNet
   flows typically pass through the interrupting MAC.  Best-effort
   queues pass through the interruptible MAC, and can thus be preempted.






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6.3.  Time-scheduled queuing

   In [IEEE8021Q], the notion of time-scheduling queue gates is
   described in section 8.6.8.4.  Below every output queue (the lower
   row of queues in Figure 3) is a gate that permits or denies the queue
   to present data for transmission selection.  The gates are controlled
   by a rotating schedule that can be locked to a clock that is
   synchronized with other DetNet transit nodes.  The DetNet class of
   service can be supplied by queuing mechanisms based on time, rather
   than the regulator model in Figure 3.  Generally speacking, this
   time-aware scheduling can be used as a layer 2 time division
   multiplexing (TDM) technique.

   Consider the static configuration of a deterministic network.  To
   provide end-to-end latency guaranteed service, network nodes can
   support time-based behavior, which is determined by gate control list
   (GCL).  GCL defines the gate operation, in open or closed state, with
   associated timing for each traffic class queue.  A time slice with
   gate state "open" is called transmission window.  The time-based
   traffic scheduling must be coordinated among the DetNet transit nodes
   along the path from sender to receiver, to control the transmission
   of time-sensitive traffic.

   Ideally all network devices are time synchronized and static GCL
   configurations on all devices along the routed path are coordinated
   to ensure that length of transmission window fits the assigned
   frames, and no two time windows for DetNet traffic on the same port
   overlap.  (DetNet flows' windows can overlap with best-effort
   windows, so that unused DetNet bandwidth is available to best-effort
   traffic.)  The processing delay, link delay and output delay in
   transmitting are considered in GCL computation.  Transmission window
   for a certain flow may require that a time offset on consecutive hops
   be selected to reduce queueing delay as much as possible.  In this
   case, TSN/DetNet frames transmit at the assigned transmission window
   at every node through the routed path, with zero congestion loss and
   bounded end-to-end latency.  Then, the worst-case end-to-end latency
   of the flow can be derived from GCL configuration.  For a TSN or
   DetNet frame, denote the transmission window on last hop closes at
   gate_close_time_last_hop.  Assuming talker supports scheduled traffic
   behavior, it starts the transmission at gate_open_time_on_talker.
   Then worst case end-to-end delay of this flow is bounded by
   gate_close_time_last_hop - gate_open_time_on_talker +
   link_delay_last_hop.

   It should be noted that scheduled traffic service relies on a
   synchronized network and coordinated GCL configuration.  Synthesis of
   GCL on multiple nodes in network is a scheduling problem considering
   all TSN/DetNet flows traversing the network, which is a non-



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   deterministic polynomial-time hard (NP-hard) problem.  Also, at this
   writing, scheduled traffic service supports no more than eight
   traffic classes, typically using up to seven priority classes and at
   least one best effort class.

6.4.  Credit-Based Shaper with Asynchronous Traffic Shaping

   Consider a network with a set of nodes (DetNet transit nodes and
   hosts) along with a set of flows between hosts.  Hosts are sources or
   destinations of flows.  There are four types of flows, namely,
   control-data traffic (CDT), class A, class B, and best effort (BE) in
   decreasing order of priority.  Flows of classes A and B are together
   referred to AVB flows.  It is assumed a subset of TSN functions as
   described next.

   It is also assumed that contention occurs only at the output port of
   a TSN node.  Each node output port performs per-class scheduling with
   eight classes: one for CDT, one for class A traffic, one for class B
   traffic, and five for BE traffic denoted as BE0-BE4 (according to TSN
   standard).  In addition, each node output port also performs per-flow
   regulation for AVB flows using an interleaved regulator (IR), called
   Asynchronous Traffic Shaper (ATS) in TSN.  Thus, at each output port
   of a node, there is one interleaved regulator per-input port and per-
   class.  The detailed picture of scheduling and regulation
   architecture at a node output port is given by Figure 4.  The packets
   received at a node input port for a given class are enqueued in the
   respective interleaved regulator at the output port.  Then, the
   packets from all the flows, including CDT and BE flows, are enqueued
   in a class based FIFO system (CBFS) [TSNwithATS].






















