Transport Area Working Group                             B. Briscoe, Ed.
Internet-Draft                                               Independent
Intended status: Informational                            K. De Schepper
Expires: May 19, 2021                                    Nokia Bell Labs
                                                        M. Bagnulo Braun
                                        Universidad Carlos III de Madrid
                                                                G. White
                                                       November 15, 2020

   Low Latency, Low Loss, Scalable Throughput (L4S) Internet Service:


   This document describes the L4S architecture, which enables Internet
   applications to achieve Low queuing Latency, Low Loss, and Scalable
   throughput (L4S).  The insight on which L4S is based is that the root
   cause of queuing delay is in the congestion controllers of senders,
   not in the queue itself.  The L4S architecture is intended to enable
   _all_ Internet applications to transition away from congestion
   control algorithms that cause queuing delay, to a new class of
   congestion controls that induce very little queuing, aided by
   explicit congestion signaling from the network.  This new class of
   congestion control can provide low latency for capacity-seeking
   flows, so applications can achieve both high bandwidth and low

   The architecture primarily concerns incremental deployment.  It
   defines mechanisms that allow the new class of L4S congestion
   controls to coexist with 'Classic' congestion controls in a shared
   network.  These mechanisms aim to ensure that the latency and
   throughput performance using an L4S-compliant congestion controller
   is usually much better (and never worse) than the performance would
   have been using a 'Classic' congestion controller, and that competing
   flows continuing to use 'Classic' controllers are typically not
   impacted by the presence of L4S.  These characteristics are important
   to encourage adoption of L4S congestion control algorithms and L4S
   compliant network elements.

   The L4S architecture consists of three components: network support to
   isolate L4S traffic from classic traffic; protocol features that
   allow network elements to identify L4S traffic; and host support for
   L4S congestion controls.

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Status of This Memo

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Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   3
   2.  L4S Architecture Overview . . . . . . . . . . . . . . . . . .   5
   3.  Terminology . . . . . . . . . . . . . . . . . . . . . . . . .   6
   4.  L4S Architecture Components . . . . . . . . . . . . . . . . .   7
   5.  Rationale . . . . . . . . . . . . . . . . . . . . . . . . . .  12
     5.1.  Why These Primary Components? . . . . . . . . . . . . . .  12
     5.2.  What L4S adds to Existing Approaches  . . . . . . . . . .  14
   6.  Applicability . . . . . . . . . . . . . . . . . . . . . . . .  17
     6.1.  Applications  . . . . . . . . . . . . . . . . . . . . . .  17
     6.2.  Use Cases . . . . . . . . . . . . . . . . . . . . . . . .  19
     6.3.  Applicability with Specific Link Technologies . . . . . .  20
     6.4.  Deployment Considerations . . . . . . . . . . . . . . . .  20
       6.4.1.  Deployment Topology . . . . . . . . . . . . . . . . .  21
       6.4.2.  Deployment Sequences  . . . . . . . . . . . . . . . .  22

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       6.4.3.  L4S Flow but Non-ECN Bottleneck . . . . . . . . . . .  25
       6.4.4.  L4S Flow but Classic ECN Bottleneck . . . . . . . . .  25
       6.4.5.  L4S AQM Deployment within Tunnels . . . . . . . . . .  26
   7.  IANA Considerations (to be removed by RFC Editor) . . . . . .  26
   8.  Security Considerations . . . . . . . . . . . . . . . . . . .  26
     8.1.  Traffic Rate (Non-)Policing . . . . . . . . . . . . . . .  26
     8.2.  'Latency Friendliness'  . . . . . . . . . . . . . . . . .  27
     8.3.  Interaction between Rate Policing and L4S . . . . . . . .  29
     8.4.  ECN Integrity . . . . . . . . . . . . . . . . . . . . . .  29
     8.5.  Privacy Considerations  . . . . . . . . . . . . . . . . .  30
   9.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  31
   10. Informative References  . . . . . . . . . . . . . . . . . . .  31
   Appendix A.  Standardization items  . . . . . . . . . . . . . . .  38
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  40

1.  Introduction

   It is increasingly common for _all_ of a user's applications at any
   one time to require low delay: interactive Web, Web services, voice,
   conversational video, interactive video, interactive remote presence,
   instant messaging, online gaming, remote desktop, cloud-based
   applications and video-assisted remote control of machinery and
   industrial processes.  In the last decade or so, much has been done
   to reduce propagation delay by placing caches or servers closer to
   users.  However, queuing remains a major, albeit intermittent,
   component of latency.  For instance spikes of hundreds of
   milliseconds are common, even with state-of-the-art active queue
   management (AQM).  During a long-running flow, queuing is typically
   configured to cause overall network delay to roughly double relative
   to expected base (unloaded) path delay.  Low loss is also important
   because, for interactive applications, losses translate into even
   longer retransmission delays.

   It has been demonstrated that, once access network bit rates reach
   levels now common in the developed world, increasing capacity offers
   diminishing returns if latency (delay) is not addressed.
   Differentiated services (Diffserv) offers Expedited Forwarding
   (EF [RFC3246]) for some packets at the expense of others, but this is
   not sufficient when all (or most) of a user's applications require
   low latency.

   Therefore, the goal is an Internet service with ultra-Low queueing
   Latency, ultra-Low Loss and Scalable throughput (L4S).  Ultra-low
   queuing latency means less than 1 millisecond (ms) on average and
   less than about 2 ms at the 99th percentile.  L4S is potentially for
   _all_ traffic - a service for all traffic needs none of the
   configuration or management baggage (traffic policing, traffic

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   contracts) associated with favouring some traffic over others.  This
   document describes the L4S architecture for achieving these goals.

   It must be said that queuing delay only degrades performance
   infrequently [Hohlfeld14].  It only occurs when a large enough
   capacity-seeking (e.g. TCP) flow is running alongside the user's
   traffic in the bottleneck link, which is typically in the access
   network.  Or when the low latency application is itself a large
   capacity-seeking or adaptive rate (e.g. interactive video) flow.  At
   these times, the performance improvement from L4S must be sufficient
   that network operators will be motivated to deploy it.

   Active Queue Management (AQM) is part of the solution to queuing
   under load.  AQM improves performance for all traffic, but there is a
   limit to how much queuing delay can be reduced by solely changing the
   network; without addressing the root of the problem.

   The root of the problem is the presence of standard TCP congestion
   control (Reno [RFC5681]) or compatible variants (e.g. TCP
   Cubic [RFC8312]).  We shall use the term 'Classic' for these Reno-
   friendly congestion controls.  Classic congestion controls induce
   relatively large saw-tooth-shaped excursions up the queue and down
   again, which have been growing as flow rate scales [RFC3649].  So if
   a network operator naively attempts to reduce queuing delay by
   configuring an AQM to operate at a shallower queue, a Classic
   congestion control will significantly underutilize the link at the
   bottom of every saw-tooth.

   It has been demonstrated that if the sending host replaces a Classic
   congestion control with a 'Scalable' alternative, when a suitable AQM
   is deployed in the network the performance under load of all the
   above interactive applications can be significantly improved.  For
   instance, queuing delay under heavy load with the example DCTCP/DualQ
   solution cited below on a DSL or Ethernet link is roughly 1 to 2
   milliseconds at the 99th percentile without losing link
   utilization [DualPI2Linux], [DCttH15] (for other link types, see
   Section 6.3).  This compares with 5 to 20 ms on _average_ with a
   Classic congestion control and current state-of-the-art AQMs such as
   FQ-CoDel [RFC8290], PIE [RFC8033] or DOCSIS PIE [RFC8034] and about
   20-30 ms at the 99th percentile [DualPI2Linux].

   It has also been demonstrated [DCttH15], [DualPI2Linux] that it is
   possible to deploy such an L4S service alongside the existing best
   efforts service so that all of a user's applications can shift to it
   when their stack is updated.  Access networks are typically designed
   with one link as the bottleneck for each site (which might be a home,
   small enterprise or mobile device), so deployment at each end of this
   link should give nearly all the benefit in each direction.  The L4S

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   approach also requires component mechanisms at the endpoints to
   fulfill its goal.  This document presents the L4S architecture, by
   describing the different components and how they interact to provide
   the scalable, low latency, low loss Internet service.

2.  L4S Architecture Overview

   There are three main components to the L4S architecture:

   1) Network:  L4S traffic needs to be isolated from the queuing
      latency of Classic traffic.  One queue per application flow (FQ)
      is one way to achieve this, e.g. FQ-CoDel [RFC8290].  However,
      just two queues is sufficient and does not require inspection of
      transport layer headers in the network, which is not always
      possible (see Section 5.2).  With just two queues, it might seem
      impossible to know how much capacity to schedule for each queue
      without inspecting how many flows at any one time are using each.
      And it would be undesirable to arbitrarily divide access network
      capacity into two partitions.  The Dual Queue Coupled AQM was
      developed as a minimal complexity solution to this problem.  It
      acts like a 'semi-permeable' membrane that partitions latency but
      not bandwidth.  As such, the two queues are for transition from
      Classic to L4S behaviour, not bandwidth prioritization.  Section 4
      gives a high level explanation of how FQ and DualQ solutions work,
      and [I-D.ietf-tsvwg-aqm-dualq-coupled] gives a full explanation of
      the DualQ Coupled AQM framework.

   2) Protocol:  A host needs to distinguish L4S and Classic packets
      with an identifier so that the network can classify them into
      their separate treatments.  [I-D.ietf-tsvwg-ecn-l4s-id] considers
      various alternative identifiers for L4S, and concludes that all
      alternatives involve compromises, but the ECT(1) and CE codepoints
      of the ECN field represent a workable solution.

   3) Host:  Scalable congestion controls already exist.  They solve the
      scaling problem with Reno congestion control that was explained in
      [RFC3649].  The one used most widely (in controlled environments)
      is Data Center TCP (DCTCP [RFC8257]), which has been implemented
      and deployed in Windows Server Editions (since 2012), in Linux and
      in FreeBSD.  Although DCTCP as-is 'works' well over the public
      Internet, most implementations lack certain safety features that
      will be necessary once it is used outside controlled environments
      like data centres (see Section 6.4.3 and Appendix A).  Scalable
      congestion control will also need to be implemented in protocols
      other than TCP (QUIC, SCTP, RTP/RTCP, RMCAT, etc.).  Indeed,
      between the present document being drafted and published, the
      following scalable congestion controls were implemented: TCP
      Prague [PragueLinux], QUIC Prague, an L4S variant of the RMCAT

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      SCReAM controller [RFC8298] and the L4S ECN part of
      BBRv2 [I-D.cardwell-iccrg-bbr-congestion-control] intended for TCP
      and QUIC transports.

