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Asynchronous Deterministic Networking Framework for Large-Scale Networks

Document Type Active Internet-Draft (individual)
Authors Jinoo Joung , Jeong-dong Ryoo , Tae-sik Cheung , Yizhou Li , Peng Liu
Last updated 2022-10-24
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DetNet Working Group                                            J. Joung
Internet-Draft                                      Sangmyung University
Intended status: Informational                                   J. Ryoo
Expires: 27 April 2023                                         T. Cheung
                                                                   Y. Li
                                                                  P. Liu
                                                            China Mobile
                                                         24 October 2022

Asynchronous Deterministic Networking Framework for Large-Scale Networks


   This document describes an overall framework of Asynchronous
   Deterministic Networking (ADN) for large-scale networks.  It
   specifies the functional architecture and requirements for providing
   latency and jitter bounds to high priority traffic, without strict
   time-synchronization of network nodes.

Status of This Memo

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

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

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

   This Internet-Draft will expire on 27 April 2023.

Copyright Notice

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

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents (
   license-info) in effect on the date of publication of this document.

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   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 Revised BSD License text as
   described in Section 4.e of the Trust Legal Provisions and are
   provided without warranty as described in the Revised BSD License.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
   2.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   4
     2.1.  Terms Used in This Document . . . . . . . . . . . . . . .   4
     2.2.  Abbreviations . . . . . . . . . . . . . . . . . . . . . .   4
   3.  Conventions Used in This Document . . . . . . . . . . . . . .   4
   4.  Framework for Latency Guarantee . . . . . . . . . . . . . . .   5
     4.1.  Problem Statement . . . . . . . . . . . . . . . . . . . .   5
     4.2.  Asynchronous Traffic Shaping (ATS)  . . . . . . . . . . .   7
     4.3.  Flow Aggregate Interleaved Regulators (FAIR)  . . . . . .   7
       4.3.1.  Overview of the FAIR  . . . . . . . . . . . . . . . .   7
       4.3.2.  The performance of the FAIR . . . . . . . . . . . . .   8
     4.4.  Port-based Flow Aggregate Regulators (PFAR) . . . . . . .   8
     4.5.  Work-conserving stateless core fair queuing (C-SCORE) . .  10
   5.  Framework for Jitter Guarantee  . . . . . . . . . . . . . . .  12
     5.1.  Problem statement . . . . . . . . . . . . . . . . . . . .  12
     5.2.  Buffered network (BN) . . . . . . . . . . . . . . . . . .  13
     5.3.  Properties of the BN  . . . . . . . . . . . . . . . . . .  15
     5.4.  Frequency synchronization between the source and the
           buffer  . . . . . . . . . . . . . . . . . . . . . . . . .  16
     5.5.  Omission of the timestamper . . . . . . . . . . . . . . .  16
     5.6.  Mitigation of the increased E2E buffered latency  . . . .  16
     5.7.  Multi-sources single-destination flows' jitter control  .  17
   6.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  17
   7.  Security Considerations . . . . . . . . . . . . . . . . . . .  17
   8.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  18
   9.  Contributor . . . . . . . . . . . . . . . . . . . . . . . . .  18
   10. References  . . . . . . . . . . . . . . . . . . . . . . . . .  18
     10.1.  Normative References . . . . . . . . . . . . . . . . . .  18
     10.2.  Informative References . . . . . . . . . . . . . . . . .  18
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  21

1.  Introduction

   Deterministic Networking (DetNet) 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 architecture of DetNet is defined in RFC 8655
   [RFC8655], and the overall framework for DetNet data plane is
   provided in RFC 8938 [RFC8938].  Various documents on DetNet IP
   (Internet Protocol) and MPLS (Multi-Protocol Label Switching) data

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   planes and their interworking with Time-Sensitive Networking (TSN)
   have been standardized.  Technical elements necessary to extend
   DetNet to a large-scale network spanning multiple administrative
   domains are identified in [I-D.liu-detnet-large-scale-requirements].

   This document considers the problem of guaranteeing both latency
   upper bounds and jitter upper bounds in large-scale networks with any
   type of topology, with random dynamic input traffic.  The jitter is
   defined as the latency difference between two packets within a flow,
   not a difference from a clock signal or from an average latency, as
   is summarized in RFC 3393 [RFC3393].

   In large-scale networks, the end-nodes join and leave, and a large
   number of flows are dynamically generated and terminated.  Achieving
   satisfactory deterministic performance in such environments would be
   challenging.  The current Internet, which has adopted the DiffServ
   architecture, has the problem of the burst accumulation and the
   cyclic dependency, which is mainly due to FIFO queuing and strict
   priority scheduling.  Cyclic dependency is defined as a situation
   wherein the graph of interference between flow paths has cycles
   [THOMAS].  The existence of such cyclic dependencies makes the proof
   of determinism a much more challenging issue and can lead to system
   instability, that is, unbounded delays [ANDREWS][BOUILLARD].  The
   Internet architecture does not have an explicit solution for the
   jitter bound as well.  Solving the problem of latency and jitter as a
   joint optimization problem would be even more difficult.