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         +--+   +--+ +--+   +--+
         |  |   |  | |  |   |  |
         |IR|   |IR| |IR|   |IR|
         |  |   |  | |  |   |  |
         +-++XXX++-+ +-++XXX++-+
           |     |     |     |
           |     |     |     |
   +---+ +-v-XXX-v-+ +-v-XXX-v-+ +-----+ +-----+ +-----+ +-----+ +-----+
   |   | |         | |         | |Class| |Class| |Class| |Class| |Class|
   |CDT| | Class A | | Class B | | BE4 | | BE3 | | BE2 | | BE1 | | BE0 |
   |   | |         | |         | |     | |     | |     | |     | |     |
   +-+-+ +----+----+ +----+----+ +--+--+ +--+--+ +--+--+ +--+--+ +--+--+
     |        |           |         |       |       |       |       |
     |      +-v-+       +-v-+       |       |       |       |       |
     |      |CBS|       |CBS|       |       |       |       |       |
     |      +-+-+       +-+-+       |       |       |       |       |
     |        |           |         |       |       |       |       |
   +-v--------v-----------v---------v-------V-------v-------v-------v--+
   |                     Strict Priority selection                     |
   +--------------------------------+----------------------------------+
                                    |
                                    V

     Figure 4: Architecture of a TSN node output port with interleaved
                             regulators (IRs)

   The CBFS includes two Credit-Based Shaper (CBS) subsystems, one for
   each class A and B.  The CBS serves a packet from a class according
   to the available credit for that class.  The credit for each class A
   or B increases based on the idle slope, and decreases based on the
   send slope, both of which are parameters of the CBS.  The CDT and
   BE0-BE4 flows in the CBFS are served by separate FIFO subsystems.
   Then, packets from all flows are served by a transmission selection
   subsystem that serves packets from each class based on its priority.
   All subsystems are non-preemptive.  Guarantees for AVB traffic can be
   provided only if CDT traffic is bounded; it is assumed that the CDT
   traffic has leaky bucket arrival curve with two parameters r_h as
   rate and b_h as bucket size, i.e., the amount of bits entering a node
   within a time interval t is bounded by r_h t + b_h.

   Additionally, it is assumed that the AVB flows are also regulated at
   their source according to leaky bucket arrival curve.  At the source
   hosts, the traffic satisfies its regulation constraint, i.e. the
   delay due to interleaved regulator at hosts is ignored.

   At each DetNet transit node implementing an interleaved regulator,
   packets of multiple flows are processed in one FIFO queue; the packet
   at the head of the queue is regulated based on its leaky bucket



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   parameters; it is released at the earliest time at which this is
   possible without violating the constraint.  The regulation parameters
   for a flow (leaky bucket rate and bucket size) are the same at its
   source and at all DetNet transit nodes along its path.  A delay bound
   of CBFS for an AVB flow f of class A or B can be computed if the
   following condition holds:

      sum of leaky bucket rates of all flows of this class at this node
      <= R, where R is given below for every class.

   If the condition holds, the delay bound is:

      d_f = T + (b_t-L_min_f)/R - L_min_f/c

   where L_min_f is the minimum packet length of flow f; c is the output
   link transmission rate; b_t is the sum of the b term (bucket size)
   for all the flows having the same class as flow f at this node.
   Parameters R and T are calculated as follows for class A and class B,
   separately:

   If f is of class A:

      R = I_A (c-r_h)/ c

      T = L_nA + b_h + r_h L_n/c)/(c-r_h)

   where L_nA is the maximum packet length of class B and BE packets;
   L_n is the maximum packet length of classes A,B, and BE.

   If f is of class B:

      R = I_B (c-r_h)/ c

      T = (L_BE + L_A + L_nA I_A/(c_h-I_A) + b_h + r_h L_n/c)/(c-r_h)

   where L_A is the maximum packet length of class A; L_BE is the
   maximum packet length of class BE.