3.  Terminology

   Classic Congestion Control:  A congestion control behaviour that can
      co-exist with standard TCP Reno [RFC5681] without causing
      significantly negative impact on its flow rate [RFC5033].  With
      Classic congestion controls, as flow rate scales, the number of
      round trips between congestion signals (losses or ECN marks) rises
      with the flow rate.  So it takes longer and longer to recover
      after each congestion event.  Therefore control of queuing and
      utilization becomes very slack, and the slightest disturbance
      prevents a high rate from being attained [RFC3649].

      For instance, with 1500 byte packets and an end-to-end round trip
      time (RTT) of 36 ms, over the years, as Reno flow rate scales from
      2 to 100 Mb/s the number of round trips taken to recover from a
      congestion event rises proportionately, from 4 to 200.
      Cubic [RFC8312] was developed to be less unscalable, but it is
      approaching its scaling limit; with the same RTT of 36 ms, at
      100Mb/s it takes about 106 round trips to recover, and at 800 Mb/s
      its recovery time triples to over 340 round trips, or still more
      than 12 seconds (Reno would take 57 seconds).

   Scalable Congestion Control:  A congestion control where the average
      time from one congestion signal to the next (the recovery time)
      remains invariant as the flow rate scales, all other factors being
      equal.  This maintains the same degree of control over queueing
      and utilization whatever the flow rate, as well as ensuring that
      high throughput is more robust to disturbances (e.g. from new
      flows starting).  For instance, DCTCP averages 2 congestion
      signals per round-trip whatever the flow rate, as do other
      recently developed scalable congestion controls, e.g. Relentless
      TCP [Mathis09], TCP Prague [PragueLinux] and the L4S variant of
      SCReAM for real-time media [RFC8298]).See Section 4.3 of
      [I-D.ietf-tsvwg-ecn-l4s-id] for more explanation.

   Classic service:  The Classic service is intended for all the
      congestion control behaviours that co-exist with Reno [RFC5681]
      (e.g. Reno itself, Cubic [RFC8312],
      Compound [I-D.sridharan-tcpm-ctcp], TFRC [RFC5348]).  The term
      'Classic queue' means a queue providing the Classic service.

   Low-Latency, Low-Loss Scalable throughput (L4S) service:  The 'L4S'
      service is intended for traffic from scalable congestion control
      algorithms, such as Data Center TCP [RFC8257].  The L4S service is

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      for more general traffic than just DCTCP--it allows the set of
      congestion controls with similar scaling properties to DCTCP to
      evolve, such as the examples listed above (Relentless, Prague,
      SCReAM).  The term 'L4S queue' means a queue providing the L4S

      The terms Classic or L4S can also qualify other nouns, such as
      'queue', 'codepoint', 'identifier', 'classification', 'packet',
      'flow'.  For example: an L4S packet means a packet with an L4S
      identifier sent from an L4S congestion control.

      Both Classic and L4S services can cope with a proportion of
      unresponsive or less-responsive traffic as well, as long as it
      does not build a queue (e.g. DNS, VoIP, game sync datagrams, etc).

   Reno-friendly:  The subset of Classic traffic that excludes
      unresponsive traffic and excludes experimental congestion controls
      intended to coexist with Reno but without always being strictly
      friendly to it (as allowed by [RFC5033]).  Reno-friendly is used
      in place of 'TCP-friendly', given that friendliness is a property
      of the congestion controller (Reno), not the wire protocol (TCP),
      which is used with many different congestion control behaviours.

   Classic ECN:  The original Explicit Congestion Notification (ECN)
      protocol [RFC3168], which requires ECN signals to be treated as
      equivalent to drops, both when generated in the network and when
      responded to by the sender.

      The names used for the four codepoints of the 2-bit IP-ECN field
      are as defined in [RFC3168]: Not ECT, ECT(0), ECT(1) and CE, where
      ECT stands for ECN-Capable Transport and CE stands for Congestion

   Site:  A home, mobile device, small enterprise or campus, where the
      network bottleneck is typically the access link to the site.  Not
      all network arrangements fit this model but it is a useful, widely
      applicable generalization.

4.  L4S Architecture Components

   The L4S architecture is composed of the following elements.

   Protocols: The L4S architecture encompasses two identifier changes
   (an unassignment and an assignment) and optional further identifiers:

   a.  An essential aspect of a scalable congestion control is the use
       of explicit congestion signals rather than losses, because the
       signals need to be sent frequently and immediately.  In contrast,

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       'Classic' ECN [RFC3168] requires an ECN signal to be treated as
       equivalent to drop, both when it is generated in the network and
       when it is responded to by hosts.  L4S needs networks and hosts
       to support a different meaning for ECN:

       *  much more frequent signals--too often to require an equivalent
          excessive degree of drop from non-ECN flows;

       *  immediately tracking every fluctuation of the queue--too soon
          to warrant dropping packets from non-ECN flows.

       So the standards track [RFC3168] has had to be updated to allow
       L4S packets to depart from the 'same as drop' constraint.
       [RFC8311] is a standards track update to relax specific
       requirements in RFC 3168 (and certain other standards track
       RFCs), which clears the way for the experimental changes proposed
       for L4S.  [RFC8311] also reclassifies the original experimental
       assignment of the ECT(1) codepoint as an ECN nonce [RFC3540] as

   b.  [I-D.ietf-tsvwg-ecn-l4s-id] recommends ECT(1) is used as the
       identifier to classify L4S packets into a separate treatment from
       Classic packets.  This satisfies the requirements for identifying
       an alternative ECN treatment in [RFC4774].

       The CE codepoint is used to indicate Congestion Experienced by
       both L4S and Classic treatments.  This raises the concern that a
       Classic AQM earlier on the path might have marked some ECT(0)
       packets as CE.  Then these packets will be erroneously classified
       into the L4S queue.  [I-D.ietf-tsvwg-ecn-l4s-id] explains why 5
       unlikely eventualities all have to coincide for this to have any
       detrimental effect, which even then would only involve a
       vanishingly small likelihood of a spurious retransmission.

   c.  A network operator might wish to include certain unresponsive,
       non-L4S traffic in the L4S queue if it is deemed to be smoothly
       enough paced and low enough rate not to build a queue.  For
       instance, VoIP, low rate datagrams to sync online games,
       relatively low rate application-limited traffic, DNS, LDAP, etc.
       This traffic would need to be tagged with specific identifiers,
       e.g. a low latency Diffserv Codepoint such as Expedited
       Forwarding (EF [RFC3246]), Non-Queue-Building
       (NQB [I-D.white-tsvwg-nqb]), or operator-specific identifiers.

   Network components: The L4S architecture aims to provide low latency
   without the _need_ for per-flow operations in network components.
   Nonetheless, the architecture does not preclude per-flow solutions -
   it encompasses the following combinations:

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   a.  The Dual Queue Coupled AQM (illustrated in Figure 1) achieves the
       'semi-permeable' membrane property mentioned earlier as follows.
       The obvious part is that using two separate queues isolates the
       queuing delay of one from the other.  The less obvious part is
       how the two queues act as if they are a single pool of bandwidth
       without the scheduler needing to decide between them.  This is
       achieved by having the Classic AQM provide a congestion signal to
       both queues in a manner that ensures a consistent response from
       the two types of congestion control.  In other words, the Classic
       AQM generates a drop/mark probability based on congestion in the
       Classic queue, uses this probability to drop/mark packets in that
       queue, and also uses this probability to affect the marking
       probability in the L4S queue.  This coupling of the congestion
       signaling between the two queues makes the L4S flows slow down to
       leave the right amount of capacity for the Classic traffic (as
       they would if they were the same type of traffic sharing the same
       queue).  Then the scheduler can serve the L4S queue with
       priority, because the L4S traffic isn't offering up enough
       traffic to use all the priority that it is given.  Therefore, on
       short time-scales (sub-round-trip) the prioritization of the L4S
       queue protects its low latency by allowing bursts to dissipate
       quickly; but on longer time-scales (round-trip and longer) the
       Classic queue creates an equal and opposite pressure against the
       L4S traffic to ensure that neither has priority when it comes to
       bandwidth.  The tension between prioritizing L4S and coupling
       marking from Classic results in per-flow fairness.  To protect
       against unresponsive traffic in the L4S queue taking advantage of
       the prioritization and starving the Classic queue, it is
       advisable not to use strict priority, but instead to use a
       weighted scheduler (see Appendix A of

       When there is no Classic traffic, the L4S queue's AQM comes into
       play, and it sets an appropriate marking rate to maintain ultra-
       low queuing delay.

       The Dual Queue Coupled AQM has been specified as generically as
       possible [I-D.ietf-tsvwg-aqm-dualq-coupled] without specifying
       the particular AQMs to use in the two queues so that designers
       are free to implement diverse ideas.  Informational appendices in
       that draft give pseudocode examples of two different specific AQM
       approaches: one called DualPI2 (pronounced Dual PI
       Squared) [DualPI2Linux] that uses the PI2 variant of PIE, and a
       zero-config variant of RED called Curvy RED.  A DualQ Coupled AQM
       based on PIE has also been specified and implemented for Low
       Latency DOCSIS [DOCSIS3.1].

