Transport Area Working Group B. Briscoe, Ed.
Internet-Draft Independent
Intended status: Informational K. De Schepper
Expires: September 10, 2020 Nokia Bell Labs
M. Bagnulo Braun
Universidad Carlos III de Madrid
G. White
March 9, 2020

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


This document describes the L4S architecture, which enables Internet applications to achieve Low 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 utilize explicit congestion signaling provided by 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 latency.

The architecture primarily concerns incremental deployment. It defines mechanisms that allow both classes of congestion control to coexist 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 and to provide appropriate congestion signaling to both types; protocol features that allow network elements to identify L4S traffic and allow for communication of congestion signaling; and host support for immediate congestion signaling with an appropriate congestion response that enables scalable performance.

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Table of Contents

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. During a long-running flow, even with state-of-the-art active queue management (AQM), the base speed-of-light path delay roughly doubles. 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 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 flow (e.g. interactive video). 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. 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 is roughly 1 millisecond (1 to 2 ms) at the 99th percentile without losing link utilization. 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] or PIE [RFC8033] and about 20-30 ms at the 99th percentile. Also, with a Classic congestion control, reducing queueing to even 5 ms is typically only possible by losing some utilization.

It has been demonstrated [DCttH15] 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 a single network node should give nearly all the benefit. The L4S 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 (illustrated in Figure 1):

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. [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 capacity in access networks is too costly to arbitrarily partition into two. 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. Note that there is no bandwidth priority between the two queues because they are for transition from Classic to L4S behaviour, not 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, 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 6.3.3 and Appendix A). A similar scalable congestion control will also need to be transplanted into 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 SCReAM controller [RFC8298] and the L4S ECN part of BBRv2 [I-D.cardwell-iccrg-bbr-congestion-control] intended for TCP and QUIC.
                     (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

3. Terminology

The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT", "SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this document are to be interpreted as described in [RFC2119]. In this document, these words will appear with that interpretation only when in ALL CAPS. Lower case uses of these words are not to be interpreted as carrying RFC-2119 significance. COMMENT: Since this will be an information document, This should be removed.

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 36ms, 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 robust to disturbances. For instance, DCTCP averages 2 congestion signals per round-trip whatever the flow rate. 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 for more general traffic than just DCTCP—it allows the set of congestion controls with similar scaling properties to DCTCP to evolve (e.g. Relentless TCP [Mathis09], TCP Prague [PragueLinux] and the L4S variant of SCREAM for real-time media [RFC8298]). The term 'L4S queue' means a queue providing the L4S service.

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).
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 the TCP protocol 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 the same as 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 Experienced.
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 the two identifier changes (an unassignment and an assignment) and optional further identifiers:

  1. 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 immediately and frequently. 'Classic' ECN [RFC3168] requires an ECN signal to be treated the same as a 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:

    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 historic.
  2. [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.
  3. 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 encompasses either dual-queue or per-flow queue solutions:

  1. The Coupled Dual Queue AQM 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.

    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 Coupled Dual Queue 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: a variant of PIE called DualPI2 (pronounced Dual PI Squared) [DualPI2Linux], and a zero-config variant of RED called Curvy RED. A DualQ Coupled AQM variant based on PIE has also been specified and implemented for Low Latency DOCSIS [DOCSIS3.1].
  2. 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. 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.

Host mechanisms: The L4S architecture includes a number of mechanisms in the end host that we enumerate next:

  1. Data Center TCP is the most widely used example of a scalable congestion control. It has been documented as an informational record of the protocol currently in use [RFC8257]. It will be necessary to define a number of safety features for a variant usable on the public Internet. A draft list of these, known as the Prague L4S requirements, has been drawn up (see Appendix A of [I-D.ietf-tsvwg-ecn-l4s-id]). The list also includes some optional performance improvements.
  2. Transport protocols other than TCP use various congestion controls 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. The following standards track RFCs currently define these protocols: ECN in TCP [RFC3168], in SCTP [RFC4960], in RTP [RFC6679], and in DCCP [RFC4340]. Not all are in widespread use, but those that are will eventually need to be updated to allow a different 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 [I-D.ietf-quic-transport] and certain real-time media congestion avoidance techniques (RMCAT) protocols.
  3. ECN feedback is sufficient for L4S in some transport protocols (RTCP, DCCP) but not others:

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 a useful signal (more would reduce delay) and an impairment (less would reduce delay):

All the above makes it clear that explicit congestion signalling is only advantageous for latency if it does not have to be considered 'the same as' drop (as was required with Classic ECN

[RFC3168]). Therefore, in a DualQ 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.