   Then, an end-to-end delay bound is calculated by the formula
   Section 4.2.2, where for Cij:

      Cij = max(d_f')

   where f' is any flow that shares the same CBFS class with flow f at
   node i and the same interleaved regulator as flow f at node j.

   More information of delay analysis in such a DetNet transit node is
   described in [TSNwithATS].



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6.4.1.  Flow Admission

   The delay calculation requires some information about each node.  For
   each node, it is required to know the idle slope of CBS for each
   class A and B (I_A and I_B), as well as the transmission rate of the
   output link (c).  Besides, it is necessary to have the information on
   each class, i.e. maximum packet length of classes A, B, and BE.
   Moreover, the leaky bucket parameters of CDT (r_h,b_h) should be
   known.  To admit a flow/flows, their delay requirements should be
   guaranteed not to be violated.  As described in Section 3.1, the two
   problems static and dynamic are addressed separately.  In either of
   the problems, the rate and delay should be guaranteed.  Thus,

   The static admission control:
           The leaky bucket parameters of all flows are known,
           therefore, for each flow a delay bound can be calculated.
           The computed delay bound for every flow should not be more
           than its delay requirement.  Moreover, the sum of the rate of
           each flow (r_f) should not be more than the rate allocated to
           each class (R).  If these two conditions hold, the
           configuration is declared admissible.

   The dynamic admission control:
           For dynamic admission control, we allocate to every node and
           class A or B, static value for rate (R) and maximum
           burstiness (b_t).  In addition, for every node and every
           class A and B, two counters are maintained:



              R_acc is equal to the sum of the leaky-bucket rates of all
              flows of this class already admitted at this node; At all
              times, we must have:



                 R_acc <=R, (Eq. 1)

              b_acc is equal to the sum of the bucket sizes of all flows
              of this class already admitted at this node; At all times,
              we must have:



                 b_acc <=b_t.  (Eq. 2)

           A new flow is admitted at this node, if Eqs. (1) and (2)
           continue to be satisfied after adding its leaky bucket rate



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           and bucket size to R_acc and b_acc.  A flow is admitted in
           the network, if it is admitted at all nodes along its path.
           When this happens, all variables R_acc and b_acc along its
           path must be incremented to reflect the addition of the flow.
           Similarly, when a flow leaves the network, all variables
           R_acc and b_acc along its path must be decremented to reflect
           the removal of the flow.

   The choice of the static values of R and b_t at all nodes and classes
   must be done in a prior configuration phase; R controls the bandwidth
   allocated to this class at this node, b_t affects the delay bound and
   the buffer requirement.  R must satisfy the constraints given in
   Annex L.1 of [IEEE8021Q].

6.5.  IntServ

   Integrated service (IntServ) is an architecture that specifies the
   elements to guarantee quality of service (QoS) on networks.  To
   satisfied guaranteed service, a flow must conform to a traffic
   specification (T-spec), and reservation is made along a path, only if
   routers are able to guarantee the required bandwidth and buffer.

   Consider the traffic model which conforms to token bucket regulator
   (r, b), with

   o  Token bucket depth (b).

   o  Token bucket rate (r).

   The traffic specification can be described as an arrival curve:

      alpha(t) = b + rt

   This token bucket regulator requires that, during any time window t,
   the number of bit for the flow is limited by alpha(t) = b + rt.

   If resource reservation on a path is applied, IntServ model of a
   router can be described as a rate-latency service curve beta(t).

      beta(t) = max(0, R(t-T))

   It describes that bits might have to wait up to T before being served
   with a rate greater or equal to R.

   It should be noted that, the guaranteed service rate R is a share of
   link's bandwidth.  The choice of R is related to the specification of
   flows which will transmit on this node.  For example, in strict
   priority policy, considering a flow with priority j, its share of



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   bandwidth may be R=c-sum(r_i), i<j, where c is the link bandwidth,
   r_i is the token bucket rate for the flows with priority higher than
   j.  The choice of T is also related to the specification of all the
   flows traversing this node.  For example, in a generalized processor
   sharing (GPS) node, T = L / R + L_max/c, where L is the maximum
   packet size for the flow, L_max is the maximum packet size in the
   node across all flows.  Other choice of R and T are also supported,
   according to the specific scheduling of the node and flows traversing
   this node.