   The basic philosophy behind the framework proposed in this document
   is to minimize the latency bounds first by taking advantage of the
   work conserving schedulers with regulators or stateless fair queuing
   schedulers, and then minimize the jitter bounds by adjusting the
   packet inter-departure times to reproduce the inter-arrival times, at
   the boundary of a network.  We argue that this is simpler than trying
   to minimize the latency and the jitter at the same time.  The direct
   benefit of such simplicity is its scalability.

   For the first problem of guaranteeing latency bound alone, the IEEE
   asynchronous traffic shaping (ATS) [IEEE802.1Qcr], the flow-aggregate
   interleaved regulators (FAIR) [FAIR][Y.3113] frameworks, the port-
   based flow aggregate regulators (PFAR) [ADN], and the work-conserving
   stateless core fair queuing (C-SCORE) are proposed as solutions.  The
   key component of the ATS and the FAIR frameworks is the interleaved
   regulator (IR)), which is described in
   [I-D.ietf-detnet-bounded-latency].  The IR has a single queue for all
   flows of the same class from the same input port.  The head of the
   queue (HOQ) is examined if the packet is eligible to exit the
   regulator.  To decide whether it is eligible, the IR must maintain
   the individual flow states.  The key component of the PFAR framework

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   is the regulators for flow aggregates (FA) per port per class, which
   regulates the FA based on the sum of average rates and the sum of
   maximum bursts of the flows that belong to the FA.  In the meantime,
   the key component of the C-SCORE is the packet state that is carried
   as meta-data.  The C-SCORE does not need to maintain flow states at
   core nodes, yet it is one of the fair queuing schedulers.  The
   service order of the packet is directly inferred from the packet
   state.  It can be implemented based on per-input port FIFO queues.
   The meta-data to be carried in the packet header is simple and can be
   updated during the stay in the queue or before joining the queue.

   For the second problem of guaranteeing jitter bound, it is necessary
   to assume that the first problem is solved, that is, the network
   guarantees latency bounds.  Furthermore, the network is required to
   specify the value of the latency bound for a flow.  The end systems
   at the network boundary, or at the source and destination nodes, then
   can adjust the inter-departure times of packets, such that they are
   similar to their inter-arrival times.  In order to identify the
   inter-arrival times at the destination node, or at the network edge
   near the destination, the packets are required to specify their
   arrival times, according to the clock at the source, or the network
   edge near the source.  The clocks are not required to be time-
   synchronized with any other clocks in a network.  In order to avoid a
   possible error due to a clock drift between a source and a
   destination, they are recommended to be frequency-synchronized.

   In this document, strict time-synchronization among network nodes is
   avoided.  It is not easily achievable, especially over a large area
   network or across multiple DetNet domains.  Asynchronous solutions
   suggested in this document can provide satisfactory latency bounds
   with careful design without complex pre-computation, configuration,
   and hardware support usually necessary for time synchronization.

2.  Terminology

2.1.  Terms Used in This Document

2.2.  Abbreviations

3.  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.

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4.  Framework for Latency Guarantee

4.1.  Problem Statement

   In Section 4, we assume there are only two classes of traffic.  The
   high priority traffic requires latency upper bound guarantee.  All
   the other traffic is considered to be the low priority traffic, and
   be completely preempted by the high priority traffic.  High priority
   (HP) traffic is our only focus.

   It is well understood that the necessary conditions for a flow to
   have a bounded latency inside a network, are that;

   *  a flow entering a network conforms to a prescribed traffic
      specification (TSpec), including the arrival rate and the maximum
      burst size, and

   *  all the network nodes serve the flow with a service rate which are
      greater than or equal to the arrival rate.

   These conditions make the resource reservation and the admission
   control mandatory.  These two functions are considered given and out
   of scope of this document.

   Here, the notion of arrival and service rates represent sustainable
   or average values.  A short-term discrepancy between these two rates
   contributes to the burst size increment, which can be accumulated as
   the flow passes through the downstream nodes.  This results in an
   increase in the latency bound.  Therefore, the value of accumulated
   burst size is a critical performance metric.

   The queuing and scheduling of a flow plays a key role in deciding the
   accumulated burst size.  Ideally, the flows can be queued in separate
   queues and the queues are scheduled according to the flow rates.  In
   this case a flow can be considered protected.  With practical fair
   schedulers, such as the Deficit Round Robin (DRR), a protected flow
   still can be affected by the other flows as much as their maximum
   packet lengths.

   If we adopt a separate queue per flow at an output port, and assume
   identical flows from all the input ports, then the maximum burst size
   of a flow out of the port, Bout, is given as the following:

                         Bout < Bin + (n-1)L*r/C,

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   where Bout is the outgoing flow's maximum burst size, Bin is the
   incoming flow's maximum burst size, n is the number of the flows, L
   is the maximum packet size, r is the average rate of the flow, and C
   is the link capacity.  This approach was taken in the integrated
   services (IntServ) framework [RFC2212].