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                        (2)                     (1)
                 .-------^------. .--------------^-------------------.
    ,-(3)-----.                                  ______
   ; ________  :            L4S   --------.     |      |
   :|Scalable| :               _\        ||___\_| mark |
   :| sender | :  __________  / /        ||   / |______|\   _________
   :|________|\; |          |/    --------'         ^    \1|condit'nl|
    `---------'\_|  IP-ECN  |              Coupling :     \|priority |_\
     ________  / |Classifier|                       :     /|scheduler| /
    |Classic |/  |__________|\    --------.      ___:__  / |_________|
    | sender |                \_\  || | |||___\_| mark/|/
    |________|                  /  || | |||   / | drop |
                         Classic  --------'     |______|

     Figure 1: Components of an L4S Solution: 1) Isolation in separate
    network queues; 2) Packet Identification Protocol; and 3) Scalable
                               Sending Host

   b.  A scheduler with per-flow queues can be used for L4S.  It is
       simple to modify an existing design such as FQ-CoDel or FQ-PIE.
       For instance within each queue of an FQ-CoDel system, as well as
       a CoDel AQM, immediate (unsmoothed) shallow threshold ECN marking
       has been added (see Sec.5.2.7 of [RFC8290]).  Then the Classic
       AQM such as CoDel or PIE is applied to non-ECN or ECT(0) packets,
       while the shallow threshold is applied to ECT(1) packets, to give
       sub-millisecond average queue delay.

   c.  It would also be possible to use dual queues for isolation, but
       with per-flow marking to control flow-rates (instead of the
       coupled per-queue marking of the Dual Queue Coupled AQM).  One of
       the two queues would be for isolating L4S packets, which would be
       classified by the ECN codepoint.  Flow rates could be controlled
       by flow-specific marking.  The policy goal of the marking could
       be to differentiate flow rates (e.g. [Nadas20], which requires
       additional signalling of a per-flow 'value'), or to equalize
       flow-rates (perhaps in a similar way to Approx Fair CoDel [AFCD],
       [I-D.morton-tsvwg-codel-approx-fair], but with two queues not

       Note that whenever the term 'DualQ' is used loosely without
       saying whether marking is per-queue or per-flow, it means a dual
       queue AQM with per-queue marking.

   Host mechanisms: The L4S architecture includes two main mechanisms in
   the end host that we enumerate next:

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   a.  Scalable Congestion Control: Data Center TCP is the most widely
       used example.  It has been documented as an informational record
       of the protocol currently in use in controlled
       environments [RFC8257].  A draft list of safety and performance
       improvements for a scalable congestion control to be usable on
       the public Internet has been drawn up (the so-called 'Prague L4S
       requirements' in Appendix A of [I-D.ietf-tsvwg-ecn-l4s-id]).  The
       subset that involve risk of harm to others have been captured as
       normative requirements in Section 4 of
       [I-D.ietf-tsvwg-ecn-l4s-id].  TCP Prague has been implemented in
       Linux as a reference implementation to address these requirements

       Transport protocols other than TCP use various congestion
       controls that are designed to be friendly with Reno.  Before they
       can use the L4S service, it will be necessary to implement
       scalable variants of each of these congestion control behaviours.
       They will eventually need to be updated to implement a scalable
       congestion response, which they will have to indicate by using
       the ECT(1) codepoint.  Scalable variants are under consideration
       for some new transport protocols that are themselves under
       development, e.g. QUIC.  Also the L4S ECN part of
       BBRv2 [I-D.cardwell-iccrg-bbr-congestion-control] is a scalable
       congestion control intended for the TCP and QUIC transports,
       amongst others.  Also an L4S variant of the RMCAT SCReAM
       controller [RFC8298] has been implemented for media transported
       over RTP.

   b.  ECN feedback is sufficient for L4S in some transport protocols
       (specifically DCCP [RFC4340] and QUIC [I-D.ietf-quic-transport]).
       But others either require update or are in the process of being

       *  For the case of TCP, the feedback protocol for ECN embeds the
          assumption from Classic ECN [RFC3168] that an ECN mark is
          equivalent to a drop, making it unusable for a scalable TCP.
          Therefore, the implementation of TCP receivers will have to be
          upgraded [RFC7560].  Work to standardize and implement more
          accurate ECN feedback for TCP (AccECN) is in
          progress [I-D.ietf-tcpm-accurate-ecn], [PragueLinux].

       *  ECN feedback is only roughly sketched in an appendix of the
          SCTP specification [RFC4960].  A fuller specification has been
          proposed in a long-expired draft [I-D.stewart-tsvwg-sctpecn],
          which would need to be implemented and deployed before SCTCP
          could support L4S.

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       *  For RTP, sufficient ECN feedback was defined in [RFC6679], but
          [I-D.ietf-avtcore-cc-feedback-message] defines the latest
          standards track improvements.

5.  Rationale

5.1.  Why These Primary Components?

   Explicit congestion signalling (protocol):  Explicit congestion
      signalling is a key part of the L4S approach.  In contrast, use of
      drop as a congestion signal creates a tension because drop is both
      an impairment (less would be better) and a useful signal (more
      would be better):

      *  Explicit congestion signals can be used many times per round
         trip, to keep tight control, without any impairment.  Under
         heavy load, even more explicit signals can be applied so the
         queue can be kept short whatever the load.  Whereas state-of-
         the-art AQMs have to introduce very high packet drop at high
         load to keep the queue short.  Further, when using ECN, the
         congestion control's sawtooth reduction can be smaller and
         therefore return to the operating point more often, without
         worrying that this causes more signals (one at the top of each
         smaller sawtooth).  The consequent smaller amplitude sawteeth
         fit between a very shallow marking threshold and an empty
         queue, so queue delay variation can be very low, without risk
         of under-utilization.

      *  Explicit congestion signals can be sent immediately to track
         fluctuations of the queue.  L4S shifts smoothing from the
         network (which doesn't know the round trip times of all the
         flows) to the host (which knows its own round trip time).
         Previously, the network had to smooth to keep a worst-case
         round trip stable, which delayed congestion signals by 100-200

      All the above makes it clear that explicit congestion signalling
      is only advantageous for latency if it does not have to be
      considered 'equivalent to' drop (as was required with Classic
      ECN [RFC3168]).  Therefore, in an L4S AQM, the L4S queue uses a
      new L4S variant of ECN that is not equivalent to
      drop [I-D.ietf-tsvwg-ecn-l4s-id], while the Classic queue uses
      either classic ECN [RFC3168] or drop, which are equivalent to each

      Before Classic ECN was standardized, there were various proposals
      to give an ECN mark a different meaning from drop.  However, there
      was no particular reason to agree on any one of the alternative

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      meanings, so 'equivalent to drop' was the only compromise that
      could be reached.  RFC 3168 contains a statement that:

         "An environment where all end nodes were ECN-Capable could
         allow new criteria to be developed for setting the CE
         codepoint, and new congestion control mechanisms for end-node
         reaction to CE packets.  However, this is a research issue, and
         as such is not addressed in this document."

   Latency isolation (network):  L4S congestion controls keep queue
      delay low whereas Classic congestion controls need a queue of the
      order of the RTT to avoid under-utilization.  One queue cannot
      have two lengths, therefore L4S traffic needs to be isolated in a
      separate queue (e.g. DualQ) or queues (e.g. FQ).

   Coupled congestion notification:  Coupling the congestion
      notification between two queues as in the DualQ Coupled AQM is not
      necessarily essential, but it is a simple way to allow senders to
      determine their rate, packet by packet, rather than be overridden
      by a network scheduler.  An alternative is for a network scheduler
      to control the rate of each application flow (see discussion in
      Section 5.2).

   L4S packet identifier (protocol):  Once there are at least two
      treatments in the network, hosts need an identifier at the IP
      layer to distinguish which treatment they intend to use.

   Scalable congestion notification:  A scalable congestion control in
      the host keeps the signalling frequency from the network high so
      that rate variations can be small when signalling is stable, and
      rate can track variations in available capacity as rapidly as
      possible otherwise.

   Low loss:  Latency is not the only concern of L4S.  The 'Low Loss"
      part of the name denotes that L4S generally achieves zero
      congestion loss due to its use of ECN.  Otherwise, loss would
      itself cause delay, particularly for short flows, due to
      retransmission delay [RFC2884].

   Scalable throughput:  The "Scalable throughput" part of the name
      denotes that the per-flow throughput of scalable congestion
      controls should scale indefinitely, avoiding the imminent scaling
      problems with Reno-friendly congestion control
      algorithms [RFC3649].  It was known when TCP congestion avoidance
      was first developed that it would not scale to high bandwidth-
      delay products (see footnote 6 in [TCP-CA]).  Today, regular
      broadband bit-rates over WAN distances are already beyond the
      scaling range of Classic Reno congestion control.  So `less

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      unscalable' Cubic [RFC8312] and Compound [I-D.sridharan-tcpm-ctcp]
      variants of TCP have been successfully deployed.  However, these
      are now approaching their scaling limits.  As the examples in
      Section 3 demonstrate, as flow rate scales Classic congestion
      controls like Reno or Cubic induce a congestion signal more and
      more infrequently (hundreds of round trips at today's flow rates
      and growing), which makes dynamic control very sloppy.  In
      contrast on average a scalable congestion control like DCTCP or
      TCP Prague induces 2 congestion signals per round trip, which
      remains invariant for any flow rate, keeping dynamic control very

      Although work on scaling congestion controls tends to start with
      TCP as the transport, the above is not intended to exclude other
      transports (e.g. SCTP, QUIC) or less elastic algorithms
      (e.g. RMCAT), which all tend to adopt the same or similar

5.2.  What L4S adds to Existing Approaches

   All the following approaches address some part of the same problem
   space as L4S.  In each case, it is shown that L4S complements them or
   improves on them, rather than being a mutually exclusive alternative:

   Diffserv:  Diffserv addresses the problem of bandwidth apportionment
      for important traffic as well as queuing latency for delay-
      sensitive traffic.  Of these, L4S solely addresses the problem of
      queuing latency.  Diffserv will still be necessary where important
      traffic requires priority (e.g. for commercial reasons, or for
      protection of critical infrastructure traffic) - see
      [I-D.briscoe-tsvwg-l4s-diffserv].  Nonetheless, the L4S approach
      can provide low latency for _all_ traffic within each Diffserv
      class (including the case where there is only the one default
      Diffserv class).

      Also, Diffserv only works for a small subset of the traffic on a
      link.  As already explained, it is not applicable when all the
      applications in use at one time at a single site (home, small
      business or mobile device) require low latency.  In contrast,
      because L4S is for all traffic, it needs none of the management
      baggage (traffic policing, traffic contracts) associated with
      favouring some packets over others.  This baggage has probably
      held Diffserv back from widespread end-to-end deployment.