   As mentioned previously in this section, delay bound and backlog
   bound can be easily obtained by comparing arrival curve and service
   curve.  Backlog bound, or buffer bound, is the maximum vertical
   derivation between curves alpha(t) and beta(t), which is v=b+rT.
   Delay bound is the maximum horizontal derivation between curves
   alpha(t) and beta(t), which is h = T+b/R.  Graphical illustration of
   the IntServ model is shown in Figure 5.

                    + bit              .        *
                    |                 .     *
                    |                .  *
                    |               *
                    |           *  .
                    |       *     .
                    |   *   |    .        ..  Service curve
                    *-----h-|---.         **  Arrival curve
                    |       v  .           h  Delay_bound
                    |       | .            v  Backlog_bound
                    |       |.
                    +-------.--------------------+ time

    Figure 5: Computation of backlog bound and delay bound.  Note that
        arrival and service curves are not necessary to be linear.

   The output bound, or the next-hop arrival curve, is alpha_out(t) = b
   + rT + rt, where burstiness of the flow is increased by rT, compared
   with the arrival curve.

   We can calculate the end-to-end delay bound for a path including N
   nodes, among which the i-th node offers service curve beta_i(t),

      beta_i(t) = max(0, R_i(t-T_i)), i=1,...,N

   By concatenating these IntServ nodes, an end-to-end service curve can
   be computed as

      beta_e2e (t) = max(0, R_e2e(t-T_e2e) )




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   where

      R_e2e = min(R_1,..., R_N)

      T_e2e = T_1 + ... + T_N

   Similarly, delay bound, backlog bound and output bound can be
   computed by using the original arrival curve alpha(t) and
   concatenated service curve beta_e2e(t).

6.6.  Cyclic Queuing and Forwarding

   Annex T of [IEEE8021Q] describes Cyclic Queuing and Forwarding (CQF),
   which provides bounded latency and zero congestion loss using the
   time-scheduled gates of [IEEE8021Q] section 8.6.8.4.  For a given
   DetNet class of service, a set of two or three buffers is provided at
   the output queue layer of Figure 3.  A cycle time Tc is configured
   for each class c, and all of the buffer sets in a class swap buffers
   simultaneously throughout the DetNet domain at that cycle rate, all
   in phase.

   0 time -->  0.7     1   (units of Tc)   2                   3
                           DetNet transit node A out port 1
   |      a      <-DT->|        b          |          c        |       d
   +------------+------+-------------------+-------------------+--------
    \_____              \_____
          \_____              \_____  queue-to-queue delay = 1.3 Tc
                \_____              \_____
                      \_____              \_____  DetNet transit node B
                            \_                  \_ queue assignment, in
          |                   |            |<-DT->|  port 2 to out 3  |
   -------+-------------------+------------+------+-------------------+-
         0.3  time-->        1.3          2.0    2.3                 3.3

         window to transfer
            to buffer c  --->  VVVVVVVVVVVV
          if dead time not                         window to transfer
             excessive         VVVVVVVVVVVVVVVVVVV <--- to buffer d
                           DetNet transit node B out port 3
   |         a         |         b         |         c         |       d
   +-------------------+-------------------+-------------------+--------
   0    time-->        1                   2                   3

                       Figure 6: CQF timing diagram

   Figure 6 shows two DetNet transit nodes A and B, including three
   timelines for:




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   1.  The output queues on port 1 in node A.

   2.  The input gate function ([IEEE8021Q], 8.6.5.1) that assigns
       packets received on port 1 of transit node B to output queues on
       port 2 of transit node B.