   The separate queues in the aforementioned case can be too many to be
   handled in real time, especially at the core of large-scale networks.
   The common practice therefore is to put all the HP flows in a single
   queue, and serve them with higher priority than best effort traffic.
   It is also well known that a proper scheduling scheme, such as the
   strict priority (SP) scheduling can guarantee service rates larger
   than the arrival rates, therefore the latency can still be
   guaranteed.  With such a single aggregate queue the flows are not
   considered protected, however.  In this case a flow's burst size in a
   node can be increased proportionally to the sum of maximum burst
   sizes of the other flows in the queue.  That is,

                        Bout < Bin + (n-1)Bin*r/C.

   The second product term on the right-hand side represents the amount
   of increased maximum burst.  It is dominated by the term (n-1)Bin,
   which is the maximum total burst from the other flows.

   Moreover, this increased burst affects the other flows' burst size at
   the next node, and this feedforward can continue indefinitely where a
   cycle is formed in a network.  This phenomenon is called a cyclic
   dependency of a network.  It is argued that the burst accumulation
   can explode into infinity, therefore the latency is no longer

   As such, a flow is required to be protected to a certain level, from
   the other flows' bursts, such that its burst accumulations are kept
   within a necessary value.  By doing so, the other flows are also
   protected.  The regulators or the fair queuing schedulers are
   proposed as solutions for such protection in this document.  They can
   decrease the accumulated burst into a desirable level and can protect
   flows from others.  In case of the regulators, however, if the
   regulation needs a separate queue per flow, then the scalability
   would be harmed just like the ideal IntServ case.  In this document
   the IR or the regulations on flow aggregates are proposed.

   The key requirement for latency guarantee is therefore to have
   scalability and a certain level of flow protection.

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4.2.  Asynchronous Traffic Shaping (ATS)

   The first solution in this document for latency guarantee is the IEEE
   TSN TG's ATS technology.  Essentially it is a combined effort of the
   flow aggregation per node per input/output ports pair per class, and
   the interleaved regulator per flow aggregate (FA).  The IR examines
   the HOQ, identifies the flow the packet belongs to, and transfers the
   packet only when it is eligible according to the initial TSpec of the
   flow.  This solution can have only one queue per FA, but suffers from
   having to maintain each individual flow state.  The detailed
   description on ATS can be found in [IEEE802.1Qcr].

4.3.  Flow Aggregate Interleaved Regulators (FAIR)

4.3.1.  Overview of the FAIR

   In the FAIR framework, the network can be divided into several
   aggregation domains (ADs).  HP flows of the same path within an AD
   are aggregated into an FA.  IRs per FA are implemented at the
   boundaries of the ADs.  An AD can consist of arbitrary number of
   nodes.  The FA can be further subdivided based on the flow
   requirements and characteristics.  For example, only video flows of
   the same path are aggregated into a single FA.

   Figure 1 shows an example architecture of the FAIR framework.  The
   IRs at the AD boundaries suppress the burst accumulations across the
   ADs with the latency upper bounds intact as they do in IEEE TSN ATS,
   if the incoming flows are all properly regulated, and the AD
   guarantees the FIFO property to all the packets in the FA [LEBOUDEC].
   It is sufficient to put every FA into a single FIFO queue in a node,
   in order to maintain the FIFO property within an AD.  However, in
   this case, if cycles are formed, the burst accumulations inside an AD
   can be accumulated indefinitely.  If the topology does not include a
   cycle and the latency bound requirement is not stringent, then the
   FIFO queue and the SP scheduler would be allowable.  Otherwise, the
   FAs are recommended to be treated with separated queues and fair-
   queuing schedulers for flow protection.

              .~~.    +---+    .~~,        +---+        .~~.
     +---+   [    ]   |IR |   [    ]       |IR |       [    ]   +----+
     |Src|->[  AD  ]->|per|->[  AD  ]-> ...|per|... ->[  AD  ]->|Dest|
     +---+   [    ]   |FA |   [    ]       |FA |       [    ]   +----+
              '~~'    +---+    '~~'        +---+        '~~'

                          Figure 1: FAIR Framework

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4.3.2.  The performance of the FAIR

   The FAIR guarantees an end-to-end delay bound with reduced complexity
   compared to the traditional flow-based approach.  Numerical analysis
   shows that, with a careful selection of AD size, the FAIR with DRR
   schedulers yields smaller latency bounds than both the IntServ and
   the ATS [FAIR].

   The ATS can be considered as a special case of the FAIR with the FIFO
   schedulers, where all the ADs encompass only a single hop.  The
   IntServ can also be considered as an extreme case of the FAIR with
   fair schedulers and queues per FA, with an AD corresponding to an
   entire network; therefore, regulators are unnecessary.