      In particular, because networks tend not to trust end systems to
      identify which packets should be favoured over others, where
      networks assign packets to Diffserv classes they often use packet
      inspection of application flow identifiers or deeper inspection of

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      application signatures.  Thus, nowadays, Diffserv doesn't always
      sit well with encryption of the layers above IP.  So users have to
      choose between privacy and QoS.

      As with Diffserv, the L4S identifier is in the IP header.  But, in
      contrast to Diffserv, the L4S identifier does not convey a want or
      a need for a certain level of quality.  Rather, it promises a
      certain behaviour (scalable congestion response), which networks
      can objectively verify if they need to.  This is because low delay
      depends on collective host behaviour, whereas bandwidth priority
      depends on network behaviour.

   State-of-the-art AQMs:  AQMs such as PIE and FQ-CoDel give a
      significant reduction in queuing delay relative to no AQM at all.
      L4S is intended to complement these AQMs, and should not distract
      from the need to deploy them as widely as possible.  Nonetheless,
      AQMs alone cannot reduce queuing delay too far without
      significantly reducing link utilization, because the root cause of
      the problem is on the host - where Classic congestion controls use
      large saw-toothing rate variations.  The L4S approach resolves
      this tension by ensuring hosts can minimize the size of their
      sawteeth without appearing so aggressive to Classic flows that
      they starve them.

   Per-flow queuing or marking:  Similarly, per-flow approaches such as
      FQ-CoDel or Approx Fair CoDel [AFCD] are not incompatible with the
      L4S approach.  However, per-flow queuing alone is not enough - it
      only isolates the queuing of one flow from others; not from
      itself.  Per-flow implementations still need to have support for
      scalable congestion control added, which has already been done in
      FQ-CoDel (see Sec.5.2.7 of [RFC8290]).  Without this simple
      modification, per-flow AQMs like FQ-CoDel would still not be able
      to support applications that need both ultra-low delay and high
      bandwidth, e.g. video-based control of remote procedures, or
      interactive cloud-based video (see Note 1 below).

      Although per-flow techniques are not incompatible with L4S, it is
      important to have the DualQ alternative.  This is because handling
      end-to-end (layer 4) flows in the network (layer 3 or 2) precludes
      some important end-to-end functions.  For instance:

      A.  Per-flow forms of L4S like FQ-CoDel are incompatible with full
          end-to-end encryption of transport layer identifiers for
          privacy and confidentiality (e.g. IPSec or encrypted VPN
          tunnels), because they require packet inspection to access the
          end-to-end transport flow identifiers.

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          In contrast, the DualQ form of L4S requires no deeper
          inspection than the IP layer.  So, as long as operators take
          the DualQ approach, their users can have both ultra-low
          queuing delay and full end-to-end encryption [RFC8404].

      B.  With per-flow forms of L4S, the network takes over control of
          the relative rates of each application flow.  Some see it as
          an advantage that the network will prevent some flows running
          faster than others.  Others consider it an inherent part of
          the Internet's appeal that applications can control their rate
          while taking account of the needs of others via congestion
          signals.  They maintain that this has allowed applications
          with interesting rate behaviours to evolve, for instance,
          variable bit-rate video that varies around an equal share
          rather than being forced to remain equal at every instant, or
          scavenger services that use less than an equal share of
          capacity [LEDBAT_AQM].

          The L4S architecture does not require the IETF to commit to
          one approach over the other, because it supports both, so that
          the market can decide.  Nonetheless, in the spirit of 'Do one
          thing and do it well' [McIlroy78], the DualQ option provides
          low delay without prejudging the issue of flow-rate control.
          Then, flow rate policing can be added separately if desired.
          This allows application control up to a point, but the network
          can still choose to set the point at which it intervenes to
          prevent one flow completely starving another.


      1.  It might seem that self-inflicted queuing delay within a per-
          flow queue should not be counted, because if the delay wasn't
          in the network it would just shift to the sender.  However,
          modern adaptive applications, e.g. HTTP/2 [RFC7540] or some
          interactive media applications (see Section 6.1), can keep low
          latency objects at the front of their local send queue by
          shuffling priorities of other objects dependent on the
          progress of other transfers.  They cannot shuffle objects once
          they have released them into the network.

   Alternative Back-off ECN (ABE):  Here again, L4S is not an
      alternative to ABE but a complement that introduces much lower
      queuing delay.  ABE [RFC8511] alters the host behaviour in
      response to ECN marking to utilize a link better and give ECN
      flows faster throughput.  It uses ECT(0) and assumes the network
      still treats ECN and drop the same.  Therefore ABE exploits any
      lower queuing delay that AQMs can provide.  But as explained

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      above, AQMs still cannot reduce queuing delay too far without
      losing link utilization (to allow for other, non-ABE, flows).

   BBR:  Bottleneck Bandwidth and Round-trip propagation time
      (BBR [I-D.cardwell-iccrg-bbr-congestion-control]) controls queuing
      delay end-to-end without needing any special logic in the network,
      such as an AQM.  So it works pretty-much on any path (although it
      has not been without problems, particularly capacity sharing in
      BBRv1).  BBR keeps queuing delay reasonably low, but perhaps not
      quite as low as with state-of-the-art AQMs such as PIE or FQ-
      CoDel, and certainly nowhere near as low as with L4S.  Queuing
      delay is also not consistently low, due to BBR's regular bandwidth
      probing spikes and its aggressive flow start-up phase.

      L4S complements BBR.  Indeed BBRv2 uses L4S ECN and a scalable L4S
      congestion control behaviour in response to any ECN signalling
      from the path.  The L4S ECN signal complements the delay based
      congestion control aspects of BBR with an explicit indication that
      hosts can use, both to converge on a fair rate and to keep below a
      shallow queue target set by the network.  Without L4S ECN, both
      these aspects need to be assumed or estimated.

6.  Applicability

6.1.  Applications

   A transport layer that solves the current latency issues will provide
   new service, product and application opportunities.

   With the L4S approach, the following existing applications also
   experience significantly better quality of experience under load:

   o  Gaming, including cloud based gaming;

   o  VoIP;

   o  Video conferencing;

   o  Web browsing;

   o  (Adaptive) video streaming;

   o  Instant messaging.

   The significantly lower queuing latency also enables some interactive
   application functions to be offloaded to the cloud that would hardly
   even be usable today:

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   o  Cloud based interactive video;

   o  Cloud based virtual and augmented reality.

   The above two applications have been successfully demonstrated with
   L4S, both running together over a 40 Mb/s broadband access link
   loaded up with the numerous other latency sensitive applications in
   the previous list as well as numerous downloads - all sharing the
   same bottleneck queue simultaneously [L4Sdemo16].  For the former, a
   panoramic video of a football stadium could be swiped and pinched so
   that, on the fly, a proxy in the cloud could generate a sub-window of
   the match video under the finger-gesture control of each user.  For
   the latter, a virtual reality headset displayed a viewport taken from
   a 360 degree camera in a racing car.  The user's head movements
   controlled the viewport extracted by a cloud-based proxy.  In both
   cases, with 7 ms end-to-end base delay, the additional queuing delay
   of roughly 1 ms was so low that it seemed the video was generated

   Using a swiping finger gesture or head movement to pan a video are
   extremely latency-demanding actions--far more demanding than VoIP.
   Because human vision can detect extremely low delays of the order of
   single milliseconds when delay is translated into a visual lag
   between a video and a reference point (the finger or the orientation
   of the head sensed by the balance system in the inner ear --- the
   vestibular system).

   Without the low queuing delay of L4S, cloud-based applications like
   these would not be credible without significantly more access
   bandwidth (to deliver all possible video that might be viewed) and
   more local processing, which would increase the weight and power
   consumption of head-mounted displays.  When all interactive
   processing can be done in the cloud, only the data to be rendered for
   the end user needs to be sent.

   Other low latency high bandwidth applications such as:

   o  Interactive remote presence;

   o  Video-assisted remote control of machinery or industrial

   are not credible at all without very low queuing delay.  No amount of
   extra access bandwidth or local processing can make up for lost time.

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6.2.  Use Cases

   The following use-cases for L4S are being considered by various
   interested parties:

   o  Where the bottleneck is one of various types of access network:
      e.g. DSL, Passive Optical Networks (PON), DOCSIS cable, mobile,
      satellite (see Section 6.3 for some technology-specific details)

   o  Private networks of heterogeneous data centres, where there is no
      single administrator that can arrange for all the simultaneous
      changes to senders, receivers and network needed to deploy DCTCP:

      *  a set of private data centres interconnected over a wide area
         with separate administrations, but within the same company

      *  a set of data centres operated by separate companies
         interconnected by a community of interest network (e.g. for the
         finance sector)

      *  multi-tenant (cloud) data centres where tenants choose their
         operating system stack (Infrastructure as a Service - IaaS)

   o  Different types of transport (or application) congestion control:

      *  elastic (TCP/SCTP);

      *  real-time (RTP, RMCAT);

      *  query (DNS/LDAP).

   o  Where low delay quality of service is required, but without
      inspecting or intervening above the IP layer [RFC8404]:

      *  mobile and other networks have tended to inspect higher layers
         in order to guess application QoS requirements.  However, with
         growing demand for support of privacy and encryption, L4S
         offers an alternative.  There is no need to select which
         traffic to favour for queuing, when L4S gives favourable
         queuing to all traffic.

   o  If queuing delay is minimized, applications with a fixed delay
      budget can communicate over longer distances, or via a longer
      chain of service functions [RFC7665] or onion routers.

   o  If delay jitter is minimized, it is possible to reduce the
      dejitter buffers on the receive end of video streaming, which
      should improve the interactive experience

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6.3.  Applicability with Specific Link Technologies

   Certain link technologies aggregate data from multiple packets into
   bursts, and buffer incoming packets while building each burst.  WiFi,
   PON and cable all involve such packet aggregation, whereas fixed
   Ethernet and DSL do not.  No sender, whether L4S or not, can do
   anything to reduce the buffering needed for packet aggregation.  So
   an AQM should not count this buffering as part of the queue that it
   controls, given no amount of congestion signals will reduce it.