   3.  The output queues on port 2 of node B.

   In this figure, the output ports on the two nodes are synchronized,
   and a new buffer starts transmitting at each tick, shown as 0, 1, 2,
   ...  The output times shown for timelines 1 and 3 are the times at
   which packets are selected for output, which is the start point of
   the output time (1) of Figure 1.  The queue assignments times on
   timeline 3 take place at the beginning of the queuing delay (6) of
   Figure 1.  Time-based CQF, as described here, does not require any
   regulator queues.  In the shown in the figure, the total time for
   delays 1 through 6 of Figure 1 is 1.3Tc.  Of course, any value is
   possible.

6.6.1.  CQF timing sequence

   In general, as shown in Figure 6, the windows for buffer assignment
   do not align perfectly with the windows for buffer transmission.  The
   input gates (the center timeline in Figure 6) must switch from using
   one buffer to using another buffer in sync with the (delayed)
   received data, at times offset by the dead time from the output
   buffer switching (the bottom timeline in Figure 6).

   If the dead time DT in Figure 6 is not excessive, then it is feasible
   to subtract the dead time from the cycle time Tc, and use the
   remainder as the input window.  In the example in Figure 6, packets
   from node A buffer a can be transferred from the input port to node
   B's buffer "c" during the window shown by the upper row "VVVV...".
   Input must cease by time = 2.0, because that is when transit node B
   starts transmitting the contents of buffer c.  In this case, only two
   output buffers are in use, one filling and one outputting.

   If the dead time is too large (e.g., if the delays placed the middle
   timeline's switching points at n+0.9, instead of n+0.3), three
   buffers are used by node B.  This case is shown by the lower row
   "VVVV..." in Figure 6.  In this case, node B places the data received
   from node A buffer a into node B buffer d between the times 1.3 and
   2.3 in Figure 6.  Buffer b starts outputting at time = 2.0, while
   buffer d is filling.  Thus, three buffers are in use, one filling,
   one waiting, and one emptying.






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6.6.2.  CQF latency calculation

   The per-hop latency is trivially determined by the wire delay and the
   queuing delay.  Since the wire delay is either absorbed into the
   queueing delay (dead time is small and two buffers are used) or
   padded out to a whole cycle time Tc (three buffers are used) the per-
   hop latency is always an integral number of cycle times Tc, with a
   latency variation at the output of the final hop of Tc.

   Ingress conditioning (Section 4.3) may be required if the source of a
   DetNet flow does not, itself, employ CQF.

   Note that there are no per-flow parameters in the CQF technique.
   Therefore, there is no requirement for per-hop configuration when a
   new DetNet flow is added to a network, except perhaps for ingress
   checks to see that the transmitter does not exceed the contracted
   bandwidth.

7.  References

7.1.  Normative References

   [I-D.ietf-detnet-architecture]
              Finn, N., Thubert, P., Varga, B., and J. Farkas,
              "Deterministic Networking Architecture", draft-ietf-
              detnet-architecture-08 (work in progress), September 2018.

   [I-D.ietf-detnet-ip]
              Varga, B., Farkas, J., Berger, L., Fedyk, D., Malis, A.,
              Bryant, S., and J. Korhonen, "DetNet Data Plane: IP",
              draft-ietf-detnet-ip-00 (work in progress), May 2019.

   [I-D.ietf-detnet-mpls]
              Varga, B., Farkas, J., Berger, L., Fedyk, D., Malis, A.,
              Bryant, S., and J. Korhonen, "DetNet Data Plane: MPLS",
              draft-ietf-detnet-mpls-00 (work in progress), May 2019.

   [RFC2212]  Shenker, S., Partridge, C., and R. Guerin, "Specification
              of Guaranteed Quality of Service", RFC 2212,
              DOI 10.17487/RFC2212, September 1997,
              <https://www.rfc-editor.org/info/rfc2212>.

   [RFC6658]  Bryant, S., Ed., Martini, L., Swallow, G., and A. Malis,
              "Packet Pseudowire Encapsulation over an MPLS PSN",
              RFC 6658, DOI 10.17487/RFC6658, July 2012,
              <https://www.rfc-editor.org/info/rfc6658>.





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   [RFC7806]  Baker, F. and R. Pan, "On Queuing, Marking, and Dropping",
              RFC 7806, DOI 10.17487/RFC7806, April 2016,
              <https://www.rfc-editor.org/info/rfc7806>.