4.4.  Port-based Flow Aggregate Regulators (PFAR)

   The IR in the ATS and the FAIR suffers from two major complex tasks;
   the flow state maintenance and the HOQ lookup to determine the flow
   to which the packet belongs.  Both tasks involve real-time packet
   processing and queue management.  As the number of flows increases,
   the IR operation may become burdensome as much as the per- flow
   regulators.  Without maintaining individual flow states, however, the
   flows can be protected to a certain level, as is described in this

   The ATS and FAIR mitigates the burst increment by placing IRs behind
   a FIFO system.  For example, consider an ATS node with a single queue
   at an output port for HP traffic.  The IR assigned for an input port
   forms a single queue for the flows from the same input port.  Further
   consider the set of incoming flows from the same input port of the
   ATS node.  Let us call this set of flows the incoming flow aggregate
   (FAin).  If we assume identical FAins from all the input ports, then
   the maximum burst size of an arbitrary set of flows out of the port,
   Bout, is given as the following:

                         Bout < Bin + (p-1)B*r/C,

   where Bin is the sum of maximum burst sizes of the flows within the
   FAin, B is the sum of initial maximum burst sizes of the flows within
   the FAin, and p is the number of the ports in the node.

   The port-based FA (PFA) is defined as a set of HP flows in the same
   class, which share the input and output ports in a relay node, such
   as a switch or router.  The only aggregation criteria for a PFA are
   the ports and the class.  The port-based flow aggregate regulators
   (PFAR) framework puts a regulator for each PFA in an output port
   module, just before the class-based queuing/scheduling system of the
   output port module.  The PFAR framework sees a PFA as a single flow

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   with the "PFA-Tspec", {the sum of the maximum initial bursts; and the
   sum of the initial arrival rates} of the flows that are the elements
   of the PFA; and regulates the PFA to meet its PFA-Tspec.

   The PFARs can be placed at the output port of a node before the
   output SP scheduler.  The architecture is similar to that suggested
   in the IEEE ATS, except that in the ATS, the IRs are placed instead
   of the PFARs.

   The burst increment of an FA in the PFAR architecture is identical to
   that in the ATS, which is given as;

                           Bout < Bin + (p-1)B*r/C,

   where B is again the initial maximum burst size of FAs.  However, the
   regulators in PFAR does introduce additional latency, which is given

                               D < (Bin - B)/r,

   where D is the latency within the regulator.

   Note that Bout is a function of (n-1)B, not (n-1)Bin; in other words,
   the burst size out of a node is affected only by the initial burst
   sizes of the other FAs from different input ports of the node.  This
   property makes the D or Bout do not increase exponentially even in
   the existence of cyclic dependencies.

   With the PFAR, the HOQ flow identification process is unnecessary,
   and only the PFAs' states, instead of individual flows' states, must
   be maintained at a node.  In this respect, the complexity of process
   of PFAR is reduced compared to IR of the ATS or the FAIR.

   In a recent study [ADN], it was also shown, through a numerical
   analysis with symmetrical networks with cycles, that PFAR, when
   implemented at every node, can achieve comparable latency bounds to
   the IEEE ATS technique.

   The ATS, the FAIR, and the PFAR frameworks maintain regulators per
   FA.  The FAs in these frameworks are composed of the flows sharing
   the same ingress/egress ports of an AD.  The ADs can encompass a
   single hop or multiple hops.  The regulators can be the IR or the
   aggregate regulator.  There can be other combinations of AD and
   regulator type, which could be further investigated and compared to
   the frameworks introduced in this document.

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4.5.  Work-conserving stateless core fair queuing (C-SCORE)

   The generalized processor sharing (GPS) [PAREKH], the weighted fair
   queuing (WFQ), the virtual clock (VC), and similar other schedulers
   utilize the concept of finish time (FT) that is the service order
   assigned to a packet.  The packet with the minimum FT in a buffer is
   served first.  We will call these works collectively as the fair
   queuing (FQ).

   As an example, the VC scheduler [ZHANG] defines the FT to be

              F(p) = max{F(p-1), A(p)} + L(p)/r,          (1)

   where (p-1) and p are consecutive packets of the flow under
   observation, A(p)is the arrival time of p, L(p) is the length of p,
   and r is the flow service rate.  The flow index is omitted.

   The key idea of the FQ is to calculate the service finish times of
   packets in an imaginary ideal fluid service model and use them as the
   service order in the real packet-based scheduler.

   While having the excellent flow protection property, the FQ needs to
   maintain the flow state, F(p-1).  For every arriving packet, the flow
   it belongs to has to be identified and its previous packet's FT
   should be extracted.  As the packet departs, the flow state, F(p),
   has to be updated as well.

   We consider a framework for constructing FTs for packets at core
   nodes without flow states.  In a core node, the following conditions
   on FTs have to be met.

   C1)  It has to keep the 'fair distance' of consecutive packets of a
        flow.  That is; Fh(p) >= Fh(p-1) + L(p)/r, where Fh(p) is the
        F(p) at node h.