   Certain link technologies also add buffering for other reasons,

   o  Radio links (cellular, WiFi, satellite) that are distant from the
      source are particularly challenging.  The radio link capacity can
      vary rapidly by orders of magnitude, so it is considered desirable
      to hold a standing queue that can utilize sudden increases of

   o  Cellular networks are further complicated by a perceived need to
      buffer in order to make hand-overs imperceptible;

   L4S cannot remove the need for all these different forms of
   buffering.  However, by removing 'the longest pole in the tent'
   (buffering for the large sawteeth of Classic congestion controls),
   L4S exposes all these 'shorter poles' to greater scrutiny.

   Until now, the buffering needed for these additional reasons tended
   to be over-specified - with the excuse that none were 'the longest
   pole in the tent'.  But having removed the 'longest pole', it becomes
   worthwhile to minimize them, for instance reducing packet aggregation
   burst sizes and MAC scheduling intervals.

6.4.  Deployment Considerations

   L4S AQMs, whether DualQ [I-D.ietf-tsvwg-aqm-dualq-coupled] or FQ,
   e.g. [RFC8290] are, in themselves, an incremental deployment
   mechanism for L4S - so that L4S traffic can coexist with existing
   Classic (Reno-friendly) traffic.  Section 6.4.1 explains why only
   deploying an L4S AQM in one node at each end of the access link will
   realize nearly all the benefit of L4S.

   L4S involves both end systems and the network, so Section 6.4.2
   suggests some typical sequences to deploy each part, and why there
   will be an immediate and significant benefit after deploying just one

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   Section 6.4.3 and Section 6.4.4 describe the converse incremental
   deployment case where there is no L4S AQM at the network bottleneck,
   so any L4S flow traversing this bottleneck has to take care in case
   it is competing with Classic traffic.

6.4.1.  Deployment Topology

   L4S AQMs will not have to be deployed throughout the Internet before
   L4S will work for anyone.  Operators of public Internet access
   networks typically design their networks so that the bottleneck will
   nearly always occur at one known (logical) link.  This confines the
   cost of queue management technology to one place.

   The case of mesh networks is different and will be discussed later in
   this section.  But the known bottleneck case is generally true for
   Internet access to all sorts of different 'sites', where the word
   'site' includes home networks, small- to medium-sized campus or
   enterprise networks and even cellular devices (Figure 2).  Also, this
   known-bottleneck case tends to be applicable whatever the access link
   technology; whether xDSL, cable, PON, cellular, line of sight
   wireless or satellite.

   Therefore, the full benefit of the L4S service should be available in
   the downstream direction when an L4S AQM is deployed at the ingress
   to this bottleneck link.  And similarly, the full upstream service
   will be available once an L4S AQM is deployed at the ingress into the
   upstream link.  (Of course, multi-homed sites would only see the full
   benefit once all their access links were covered.)

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                                           (      )
                         __          __  (          )
                        |DQ\________/DQ|( enterprise )
                    ___ |__/        \__| ( /campus  )
                   (   )                   (______)
                 (      )                           ___||_
   +----+      (          )  __                 __ /      \
   | DC |-----(    Core    )|DQ\_______________/DQ|| home |
   +----+      (          ) |__/               \__||______|
                  (_____) __
                         |DQ\__/\        __ ,===.
                         |__/    \  ____/DQ||| ||mobile
                                  \/    \__|||_||device
                                            | o |

   Figure 2: Likely location of DualQ (DQ) Deployments in common access

   Deployment in mesh topologies depends on how over-booked the core is.
   If the core is non-blocking, or at least generously provisioned so
   that the edges are nearly always the bottlenecks, it would only be
   necessary to deploy an L4S AQM at the edge bottlenecks.  For example,
   some data-centre networks are designed with the bottleneck in the
   hypervisor or host NICs, while others bottleneck at the top-of-rack
   switch (both the output ports facing hosts and those facing the

   An L4S AQM would eventually also need to be deployed at any other
   persistent bottlenecks such as network interconnections, e.g. some
   public Internet exchange points and the ingress and egress to WAN
   links interconnecting data-centres.

6.4.2.  Deployment Sequences

   For any one L4S flow to work, it requires 3 parts to have been
   deployed.  This was the same deployment problem that ECN
   faced [RFC8170] so we have learned from that experience.

   Firstly, L4S deployment exploits the fact that DCTCP already exists
   on many Internet hosts (Windows, FreeBSD and Linux); both servers and
   clients.  Therefore, just deploying an L4S AQM at a network
   bottleneck immediately gives a working deployment of all the L4S
   parts.  DCTCP needs some safety concerns to be fixed for general use
   over the public Internet (see Section 2.3 of
   [I-D.ietf-tsvwg-ecn-l4s-id]), but DCTCP is not on by default, so

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   these issues can be managed within controlled deployments or
   controlled trials.

   Secondly, the performance improvement with L4S is so significant that
   it enables new interactive services and products that were not
   previously possible.  It is much easier for companies to initiate new
   work on deployment if there is budget for a new product trial.  If,
   in contrast, there were only an incremental performance improvement
   (as with Classic ECN), spending on deployment tends to be much harder
   to justify.

   Thirdly, the L4S identifier is defined so that initially network
   operators can enable L4S exclusively for certain customers or certain
   applications.  But this is carefully defined so that it does not
   compromise future evolution towards L4S as an Internet-wide service.
   This is because the L4S identifier is defined not only as the end-to-
   end ECN field, but it can also optionally be combined with any other
   packet header or some status of a customer or their access
   link [I-D.ietf-tsvwg-ecn-l4s-id].  Operators could do this anyway,
   even if it were not blessed by the IETF.  However, it is best for the
   IETF to specify that, if they use their own local identifier, it must
   be in combination with the IETF's identifier.  Then, if an operator
   has opted for an exclusive local-use approach, later they only have
   to remove this extra rule to make the service work Internet-wide - it
   will already traverse middleboxes, peerings, etc.

   | | Servers or proxies |      Access link     |             Clients |
   |0| DCTCP (existing)   |                      |    DCTCP (existing) |
   |1|                    |Add L4S AQM downstream|                     |
   |2| Upgrade DCTCP to   |                      |Replace DCTCP feedb'k|
   | | TCP Prague         |                      |         with AccECN |
   | |                 FULLY     WORKS     DOWNSTREAM                  |
   | |                    |                      |    Upgrade DCTCP to |
   |3|                    | Add L4S AQM upstream |          TCP Prague |
   | |                    |                      |                     |
   | |              FULLY WORKS UPSTREAM AND DOWNSTREAM                |

                 Figure 3: Example L4S Deployment Sequence

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   Figure 3 illustrates some example sequences in which the parts of L4S
   might be deployed.  It consists of the following stages:

   1.  Here, the immediate benefit of a single AQM deployment can be
       seen, but limited to a controlled trial or controlled deployment.
       In this example downstream deployment is first, but in other
       scenarios the upstream might be deployed first.  If no AQM at all
       was previously deployed for the downstream access, an L4S AQM
       greatly improves the Classic service (as well as adding the L4S
       service).  If an AQM was already deployed, the Classic service
       will be unchanged (and L4S will add an improvement on top).

   2.  In this stage, the name 'TCP Prague' [PragueLinux] is used to
       represent a variant of DCTCP that is safe to use in a production
       Internet environment.  If the application is primarily
       unidirectional, 'TCP Prague' at one end will provide all the
       benefit needed.  For TCP transports, Accurate ECN feedback
       (AccECN) [I-D.ietf-tcpm-accurate-ecn] is needed at the other end,
       but it is a generic ECN feedback facility that is already planned
       to be deployed for other purposes, e.g. DCTCP, BBR.  The two ends
       can be deployed in either order, because, in TCP, an L4S
       congestion control only enables itself if it has negotiated the
       use of AccECN feedback with the other end during the connection
       handshake.  Thus, deployment of TCP Prague on a server enables
       L4S trials to move to a production service in one direction,
       wherever AccECN is deployed at the other end.  This stage might
       be further motivated by the performance improvements of TCP
       Prague relative to DCTCP (see Appendix A.2 of

       Unlike TCP, from the outset, QUIC ECN
       feedback [I-D.ietf-quic-transport] has supported L4S.  Therefore,
       if the transport is QUIC, one-ended deployment of a Prague
       congestion control at this stage is simple and sufficient.

   3.  This is a two-move stage to enable L4S upstream.  An L4S AQM or
       TCP Prague can be deployed in either order as already explained.
       To motivate the first of two independent moves, the deferred
       benefit of enabling new services after the second move has to be
       worth it to cover the first mover's investment risk.  As
       explained already, the potential for new interactive services
       provides this motivation.  An L4S AQM also improves the upstream
       Classic service - significantly if no other AQM has already been

   Note that other deployment sequences might occur.  For instance: the
   upstream might be deployed first; a non-TCP protocol might be used
   end-to-end, e.g. QUIC, RTP; a body such as the 3GPP might require L4S

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   to be implemented in 5G user equipment, or other random acts of

6.4.3.  L4S Flow but Non-ECN Bottleneck

   If L4S is enabled between two hosts, the L4S sender is required to
   coexist safely with Reno in response to any drop (see Section 4.3 of

   Unfortunately, as well as protecting Classic traffic, this rule
   degrades the L4S service whenever there is any loss, even if the
   cause is not persistent congestion at a bottleneck, e.g.:

   o  congestion loss at other transient bottlenecks, e.g. due to bursts
      in shallower queues;

   o  transmission errors, e.g. due to electrical interference;

   o  rate policing.

   Three complementary approaches are in progress to address this issue,
   but they are all currently research:

   o  In Prague congestion control, ignore certain losses deemed
      unlikely to be due to congestion (using some ideas from
      BBR [I-D.cardwell-iccrg-bbr-congestion-control] regarding isolated
      losses).  This could mask any of the above types of loss while
      still coexisting with drop-based congestion controls.

   o  A combination of RACK, L4S and link retransmission without
      resequencing could repair transmission errors without the head of
      line blocking delay usually associated with link-layer
      retransmission [UnorderedLTE], [I-D.ietf-tsvwg-ecn-l4s-id];

   o  Hybrid ECN/drop rate policers (see Section 8.3).