   [RFC8578]  Grossman, E., Ed., "Deterministic Networking Use Cases",
              RFC 8578, DOI 10.17487/RFC8578, May 2019,
              <https://www.rfc-editor.org/info/rfc8578>.

7.2.  Informative References

   [bennett2002delay]
              J.C.R. Bennett, K. Benson, A. Charny, W.F. Courtney, and
              J.-Y. Le Boudec, "Delay Jitter Bounds and Packet Scale
              Rate Guarantee for Expedited Forwarding",
              <https://dl.acm.org/citation.cfm?id=581870>.

   [charny2000delay]
              A. Charny and J.-Y. Le Boudec, "Delay Bounds in a Network
              with Aggregate Scheduling", <https://link.springer.com/
              chapter/10.1007/3-540-39939-9_1>.

   [IEEE8021Q]
              IEEE 802.1, "IEEE Std 802.1Q-2018: IEEE Standard for Local
              and metropolitan area networks - Bridges and Bridged
              Networks", 2018,
              <http://ieeexplore.ieee.org/document/8403927>.

   [IEEE8021Qcr]
              IEEE 802.1, "IEEE P802.1Qcr: IEEE Draft Standard for Local
              and metropolitan area networks - Bridges and Bridged
              Networks - Amendment: Asynchronous Traffic Shaping", 2017,
              <http://www.ieee802.org/1/files/private/cr-drafts/>.

   [IEEE8021TSN]
              IEEE 802.1, "IEEE 802.1 Time-Sensitive Networking (TSN)
              Task Group", <http://www.ieee802.org/1/>.

   [IEEE8023]
              IEEE 802.3, "IEEE Std 802.3-2018: IEEE Standard for
              Ethernet", 2018,
              <http://ieeexplore.ieee.org/document/8457469>.

   [le_boudec_theory_2018]
              J.-Y. Le Boudec, "A Theory of Traffic Regulators for
              Deterministic Networks with Application to Interleaved
              Regulators", <http://arxiv.org/abs/1801.08477/>.





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   [NetCalBook]
              Le Boudec, Jean-Yves, and Patrick Thiran, "Network
              calculus: a theory of deterministic queuing systems for
              the internet", 2001, <https://arxiv.org/abs/1804.10608/>.

   [Specht2016UBS]
              J. Specht and S. Samii, "Urgency-Based Scheduler for Time-
              Sensitive Switched Ethernet Networks",
              <https://ieeexplore.ieee.org/abstract/document/7557870>.

   [TSNwithATS]
              E. Mohammadpour, E. Stai, M. Mohiuddin, and J.-Y. Le
              Boudec, "End-to-end Latency and Backlog Bounds in Time-
              Sensitive Networking with Credit Based Shapers and
              Asynchronous Traffic Shaping",
              <https://arxiv.org/abs/1804.10608/>.

Authors' Addresses

   Norman Finn
   Huawei Technologies Co. Ltd
   3101 Rio Way
   Spring Valley, California  91977
   US

   Phone: +1 925 980 6430
   Email: nfinn@nfinnconsulting.com


   Jean-Yves Le Boudec
   EPFL
   IC Station 14
   Lausanne EPFL  1015
   Switzerland

   Email: jean-yves.leboudec@epfl.ch


   Ehsan Mohammadpour
   EPFL
   IC Station 14
   Lausanne EPFL  1015
   Switzerland

   Email: ehsan.mohammadpour@epfl.ch






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   Jiayi Zhang
   Huawei Technologies Co. Ltd
   Q22, No.156 Beiqing Road
   Beijing  100095
   China

   Email: zhangjiayi11@huawei.com


   Balazs Varga
   Ericsson
   Konyves Kalman krt. 11/B
   Budapest  1097
   Hungary

   Email: balazs.a.varga@ericsson.com


   Janos Farkas
   Ericsson
   Konyves Kalman krt. 11/B
   Budapest  1097
   Hungary

   Email: janos.farkas@ericsson.com


























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