   C2)  The order of FTs and the actual service order, within a flow,
        have to be kept.  That is; Fh(p) > Fh(p-1) and Ch(p) > Ch(p-1),
        where Ch(p) is the actual service completion time of packet p at
        node h.

   C3)  The time lapse at each hop has to be reflected.  That is; Fh(p)
        >= F(h-1)(p), where F(h-1)(p) is the FT of p at the node h-1,
        the upstream node of h.

   C4)  The FTs of a flow have to be aligned to the packet arrival
        times.  That is; L(p)/r <= Fh(p)- Ah(p) < Delta.

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   Delta can be any finite positive value [STILIADIS].  In other words,
   the Fh(p) should be larger than Ah(p)+L(p)/r, as in (1), yet still
   should grow at the same rate as Ah(p).

   In essence, (1) has to be approximated in core nodes.  There can be
   many possible solutions to meet these conditions.  We propose a
   generic framework for constructing FTs in core nodes, without flow
   state, in the following.

   We denote a 'node' to be an output port of a relay node.

   Requirement 1: In the entrance node, it is required to obtain the FTs
   with (1).  That is to obtain F0(p) as in the VC, where 0 denotes the
   entrance node of the flow under observation.

                    F0(p) = max{F0(p-1), A0(p)}+L(p)/r.

   Note that F0(p) keeps the fair distances from the FTs of consecutive
   packets of the flow.

   Requirement 2: It is required to increase the FT of a packet by an
   amount that depends on the node and the packet, dh(p), in a core node

                      Fh(p) = F(h-1)(p) + d(h-1)(p).

   Requirement 3: It is required that dh(p) is a non-decreasing function
   of p, within a node busy period.

   Definition 1: A node busy period is a maximal interval between
   consecutive node idle periods.  During a node idle period, the node
   has no packet to send.

   By Requirements 1, 2, and 3; Conditions 1), 2), and 3) are met.

   Requirement 4: It is required that Ah(p)+dh(p) >= A(h+1)(p).

   One example of dh(p) is a measured maximum latency of a packet in the
   node h up until the current packet p, since the start of a node busy
   period.  Let us denote this local maximum latency with uh(p).  It may
   be reset to an initial value during a node idle period.  An example
   of the initial value of uh(p) is the propagation delay from node h to
   (h+1).  By letting dh(p)=uh(p), Requirement 4 is satisfied.

   dh(p) may not be a function of p, and dependent only on the node.
   Then it could be denoted as dh.

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   One example of dh is letting dh = Uh, where Uh is the latency upper
   bound in node h for any p.  Uh can be a theoretical one, or be
   obtained by long-term measurements.  By letting dh(p)=Uh, Requirement
   4 is satisfied.

   If Requirement 4 is satisfied then it can be guaranteed Fh(p) >=
   Ah(p)+L(p)/r, for all h>=0, and it can be proven that Condition 4) is

   In a core node, the service order of packets from the same input port
   can be preserved.  That is, if Ah(p)> Ah(p') then Ch(p)>Ch(p') for
   packets p and p' that travel together the nodes (h-1) and h.  By
   preserving the service order of packets from the same input port,
   using per-input port FIFO queues is possible.  An example
   implementation would be as the follows: The output port module is
   composed of per-input port FIFO queues.  As a packet enters the FIFO
   queue according to its input port, it should join the queue at the
   tail and be marked with its FT.  The scheduler will examine the
   smallest FT among the packets at the HoQ of the FIFO queues.

   Note that Ah(p)> Ah(p') does not guarantee Fh(p)>Fh(p') when p and p'
   belong to different flows.  For example, p' may have a smaller FT but
   arrive later while p is in service.  However, it is proven that this
   service completion time discrepancy, C0(p)-F0(p), between real packet
   system and ideal fluid system is bounded by Lmax/C [PAREKH], where
   Lmax is the maximum packet length over all the flows, and C is the
   link capacity.

   The meta-data to carry in a packet are Fh(p) and dh(p).  These are
   dynamic and thus need to be updated at every hop.  Note that if dh(p)
   = dh then it can also be signaled out-of-band between the neighboring
   nodes.  Fh(p) can be obtained by a simple summation of two meta-data,
   and updated during the time interval between the packet arrival and
   its reaching HoQ of the FIFO queue.

   The proposed FT construction framework has advantages of simple FIFO-
   based implementation and simple meta-data management.  We call this
   solution the work conserving stateless core fair queuing (C-SCORE),
   which can be compared to the existing non-work conserving scheme

5.  Framework for Jitter Guarantee

5.1.  Problem statement

   The problem of guaranteeing jitter bounds in arbitrarily sized
   networks with any type of topology with random dynamic input traffic
   is considered.