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 meanings, so 'the same as drop' was the only compromise that could be reached. RFC 3168 contains a statement that:
Latency isolation with coupled congestion notification (network):
Using just two queues is not essential to L4S (more would be possible), but it is the simplest way to isolate all the L4S traffic that keeps latency low from all the legacy Classic traffic that does not.

Similarly, coupling the congestion notification between the queues is not necessarily essential, but it is a clever and simple way to allow senders to determine their rate, packet-by-packet, rather than be overridden by a network scheduler. Because otherwise a network scheduler would have to inspect at least transport layer headers, and it would have to continually assign a rate to each flow without any easy way to understand application intent.
L4S packet identifier (protocol):
Once there are at least two separate treatments in the network, hosts need an identifier at the IP layer to distinguish which treatment they intend to use.
Scalable congestion notification (host):
A scalable congestion control keeps the signalling frequency 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 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. For instance, at 800Mb/s with a 20ms round trip, Cubic induces a congestion signal only every 500 round trips or 10 seconds, which makes its 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 tight.

5.2. Why Not Alternative 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 addresses the problem of bandwidth apportionment for important traffic as well as queuing latency for delay-sensitive traffic. L4S solely addresses the problem of queuing latency (as well as loss and throughput scaling). 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, if there are Diffserv classes for important traffic, the L4S approach can provide low latency for all traffic within each Diffserv class (including the case where there is only one Diffserv class).

Also, as already explained, Diffserv only works for a small subset of the traffic on a link. 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. Also, 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 held Diffserv back from widespread end-to-end deployment.
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, without addressing the large saw-toothing rate variations of Classic congestion controls, AQMs alone cannot reduce queuing delay too far without significantly reducing link utilization. The L4S approach resolves this tension by ensuring hosts can minimize the size of their sawteeth without appearing so aggressive to legacy flows that they starve them.
Per-flow queuing:
Similarly, per-flow queuing is not incompatible with the L4S approach. However, one queue for every flow can be thought of as overkill compared to the minimum of two queues for all traffic needed for the L4S approach. The overkill of per-flow queuing has side-effects:
  1. fq makes high performance networking equipment costly (processing and memory) - in contrast dual queue code can be very simple;
  2. fq requires packet inspection into the end-to-end transport layer, which doesn't sit well alongside encryption for privacy - in contrast the use of ECN as the classifier for L4S requires no deeper inspection than the IP layer;
  3. fq isolates the queuing of each flow from the others but not from itself so existing FQ implementations still need to have support for scalable congestion control added.

    It might seem that self-inflicted queuing delay should not count, 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 the interactive media applications described in Section 6, 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 packets once they have released them into the network.
  4. fq prevents any one flow from consuming more than 1/N of the capacity at any instant, where N is the number of flows. This is fine if all flows are elastic, but it does not sit well with a variable bit rate real-time multimedia flow, which requires wriggle room to sometimes take more and other times less than a 1/N share.

    It might seem that an fq scheduler offers the benefit that it prevents individual flows from hogging all the bandwidth. However, L4S has been deliberately designed so that policing of individual flows can be added as a policy choice, rather than requiring one specific policy choice as the mechanism itself. A scheduler (like fq) has to decide packet-by-packet which flow to schedule without knowing application intent. Whereas a separate policing function can be configured less strictly, so that senders can still control the instantaneous rate of each flow dependent on the needs of each application (e.g. variable rate video), giving more wriggle-room before a flow is deemed non-compliant. Also policing of queuing and of flow-rates can be applied independently.
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 above, AQMs still cannot reduce queuing delay too far without losing link utilization (to allow for other, non-ABE, flows).
v1 of 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. Setting some problems with capacity sharing aside, queuing delay is good with BBRv1, 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 its regular bandwidth probes and the aggressive flow start-up phase.

L4S is a complement to BBRv1. Indeed BBRv2 uses L4S ECN and a scalable L4S congestion control behaviour in response to any ECN signalling from the path.

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 will experience significantly better quality of experience under load:

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

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 locally.

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:

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.