   L4S deployment scenarios that minimize these issues (e.g. over
   wireline networks) can proceed in parallel to this research, in the
   expectation that research success could continually widen L4S

6.4.4.  L4S Flow but Classic ECN Bottleneck

   Classic ECN support is starting to materialize on the Internet as an
   increased level of CE marking.  It is hard to detect whether this is
   all due to the addition of support for ECN in the Linux
   implementation of FQ-CoDel, which is not problematic, because FQ
   inherently forces the throughput of each flow to be equal

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   irrespective of its aggressiveness.  However, some of this Classic
   ECN marking might be due to single-queue ECN deployment.  This case
   is discussed in Section 4.3 of [I-D.ietf-tsvwg-ecn-l4s-id]).

6.4.5.  L4S AQM Deployment within Tunnels

   An L4S AQM uses the ECN field to signal congestion.  So, in common
   with Classic ECN, if the AQM is within a tunnel or at a lower layer,
   correct functioning of ECN signalling requires correct propagation of
   the ECN field up the layers [RFC6040],

7.  IANA Considerations (to be removed by RFC Editor)

   This specification contains no IANA considerations.

8.  Security Considerations

8.1.  Traffic Rate (Non-)Policing

   Because the L4S service can serve all traffic that is using the
   capacity of a link, it should not be necessary to rate-police access
   to the L4S service.  In contrast, Diffserv only works if some packets
   get less favourable treatment than others.  So Diffserv has to use
   traffic rate policers to limit how much traffic can be favoured.  In
   turn, traffic policers require traffic contracts between users and
   networks as well as pairwise between networks.  Because L4S will lack
   all this management complexity, it is more likely to work end-to-end.

   During early deployment (and perhaps always), some networks will not
   offer the L4S service.  In general, these networks should not need to
   police L4S traffic - they are required not to change the L4S
   identifier, merely treating the traffic as best efforts traffic, as
   they already treat traffic with ECT(1) today.  At a bottleneck, such
   networks will introduce some queuing and dropping.  When a scalable
   congestion control detects a drop it will have to respond safely with
   respect to Classic congestion controls (as required in Section 4.3 of
   [I-D.ietf-tsvwg-ecn-l4s-id]).  This will degrade the L4S service to
   be no better (but never worse) than Classic best efforts, whenever a
   non-ECN bottleneck is encountered on a path (see Section 6.4.3).

   In some cases, networks that solely support Classic ECN [RFC3168] in
   a single queue bottleneck might opt to police L4S traffic in order to
   protect competing Classic ECN traffic.

   Certain network operators might choose to restrict access to the L4S
   class, perhaps only to selected premium customers as a value-added

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   service.  Their packet classifier (item 2 in Figure 1) could identify
   such customers against some other field (e.g. source address range)
   as well as ECN.  If only the ECN L4S identifier matched, but not the
   source address (say), the classifier could direct these packets (from
   non-premium customers) into the Classic queue.  Explaining clearly
   how operators can use an additional local classifiers (see
   [I-D.ietf-tsvwg-ecn-l4s-id]) is intended to remove any motivation to
   bleach the L4S identifier.  Then at least the L4S ECN identifier will
   be more likely to survive end-to-end even though the service may not
   be supported at every hop.  Such local arrangements would only
   require simple registered/not-registered packet classification,
   rather than the managed, application-specific traffic policing
   against customer-specific traffic contracts that Diffserv uses.

8.2.  'Latency Friendliness'

   Like the Classic service, the L4S service relies on self-constraint -
   limiting rate in response to congestion.  In addition, the L4S
   service requires self-constraint in terms of limiting latency
   (burstiness).  It is hoped that self-interest and guidance on dynamic
   behaviour (especially flow start-up, which might need to be
   standardized) will be sufficient to prevent transports from sending
   excessive bursts of L4S traffic, given the application's own latency
   will suffer most from such behaviour.

   Whether burst policing becomes necessary remains to be seen.  Without
   it, there will be potential for attacks on the low latency of the L4S

   If needed, various arrangements could be used to address this

   Local bottleneck queue protection:  A per-flow (5-tuple) queue
      protection function [I-D.briscoe-docsis-q-protection] has been
      developed for the low latency queue in DOCSIS, which has adopted
      the DualQ L4S architecture.  It protects the low latency service
      from any queue-building flows that accidentally or maliciously
      classify themselves into the low latency queue.  It is designed to
      score flows based solely on their contribution to queuing (not
      flow rate in itself).  Then, if the shared low latency queue is at
      risk of exceeding a threshold, the function redirects enough
      packets of the highest scoring flow(s) into the Classic queue to
      preserve low latency.

   Distributed traffic scrubbing:  Rather than policing locally at each
      bottleneck, it may only be necessary to address problems
      reactively, e.g. punitively target any deployments of new bursty

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      malware, in a similar way to how traffic from flooding attack
      sources is rerouted via scrubbing facilities.

   Local bottleneck per-flow scheduling:  Per-flow scheduling should
      inherently isolate non-bursty flows from bursty (see Section 5.2
      for discussion of the merits of per-flow scheduling relative to
      per-flow policing).

   Distributed access subnet queue protection:  Per-flow queue
      protection could be arranged for a queue structure distributed
      across a subnet inter-communicating using lower layer control
      messages (see Section 2.1.4 of [QDyn]).  For instance, in a radio
      access network user equipment already sends regular buffer status
      reports to a radio network controller, which could use this
      information to remotely police individual flows.

   Distributed Congestion Exposure to Ingress Policers:  The Congestion
      Exposure (ConEx) architecture [RFC7713] which uses egress audit to
      motivate senders to truthfully signal path congestion in-band
      where it can be used by ingress policers.  An edge-to-edge variant
      of this architecture is also possible.

   Distributed Domain-edge traffic conditioning:  An architecture
      similar to Diffserv [RFC2475] may be preferred, where traffic is
      proactively conditioned on entry to a domain, rather than
      reactively policed only if it is leads to queuing once combined
      with other traffic at a bottleneck.

   Distributed core network queue protection:  The policing function
      could be divided between per-flow mechanisms at the network
      ingress that characterize the burstiness of each flow into a
      signal carried with the traffic, and per-class mechanisms at
      bottlenecks that act on these signals if queuing actually occurs
      once the traffic converges.  This would be somewhat similar to the
      idea behind core stateless fair queuing, which is in turn similar
      to [Nadas20].

   None of these possible queue protection capabilities are considered a
   necessary part of the L4S architecture, which works without them (in
   a similar way to how the Internet works without per-flow rate
   policing).  Indeed, under normal circumstances, latency policers
   would not intervene, and if operators found they were not necessary
   they could disable them.  Part of the L4S experiment will be to see
   whether such a function is necessary, and which arrangements are most
   appropriate to the size of the problem.

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8.3.  Interaction between Rate Policing and L4S

   As mentioned in Section 5.2, L4S should remove the need for low
   latency Diffserv classes.  However, those Diffserv classes that give
   certain applications or users priority over capacity, would still be
   applicable in certain scenarios (e.g. corporate networks).  Then,
   within such Diffserv classes, L4S would often be applicable to give
   traffic low latency and low loss as well.  Within such a Diffserv
   class, the bandwidth available to a user or application is often
   limited by a rate policer.  Similarly, in the default Diffserv class,
   rate policers are used to partition shared capacity.

   A classic rate policer drops any packets exceeding a set rate,
   usually also giving a burst allowance (variants exist where the
   policer re-marks non-compliant traffic to a discard-eligible Diffserv
   codepoint, so they may be dropped elsewhere during contention).
   Whenever L4S traffic encounters one of these rate policers, it will
   experience drops and the source will have to fall back to a Classic
   congestion control, thus losing the benefits of L4S (Section 6.4.3).
   So, in networks that already use rate policers and plan to deploy
   L4S, it will be preferable to redesign these rate policers to be more
   friendly to the L4S service.

   L4S-friendly rate policing is currently a research area (note that
   this is not the same as latency policing).  It might be achieved by
   setting a threshold where ECN marking is introduced, such that it is
   just under the policed rate or just under the burst allowance where
   drop is introduced.  This could be applied to various types of rate
   policer, e.g. [RFC2697], [RFC2698] or the 'local' (non-ConEx) variant
   of the ConEx congestion policer [I-D.briscoe-conex-policing].  It
   might also be possible to design scalable congestion controls to
   respond less catastrophically to loss that has not been preceded by a
   period of increasing delay.

   The design of L4S-friendly rate policers will require a separate
   dedicated document.  For further discussion of the interaction
   between L4S and Diffserv, see [I-D.briscoe-tsvwg-l4s-diffserv].

8.4.  ECN Integrity

   Receiving hosts can fool a sender into downloading faster by
   suppressing feedback of ECN marks (or of losses if retransmissions
   are not necessary or available otherwise).  Various ways to protect
   transport feedback integrity have been developed.  For instance:

   o  The sender can test the integrity of the receiver's feedback by
      occasionally setting the IP-ECN field to the congestion
      experienced (CE) codepoint, which is normally only set by a

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      congested link.  Then the sender can test whether the receiver's
      feedback faithfully reports what it expects (see 2nd para of
      Section 20.2 of [RFC3168]).

   o  A network can enforce a congestion response to its ECN markings
      (or packet losses) by auditing congestion exposure
      (ConEx) [RFC7713].

   o  The TCP authentication option (TCP-AO [RFC5925]) can be used to
      detect tampering with TCP congestion feedback.

   o  The ECN Nonce [RFC3540] was proposed to detect tampering with
      congestion feedback, but it has been reclassified as
      historic [RFC8311].

   Appendix C.1 of [I-D.ietf-tsvwg-ecn-l4s-id] gives more details of
   these techniques including their applicability and pros and cons.

8.5.  Privacy Considerations

   As discussed in Section 5.2, the L4S architecture does not preclude
   approaches that inspect end-to-end transport layer identifiers.  For
   instance it is simple to add L4S support to FQ-CoDel, which
   classifies by application flow ID in the network.  However, the main
   innovation of L4S is the DualQ AQM framework that does not need to
   inspect any deeper than the outermost IP header, because the L4S
   identifier is in the IP-ECN field.

   Thus, the L4S architecture enables ultra-low queuing delay without
   _requiring_ inspection of information above the IP layer.  This means
   that users who want to encrypt application flow identifiers, e.g. in
   IPSec or other encrypted VPN tunnels, don't have to sacrifice low
   delay [RFC8404].