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   There are several possible solutions to guarantee jitter bounds in
   packet networks, such as IEEE TSN's cyclic queuing and forwarding
   (CQF) [IEEE802.1Qch], its asynchronous variations
   [I-D.yizhou-detnet-ipv6-options-for-cqf-variant], and the latency-
   based forwarding (LBF) [LBF].

   The CQF requires time-synchronization across every node in the
   network including the source.  It is not scalable to a large network
   with significant propagation delays between the nodes.  The
   asynchronous CQFs are scalable, but they may not satisfy
   applications' jitter requirements.  This is because their jitter
   bounds cannot be controlled as desired, but are only determined by
   the cycle time, which should be large enough to accommodate all the
   traffic to be forwarded.

   The systems with slotted operations such as the CQF and its
   variations turn the problem of packet scheduling into the problem of
   scheduling flows to fit into slots.  The difficulty of such a slot
   scheduling is a significant drawback in large scale dynamic networks
   with irregular traffic generations and various propagation delays.

   The LBF is a framework of the forwarding action decision based on the
   flow and packet status, such as the delay budget left for a packet in
   a node.  The LBF does not specify the actions to take according to
   the status.  It suggests a packet slow down or speedup by changing
   the service order, by pushing packets into any desirable position of
   a first out queue, as a possible action to take.  In essence, by
   having latency budget information of every packet, the LBF is
   expected to maintain the latency and jitter within desired bounds.
   The processing latency required in LBF includes times 1) to lookup
   the latency budget information on every packet header, 2) to decide
   the queue position of the packet, 3) to modify the queue linked list,
   and 4) to update the budget information on the packet upon
   transmission.  This processing latency, however, can affect the
   scalability especially in high speed core networks.

   The ATS, the FAIR, and the PFAR utilize the regulation function to
   proactively prevent the possible burst accumulation in the downstream
   nodes.  It is not clear whether the LBF can take such preventive
   action.  If so the LBF can also act as a regulator and yield a
   similar latency bound.

5.2.  Buffered network (BN)

   The BN framework in this document for jitter bound guarantee is
   composed of

   *  a network that guarantees latency upper bounds;

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   *  a timestamper for packets with a clock that is not necessarily
      synchronized with the other nodes, which resides in between,
      including the source and the network ingress interface; and

   *  a buffer that can hold the packets for a predetermined interval,
      which resides in between, including the destination and the
      network egress interface.

   Figure 2 depicts the overall architecture of the BN framework for
   jitter-bound guarantees [BN].  Only a single flow is depicted between
   the source and destination in Figure 2.  The arrival (an), departure
   (bn), and buffer-out (cn) times of the nth packet of a flow are
   denoted.  The end-to-end (E2E) latency and the E2E buffered latency
   are defined as (bn-an) and (cn-an), respectively.

   +-----+an +-------------+   | Network with |bn +--------+cn +-------+
   | Src |-->| Timestamper |-->|   latency    |-->| Buffer |-->| Dest. |
   +-----+   +-------------+   |  guarantee   |   +--------+   +-------+
           |<--------------- E2E latency ------>|
           |<--------------- E2E buffered latency ---------->|

       Figure 2: Buffered Network (BN) Framework for Jitter Guarantee

   The buffer supports as many as the number of the flows destined for
   the destination.  The destination shown in Figure 2 can be an end
   station or another deterministic network.  The buffer holds packets
   in a flow according to predefined intervals.  The decision of the
   buffering intervals involves the time-stamp value within each packet.

   The network in between the time-stamper and the buffer can be of
   arbitrarily sized network.  The input traffic can be dynamic.  It is
   required that the network be able to guarantee and identify the E2E
   latency upper bounds of the flows.  The network is also required to
   let the buffer be aware of the E2E latency upper bounds of the flows
   it has to process.  It is recommended that the E2E latency lower
   bound information is provided by the network as well.  The lower
   bound may be contributed from the transmission and propagation delays
   within the network.

   The time-stamper marks on the packets their arrival times.  The time-
   stamping function can use the real-time transport protocol (RTP) over
   the user datagram protocol (UDP) or the transmission control protocol
   (TCP).  Either the source or network ingress interface can stamp the
   packet.  In the case where the source stamps, the timestamp value is
   the packet departure time from the source, which is only a
   propagation time away from the packet arrival time to the network.

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   The source and destination do not need to share a synchronized clock.
   All we need to know is the differences between the time stamps, that
   is, the information about the inter-arrival times.

5.3.  Properties of the BN

   Let the arrival time of the nth packet of a flow be an.  Similarly,
   let bn be the departure time from the network of the nth packet.
   Then, a1 and b1 are the arrival and departure times of the first
   packet of the flow, respectively.  The first packet of a flow is
   defined as the first packet generated by the source, among all the
   packets that belong to the flow.  Further, let cn be the buffer-out
   time of the nth packet of the flow.  Let us define m as the jitter
   control parameter, which will be described later in detail.