   Because L4S can provide low delay for a broad set of applications
   that choose to use it, there is no need for individual applications
   or classes within that broad set to be distinguishable in any way
   while traversing networks.  This removes much of the ability to
   correlate between the delay requirements of traffic and other
   identifying features [RFC6973].  There may be some types of traffic
   that prefer not to use L4S, but the coarse binary categorization of
   traffic reveals very little that could be exploited to compromise

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9.  Acknowledgements

   Thanks to Richard Scheffenegger, Wes Eddy, Karen Nielsen, David Black
   and Jake Holland for their useful review comments.

   Bob Briscoe and Koen De Schepper were part-funded by the European
   Community under its Seventh Framework Programme through the Reducing
   Internet Transport Latency (RITE) project (ICT-317700).  Bob Briscoe
   was also part-funded by the Research Council of Norway through the
   TimeIn project, partly by CableLabs and partly by the Comcast
   Innovation Fund.  The views expressed here are solely those of the

10.  Informative References

   [AFCD]     Xue, L., Kumar, S., Cui, C., Kondikoppa, P., Chiu, C-H.,
              and S-J. Park, "Towards fair and low latency next
              generation high speed networks: AFCD queuing", Journal of
              Network and Computer Applications 70:183--193, July 2016.

   [DCttH15]  De Schepper, K., Bondarenko, O., Briscoe, B., and I.
              Tsang, "`Data Centre to the Home': Ultra-Low Latency for
              All", RITE project Technical Report , 2015,

              CableLabs, "MAC and Upper Layer Protocols Interface
              (MULPI) Specification, CM-SP-MULPIv3.1", Data-Over-Cable
              Service Interface Specifications DOCSIS(R) 3.1 Version i17
              or later, January 2019, <https://specification-

              Albisser, O., De Schepper, K., Briscoe, B., Tilmans, O.,
              and H. Steen, "DUALPI2 - Low Latency, Low Loss and
              Scalable (L4S) AQM", Proc. Linux Netdev 0x13 , March 2019,

              Hohlfeld , O., Pujol, E., Ciucu, F., Feldmann, A., and P.
              Barford, "A QoE Perspective on Sizing Network Buffers",
              Proc. ACM Internet Measurement Conf (IMC'14) hmm, November

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              Briscoe, B., "Network Performance Isolation using
              Congestion Policing", draft-briscoe-conex-policing-01
              (work in progress), February 2014.

              Briscoe, B. and G. White, "Queue Protection to Preserve
              Low Latency", draft-briscoe-docsis-q-protection-00 (work
              in progress), July 2019.

              Briscoe, B., "Interactions between Low Latency, Low Loss,
              Scalable Throughput (L4S) and Differentiated Services",
              draft-briscoe-tsvwg-l4s-diffserv-02 (work in progress),
              November 2018.

              Cardwell, N., Cheng, Y., Yeganeh, S., and V. Jacobson,
              "BBR Congestion Control", draft-cardwell-iccrg-bbr-
              congestion-control-00 (work in progress), July 2017.

              Sarker, Z., Perkins, C., Singh, V., and M. Ramalho, "RTP
              Control Protocol (RTCP) Feedback for Congestion Control",
              draft-ietf-avtcore-cc-feedback-message-09 (work in
              progress), November 2020.

              Iyengar, J. and M. Thomson, "QUIC: A UDP-Based Multiplexed
              and Secure Transport", draft-ietf-quic-transport-32 (work
              in progress), October 2020.

              Briscoe, B., Kuehlewind, M., and R. Scheffenegger, "More
              Accurate ECN Feedback in TCP", draft-ietf-tcpm-accurate-
              ecn-13 (work in progress), November 2020.

              Bagnulo, M. and B. Briscoe, "ECN++: Adding Explicit
              Congestion Notification (ECN) to TCP Control Packets",
              draft-ietf-tcpm-generalized-ecn-06 (work in progress),
              October 2020.

              Schepper, K., Briscoe, B., and G. White, "DualQ Coupled
              AQMs for Low Latency, Low Loss and Scalable Throughput
              (L4S)", draft-ietf-tsvwg-aqm-dualq-coupled-12 (work in
              progress), July 2020.

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              Briscoe, B., Kaippallimalil, J., and P. Thaler,
              "Guidelines for Adding Congestion Notification to
              Protocols that Encapsulate IP", draft-ietf-tsvwg-ecn-
              encap-guidelines-13 (work in progress), May 2019.

              Schepper, K. and B. Briscoe, "Identifying Modified
              Explicit Congestion Notification (ECN) Semantics for
              Ultra-Low Queuing Delay (L4S)", draft-ietf-tsvwg-ecn-l4s-
              id-11 (work in progress), November 2020.

              Briscoe, B., "Propagating Explicit Congestion Notification
              Across IP Tunnel Headers Separated by a Shim", draft-ietf-
              tsvwg-rfc6040update-shim-10 (work in progress), March

              Morton, J. and P. Heist, "Controlled Delay Approximate
              Fairness AQM", draft-morton-tsvwg-codel-approx-fair-01
              (work in progress), March 2020.

              Sridharan, M., Tan, K., Bansal, D., and D. Thaler,
              "Compound TCP: A New TCP Congestion Control for High-Speed
              and Long Distance Networks", draft-sridharan-tcpm-ctcp-02
              (work in progress), November 2008.

              Stewart, R., Tuexen, M., and X. Dong, "ECN for Stream
              Control Transmission Protocol (SCTP)", draft-stewart-
              tsvwg-sctpecn-05 (work in progress), January 2014.

              White, G. and T. Fossati, "Identifying and Handling Non
              Queue Building Flows in a Bottleneck Link", draft-white-
              tsvwg-nqb-02 (work in progress), June 2019.

              Bondarenko, O., De Schepper, K., Tsang, I., and B.
              Briscoe, "orderedUltra-Low Delay for All: Live Experience,
              Live Analysis", Proc. MMSYS'16 pp33:1--33:4, May 2016,
              (videos of demos:

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              Al-Saadi, R., Armitage, G., and J. But, "Characterising
              LEDBAT Performance Through Bottlenecks Using PIE, FQ-CoDel
              and FQ-PIE Active Queue Management", Proc. IEEE 42nd
              Conference on Local Computer Networks (LCN) 278--285,
              2017, <>.

              Mathis, M., "Relentless Congestion Control", PFLDNeT'09 ,
              May 2009, <

              McIlroy, M., Pinson, E., and B. Tague, "UNIX Time-Sharing
              System: Foreword", The Bell System Technical Journal
              57:6(1902--1903), July 1978,

   [Nadas20]  Nadas, S., Gombos, G., Fejes, F., and S. Laki, "A
              Congestion Control Independent L4S Scheduler", Proc.
              Applied Networking Research Workshop (ANRW '20) 45--51,
              July 2020.

              Eggert, L., "Experimental Specification of New Congestion
              Control Algorithms", IETF Operational Note ion-tsv-alt-cc,
              July 2007.

              Briscoe, B., De Schepper, K., Albisser, O., Misund, J.,
              Tilmans, O., Kuehlewind, M., and A. Ahmed, "Implementing
              the `TCP Prague' Requirements for Low Latency Low Loss
              Scalable Throughput (L4S)", Proc. Linux Netdev 0x13 ,
              March 2019, <

   [QDyn]     Briscoe, B., "Rapid Signalling of Queue Dynamics",
     Technical Report TR-BB-2017-001;
              arXiv:1904.07044 [cs.NI], September 2017,

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

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   [RFC2697]  Heinanen, J. and R. Guerin, "A Single Rate Three Color
              Marker", RFC 2697, DOI 10.17487/RFC2697, September 1999,

   [RFC2698]  Heinanen, J. and R. Guerin, "A Two Rate Three Color
              Marker", RFC 2698, DOI 10.17487/RFC2698, September 1999,

   [RFC2884]  Hadi Salim, J. and U. Ahmed, "Performance Evaluation of
              Explicit Congestion Notification (ECN) in IP Networks",
              RFC 2884, DOI 10.17487/RFC2884, July 2000,

   [RFC3168]  Ramakrishnan, K., Floyd, S., and D. Black, "The Addition
              of Explicit Congestion Notification (ECN) to IP",
              RFC 3168, DOI 10.17487/RFC3168, September 2001,

   [RFC3246]  Davie, B., Charny, A., Bennet, J., Benson, K., Le Boudec,
              J., Courtney, W., Davari, S., Firoiu, V., and D.
              Stiliadis, "An Expedited Forwarding PHB (Per-Hop
              Behavior)", RFC 3246, DOI 10.17487/RFC3246, March 2002,

   [RFC3540]  Spring, N., Wetherall, D., and D. Ely, "Robust Explicit
              Congestion Notification (ECN) Signaling with Nonces",
              RFC 3540, DOI 10.17487/RFC3540, June 2003,

   [RFC3649]  Floyd, S., "HighSpeed TCP for Large Congestion Windows",
              RFC 3649, DOI 10.17487/RFC3649, December 2003,

   [RFC4340]  Kohler, E., Handley, M., and S. Floyd, "Datagram
              Congestion Control Protocol (DCCP)", RFC 4340,
              DOI 10.17487/RFC4340, March 2006,

   [RFC4774]  Floyd, S., "Specifying Alternate Semantics for the
              Explicit Congestion Notification (ECN) Field", BCP 124,
              RFC 4774, DOI 10.17487/RFC4774, November 2006,

   [RFC4960]  Stewart, R., Ed., "Stream Control Transmission Protocol",
              RFC 4960, DOI 10.17487/RFC4960, September 2007,

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   [RFC5033]  Floyd, S. and M. Allman, "Specifying New Congestion
              Control Algorithms", BCP 133, RFC 5033,
              DOI 10.17487/RFC5033, August 2007,

   [RFC5348]  Floyd, S., Handley, M., Padhye, J., and J. Widmer, "TCP
              Friendly Rate Control (TFRC): Protocol Specification",
              RFC 5348, DOI 10.17487/RFC5348, September 2008,

   [RFC5681]  Allman, M., Paxson, V., and E. Blanton, "TCP Congestion
              Control", RFC 5681, DOI 10.17487/RFC5681, September 2009,

   [RFC5925]  Touch, J., Mankin, A., and R. Bonica, "The TCP
              Authentication Option", RFC 5925, DOI 10.17487/RFC5925,
              June 2010, <>.

   [RFC6040]  Briscoe, B., "Tunnelling of Explicit Congestion
              Notification", RFC 6040, DOI 10.17487/RFC6040, November
              2010, <>.

   [RFC6679]  Westerlund, M., Johansson, I., Perkins, C., O'Hanlon, P.,
              and K. Carlberg, "Explicit Congestion Notification (ECN)
              for RTP over UDP", RFC 6679, DOI 10.17487/RFC6679, August
              2012, <>.

   [RFC6973]  Cooper, A., Tschofenig, H., Aboba, B., Peterson, J.,
              Morris, J., Hansen, M., and R. Smith, "Privacy
              Considerations for Internet Protocols", RFC 6973,
              DOI 10.17487/RFC6973, July 2013,

   [RFC7540]  Belshe, M., Peon, R., and M. Thomson, Ed., "Hypertext
              Transfer Protocol Version 2 (HTTP/2)", RFC 7540,
              DOI 10.17487/RFC7540, May 2015,

   [RFC7560]  Kuehlewind, M., Ed., Scheffenegger, R., and B. Briscoe,
              "Problem Statement and Requirements for Increased Accuracy
              in Explicit Congestion Notification (ECN) Feedback",
              RFC 7560, DOI 10.17487/RFC7560, August 2015,

   [RFC7665]  Halpern, J., Ed. and C. Pignataro, Ed., "Service Function
              Chaining (SFC) Architecture", RFC 7665,
              DOI 10.17487/RFC7665, October 2015,

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   [RFC7713]  Mathis, M. and B. Briscoe, "Congestion Exposure (ConEx)
              Concepts, Abstract Mechanism, and Requirements", RFC 7713,
              DOI 10.17487/RFC7713, December 2015,

   [RFC8033]  Pan, R., Natarajan, P., Baker, F., and G. White,
              "Proportional Integral Controller Enhanced (PIE): A
              Lightweight Control Scheme to Address the Bufferbloat
              Problem", RFC 8033, DOI 10.17487/RFC8033, February 2017,

   [RFC8034]  White, G. and R. Pan, "Active Queue Management (AQM) Based
              on Proportional Integral Controller Enhanced PIE) for
              Data-Over-Cable Service Interface Specifications (DOCSIS)
              Cable Modems", RFC 8034, DOI 10.17487/RFC8034, February
              2017, <>.

   [RFC8170]  Thaler, D., Ed., "Planning for Protocol Adoption and
              Subsequent Transitions", RFC 8170, DOI 10.17487/RFC8170,
              May 2017, <>.

   [RFC8257]  Bensley, S., Thaler, D., Balasubramanian, P., Eggert, L.,
              and G. Judd, "Data Center TCP (DCTCP): TCP Congestion
              Control for Data Centers", RFC 8257, DOI 10.17487/RFC8257,
              October 2017, <>.

   [RFC8290]  Hoeiland-Joergensen, T., McKenney, P., Taht, D., Gettys,
              J., and E. Dumazet, "The Flow Queue CoDel Packet Scheduler
              and Active Queue Management Algorithm", RFC 8290,
              DOI 10.17487/RFC8290, January 2018,

   [RFC8298]  Johansson, I. and Z. Sarker, "Self-Clocked Rate Adaptation
              for Multimedia", RFC 8298, DOI 10.17487/RFC8298, December
              2017, <>.

   [RFC8311]  Black, D., "Relaxing Restrictions on Explicit Congestion
              Notification (ECN) Experimentation", RFC 8311,
              DOI 10.17487/RFC8311, January 2018,

   [RFC8312]  Rhee, I., Xu, L., Ha, S., Zimmermann, A., Eggert, L., and
              R. Scheffenegger, "CUBIC for Fast Long-Distance Networks",
              RFC 8312, DOI 10.17487/RFC8312, February 2018,

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   [RFC8404]  Moriarty, K., Ed. and A. Morton, Ed., "Effects of
              Pervasive Encryption on Operators", RFC 8404,
              DOI 10.17487/RFC8404, July 2018,

   [RFC8511]  Khademi, N., Welzl, M., Armitage, G., and G. Fairhurst,
              "TCP Alternative Backoff with ECN (ABE)", RFC 8511,
              DOI 10.17487/RFC8511, December 2018,

   [TCP-CA]   Jacobson, V. and M. Karels, "Congestion Avoidance and
              Control", Laurence Berkeley Labs Technical Report ,
              November 1988, <>.

              Briscoe, B. and K. De Schepper, "Scaling TCP's Congestion
              Window for Small Round Trip Times", BT Technical Report
              TR-TUB8-2015-002, May 2015,

              Austrheim, M., "Implementing immediate forwarding for 4G
              in a network simulator", Masters Thesis, Uni Oslo , June

Appendix A.  Standardization items

   The following table includes all the items that will need to be
   standardized to provide a full L4S architecture.

   The table is too wide for the ASCII draft format, so it has been
   split into two, with a common column of row index numbers on the

   The columns in the second part of the table have the following

   WG:  The IETF WG most relevant to this requirement.  The "tcpm/iccrg"
      combination refers to the procedure typically used for congestion
      control changes, where tcpm owns the approval decision, but uses
      the iccrg for expert review [NewCC_Proc];

   TCP:  Applicable to all forms of TCP congestion control;

   DCTCP:  Applicable to Data Center TCP as currently used (in
      controlled environments);

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   DCTCP bis:  Applicable to any future Data Center TCP congestion
      control intended for controlled environments;

   XXX Prague:  Applicable to a Scalable variant of XXX (TCP/SCTP/RMCAT)
      congestion control.

   | Req | Requirement            | Reference                          |
   | #   |                        |                                    |
   | 0   | ARCHITECTURE           |                                    |
   | 1   | L4S IDENTIFIER         | [I-D.ietf-tsvwg-ecn-l4s-id]        |
   | 2   | DUAL QUEUE AQM         | [I-D.ietf-tsvwg-aqm-dualq-coupled] |
   | 3   | Suitable ECN Feedback  | [I-D.ietf-tcpm-accurate-ecn],      |
   |     |                        | [I-D.stewart-tsvwg-sctpecn].       |
   |     |                        |                                    |
   |     | SCALABLE TRANSPORT -   |                                    |
   |     | SAFETY ADDITIONS       |                                    |
   | 4-1 | Fall back to           | [I-D.ietf-tsvwg-ecn-l4s-id] S.2.3, |
   |     | Reno/Cubic on loss     | [RFC8257]                          |
   | 4-2 | Fall back to           | [I-D.ietf-tsvwg-ecn-l4s-id] S.2.3  |
   |     | Reno/Cubic if classic  |                                    |
   |     | ECN bottleneck         |                                    |
   |     | detected               |                                    |
   |     |                        |                                    |
   | 4-3 | Reduce RTT-dependence  | [I-D.ietf-tsvwg-ecn-l4s-id] S.2.3  |
   |     |                        |                                    |
   | 4-4 | Scaling TCP's          | [I-D.ietf-tsvwg-ecn-l4s-id] S.2.3, |
   |     | Congestion Window for  | [TCP-sub-mss-w]                    |
   |     | Small Round Trip Times |                                    |
   |     | SCALABLE TRANSPORT -   |                                    |
   |     | PERFORMANCE            |                                    |
   |     | ENHANCEMENTS           |                                    |
   | 5-1 | Setting ECT in TCP     | [I-D.ietf-tcpm-generalized-ecn]    |
   |     | Control Packets and    |                                    |
   |     | Retransmissions        |                                    |
   | 5-2 | Faster-than-additive   | [I-D.ietf-tsvwg-ecn-l4s-id] (Appx  |
   |     | increase               | A.2.2)                             |
   | 5-3 | Faster Convergence at  | [I-D.ietf-tsvwg-ecn-l4s-id] (Appx  |
   |     | Flow Start             | A.2.2)                             |

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   | #   | WG     | TCP | DCTCP | DCTCP-bis | TCP    | SCTP   | RMCAT  |
   |     |        |     |       |           | Prague | Prague | Prague |
   | 0   | tsvwg  | Y   | Y     | Y         | Y      | Y      | Y      |
   | 1   | tsvwg  |     |       | Y         | Y      | Y      | Y      |
   | 2   | tsvwg  | n/a | n/a   | n/a       | n/a    | n/a    | n/a    |
   |     |        |     |       |           |        |        |        |
   |     |        |     |       |           |        |        |        |
   |     |        |     |       |           |        |        |        |
   | 3   | tcpm   | Y   | Y     | Y         | Y      | n/a    | n/a    |
   |     |        |     |       |           |        |        |        |
   | 4-1 | tcpm   |     | Y     | Y         | Y      | Y      | Y      |
   |     |        |     |       |           |        |        |        |
   | 4-2 | tcpm/  |     |       |           | Y      | Y      | ?      |
   |     | iccrg? |     |       |           |        |        |        |
   |     |        |     |       |           |        |        |        |
   |     |        |     |       |           |        |        |        |
   |     |        |     |       |           |        |        |        |
   |     |        |     |       |           |        |        |        |
   | 4-3 | tcpm/  |     |       | Y         | Y      | Y      | ?      |
   |     | iccrg? |     |       |           |        |        |        |
   | 4-4 | tcpm   | Y   | Y     | Y         | Y      | Y      | ?      |
   |     |        |     |       |           |        |        |        |
   |     |        |     |       |           |        |        |        |
   | 5-1 | tcpm   | Y   | Y     | Y         | Y      | n/a    | n/a    |
   |     |        |     |       |           |        |        |        |
   | 5-2 | tcpm/  |     |       | Y         | Y      | Y      | ?      |
   |     | iccrg? |     |       |           |        |        |        |
   | 5-3 | tcpm/  |     |       | Y         | Y      | Y      | ?      |
   |     | iccrg? |     |       |           |        |        |        |

Authors' Addresses

   Bob Briscoe (editor)


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   Koen De Schepper
   Nokia Bell Labs


   Marcelo Bagnulo
   Universidad Carlos III de Madrid
   Av. Universidad 30
   Leganes, Madrid 28911

   Phone: 34 91 6249500

   Greg White


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