   Since buffers can be without cut-through capability, the processing
   delay within a buffer has to be taken in account.  Let gn be the
   processing delay within the buffer of the nth packet of the flow.
   The gn includes the time to look up the timestamp and to store/
   forward the packet.  However, it does not include an intentional
   buffer-holding interval.  By definition, cn - bn >= gn.  Let
   max_n(gn)=g, the maximum processing delay for the flow in the buffer.
   It is assumed that a buffer can identify the value of g.  Let U and W
   be the latency upper and lower bounds guaranteed to the flow by the
   network.  Let m be the jitter control parameter, W+g <= m.

   The rules for the buffer-holding interval decision are given as

   *  c1=(b1+m-W),

   *  cn=max{(bn+g), (c1+an-a1)}, for n > 1.

   The second rule governing the cn states that a packet should be held
   in the buffer to make its inter-buffer-out time, (cn-c1), equal to
   the inter-arrival time, (an-a1).  However, when its departure from
   the network is too late, the inter-buffer-out time should be larger
   than the inter-arrival time, then hold the packet as much as the
   maximum processing delay in the buffer, that is, cn=bn+g.  The buffer
   does not need to know the exact values of an or a1.  It is sufficient
   to determine the difference between these values, which can be easily
   obtained by subtracting the timestamp values of the two packets.

   The following theorems holds [ADN].

   Theorem 1 (Upper bound of E2E buffered latency).  The latency from
   the packet arrival to the buffer-out times (cn-an), is upper bounded
   by (U-W+m).

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   Theorem 2 (Lower bound of E2E buffered latency).  The latency from
   the packet arrival to the buffer-out times (cn-an), is lower bounded
   by m.

   Theorem 3 (Upper bound of jitter).  The jitter is upper bounded by
   max{0, (U+g-m)}.

   By setting m=(U+g), we can achieve zero jitter.  In this case, the
   E2E buffered latency bound becomes (2U+g-W), which is roughly twice
   the E2E latency bound.  In contrast, if we set m to its minimum
   possible value W+g, then the jitter bound becomes (U-W), which is
   roughly equal to U, while the E2E buffered latency bound becomes U,
   which is the same as the E2E latency bound.

   The parameter m directly controls the holding interval of the first
   packet.  It plays a critical role in determining the jitter and the
   buffered latency upper bounds of a flow in the BN framework.  The
   larger the m, the smaller the jitter bound, and the larger the
   latency bound.  With a sufficiently large m, we can guarantee zero
   jitter, at the cost of an increased latency bound.

5.4.  Frequency synchronization between the source and the buffer

   Clock drift refers to phenomena wherein a clock does not run at
   exactly the same rate as a reference clock.  If we do not frequency-
   synchronize the clocks of different nodes in a network, clock drift
   is unavoidable.  Consequently, jitter occurs owing to the clock
   frequency difference or clock drift between the source (timestamper)
   and the buffer.  Therefore, it is recommended to frequency-
   synchronize the source (timestamper) and the buffer.

5.5.  Omission of the timestamper

   For isochronous traffic whose inter-arrival times are well-known
   fixed values, and the network can preserve the FIFO property for such
   traffic, then the timestampers can be omitted.

   Otherwise the FIFO property cannot be guaranteed, then a sequence
   number field in the packet header would be enough to replace the

5.6.  Mitigation of the increased E2E buffered latency

   The increased E2E buffered latency bound by the proposed framework,
   from U to almost 2U, can be mitigated by one of the added
   functionalities given as follows.

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   1) First, one can measure the E2E latency of a flow's first packet
   exactly, and buffer it to make its E2E buffered latency be U.  Then,
   by following the rules given in Section 5.3, every subsequent packet
   will experience the same E2E buffered latency, which is U, with zero
   jitter.  An example of the exact latency measurement may be performed
   by time-synchronization between the source (timestamper) and the
   buffer.  However, how to measure the latency is for further

   2) Second, one can expedite the first packet's service with a special
   treatment, to make its latency lower, compared to the other packets
   of the flow.  If we can make the first packet's latency to be a small
   value d, then every packet will experience the same buffered latency
   d+U, with zero jitter.  Considering that the E2E latency bound is
   calculated from the worst case in which rare events occur
   simultaneously, however, the first packet's latency is likely to be
   far less than what the bound suggests.  Therefore, the special
   treatment to the first packet may be ineffective in real

5.7.  Multi-sources single-destination flows' jitter control

   The BN framework can also be used for jitter control among multiple
   sources' flows having a single destination.  When a session is
   composed of more than one sources, physically or virtually separated,
   the buffer at the boundary can mitigate the latency variations of
   packets from different sources due to different routes or network
   treatments.  Such a scenario may arise in cases such as

      1) that a central unit controls multiple devices for a coordinated
      execution in smart factories, or

      2) multi-user conferencing applications, in which multiple
      devices/users physically separated can have a difficulty in real-
      time interactions.

   The sources, or the ingress boundary nodes of the network, need to be
   synchronized with each other in order for the time-stamps from
   separated sources to be able to identify the absolute arrival times.

6.  IANA Considerations

   There are no IANA actions required by this document.

7.  Security Considerations

   This section will be described later.

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8.  Acknowledgements

9.  Contributor

10.  References

10.1.  Normative References

              Finn, N., Boudec, J. L., Mohammadpour, E., Zhang, J., and
              B. Varga, "DetNet Bounded Latency", Work in Progress,
              Internet-Draft, draft-ietf-detnet-bounded-latency-10, 8
              April 2022, <

              Liu, P., Li, Y., Eckert, T., Xiong, Q., Ryoo, J., Zhu, S.,
              and X. Geng, "Requirements for Large-Scale Deterministic
              Networks", Work in Progress, Internet-Draft, draft-liu-
              detnet-large-scale-requirements-05, 20 October 2022,

   [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, <>.

   [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,

10.2.  Informative References

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   [ADN]      Joung, J., Kwon, J., Ryoo, J., and T. Cheung,
              "Asynchronous Deterministic Network Based on the DiffServ
              Architecture", IEEE Access, vol. 10, pp. 15068-15083,
              doi:10.1109/ACCESS.2022.3146398, 2022.

   [ANDREWS]  Andrews, M., "Instability of FIFO in the permanent
              sessions model at arbitrarily small network loads", ACM
              Trans. Algorithms, vol. 5, no. 3, pp. 1-29, doi:
              10.1145/1541885.1541894, July 2009.

   [BN]       Joung, J. and J. Kwon, "Zero jitter for deterministic
              networks without time-synchronization", IEEE Access, vol.
              9, pp. 49398-49414, doi:10.1109/ACCESS.2021.3068515, 2021.

              Bouillard, A., Boyer, M., and E. Le Corronc,
              "Deterministic network calculus: From theory to practical
              implementation", in Networks and Telecommunications.
              Hoboken, NJ, USA: Wiley, doi: 10.1002/9781119440284, 2018.

   [FAIR]     Joung, J., "Framework for delay guarantee in multi-domain
              networks based on interleaved regulators",
              Electronics, vol. 9, no. 3, p. 436,
              doi:10.3390/electronics9030436, March 2020.

              Li, Y., Ren, S., Li, G., Yang, F., Ryoo, J., and P. Liu,
              "IPv6 Options for Cyclic Queuing and Forwarding Variants",
              Work in Progress, Internet-Draft, draft-yizhou-detnet-
              ipv6-options-for-cqf-variant-00, 19 June 2022,

              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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   [LBF]      Clenm, A. and T. Eckert, "High-precision latency
              forwarding over packet-programmable networks", NOMS 2020
              - IEEE/IFIP Network Operations and Management Symposium,
              April 2020.

   [LEBOUDEC] Le Boudec, J., "A theory of traffic regulators for
              deterministic networks with application to interleaved
              regulators", IEEE/ACM Trans. Networking, vol. 26, no. 6,
              pp. 2721-2733, doi:10.1109/TNET.2018.2875191, December

   [PAREKH]   Parekh, A. and R. Gallager, "A generalized processor
              sharing approach to flow control in integrated services
              networks: the single-node case", IEEE/ACM Trans.
              Networking, vol. 1, no. 3, pp. 344-357, June 1993.

   [RFC2212]  Shenker, S., Partridge, C., and R. Guerin, "Specification
              of Guaranteed Quality of Service", RFC 2212,
              DOI 10.17487/RFC2212, September 1997,

   [RFC3393]  Demichelis, C. and P. Chimento, "IP Packet Delay Variation
              Metric for IP Performance Metrics (IPPM)", RFC 3393,
              DOI 10.17487/RFC3393, November 2002,

              Stiliadis, D. and A. Anujan, "Rate-proportional servers: A
              design methodology for fair queueing algorithms", IEEE/ACM
              Trans. Networking, vol. 6, no. 2, pp. 164-174, 1998.

   [STOICA]   Stoica, I. and H. Zhang, "Providing guaranteed services
              without per flow management", ACM SIGCOMM Computer
              Communication Review, vol. 29, no. 4, pp. 81-94, 1999.

   [THOMAS]   Thomas, L., Le Boudec, J., and A. Mifdaoui, "On cyclic
              dependencies and regulators in time-sensitive networks",
              in Proc. IEEE Real-Time Syst. Symp. (RTSS), York, U.K.,
              pp. 299-311, December 2019.

   [Y.3113]   International Telecommunication Union, "Framework for
              Latency Guarantee in Large Scale Networks Including
              IMT-2020 Network", ITU-T Recommendation Y.3113, February

   [ZHANG]    Zhang, L., "Virtual clock: A new traffic control algorithm
              for packet switching networks", in Proc. ACM symposium on
              Communications architectures & protocols, pp. 19-29, 1990.

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Authors' Addresses

   Jinoo Joung
   Sangmyung University

   Jeong-dong Ryoo

   Taesik Cheung

   Yizhou Li

   Peng Liu
   China Mobile

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