6.2. Use Cases

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

6.3. Deployment Considerations

The DualQ is, in itself, an incremental deployment framework for L4S AQMs so that L4S traffic can coexist with existing Classic (Reno-friendly) traffic. Section 6.3.1 explains why only deploying a DualQ AQM [I-D.ietf-tsvwg-aqm-dualq-coupled] 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 6.3.2 suggests some typical sequences to deploy each part, and why there will be an immediate and significant benefit after deploying just one part.

If an ECN-enabled DualQ AQM has not been deployed at a bottleneck, an L4S flow is required to include a fall-back strategy to Classic behaviour. Section 6.3.3 describes how an L4S flow detects this, and how to minimize the effect of false negative detection.

6.3.1. Deployment Topology

DualQ 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, cellular, line-of-sight wireless or satellite.

Therefore, the full benefit of the L4S service should be available in the downstream direction when the DualQ AQM is deployed at the ingress to this bottleneck link (or links for multihomed sites). And similarly, the full upstream service will be available once the DualQ is deployed at the upstream ingress.

                                        (      )
                      __          __  (          )
                     |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 topologies

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 the DualQ 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 core).

The DualQ 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.

6.3.2. 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 this.

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 DualQ 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 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 they must use their own local identifier in combination with the IETF's identifier. Then, if an operator enables the optional local-use approach, 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 |
|1| DCTCP (existing)   |                      |    DCTCP (existing) |
| |                    | DualQ AQM downstream |                     |
|2| TCP Prague         |                      |  AccECN (already in |
| |                    |                      | progress:DCTCP/BBR) |
| |                 FULLY     WORKS     DOWNSTREAM                  |
|3|                    |  DualQ AQM upstream  |          TCP Prague |
| |                    |                      |                     |
| |              FULLY WORKS UPSTREAM AND DOWNSTREAM                |

Figure 3: Example L4S Deployment Sequences

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, the DualQ 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' is used to represent a variant of DCTCP that is safe to use in a production environment. If the application is primarily unidirectional, 'TCP Prague' at one end will provide all the benefit needed. 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 [I-D.cardwell-iccrg-bbr-congestion-control]. 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 [I-D.ietf-tsvwg-ecn-l4s-id]).
  3. This is a two-move stage to enable L4S upstream. The DualQ 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. The DualQ AQM also greatly improves the upstream Classic service, assuming no other AQM has already been deployed.

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, RMCAT; a body such as the 3GPP might require L4S to be implemented in 5G user equipment, or other random acts of kindness.

6.3.3. L4S Flow but Non-L4S Bottleneck

If L4S is enabled between two hosts but there is no L4S AQM at the bottleneck, any drop from the bottleneck will trigger the L4S sender to fall back to a classic ('Reno-friendly') behaviour (see Appendix A.1.3 of [I-D.ietf-tsvwg-ecn-l4s-id]).

Unfortunately, as well as protecting legacy traffic, this rule degrades the L4S service whenever there is a loss, even if the loss was not from a non-DualQ bottleneck (false negative). And unfortunately, prevalent drop can be due to other causes, e.g.:

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

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 applicability.

Classic ECN support is starting to materialize on the Internet as an increased level of CE marking. Given some of this Classic ECN might be due to single-queue ECN deployment, an L4S sender will have to fall back to a classic ('Reno-friendly') behaviour if it detects that ECN marking is accompanied by greater queuing delay or greater delay variation than would be expected with L4S (see Appendix A.1.4 of [I-D.ietf-tsvwg-ecn-l4s-id]). 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 would not require fall-back to Classic behaviour, because FQ inherently forces the throughput of each flow to be equal irrespective of its aggressiveness.

6.3.4. Other Potential Deployment Issues

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], [I-D.ietf-tsvwg-ecn-encap-guidelines].

7. IANA Considerations

This specification contains no IANA considerations.

8. Security Considerations

8.1. Traffic (Non-)Policing

Because the L4S service can serve all traffic that is using the capacity of a link, it should not be necessary to 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. These networks do not need to police or re-mark L4S traffic - they just forward it unchanged as best efforts traffic, as they already forward 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 as if it is a Classic congestion control (as required in Section 2.3 of [I-D.ietf-tsvwg-ecn-l4s-id]). This will ensure safe interworking with other traffic at the 'legacy' bottleneck, but it will degrade the L4S service to no better (but never worse) than classic best efforts, whenever a legacy (non-L4S) bottleneck is encountered on a path.

Certain network operators might choose to restrict access to the L4S class, perhaps only to selected premium customers as a value-added 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. Clearly explaining how operators can use an additional local classifiers (see [I-D.ietf-tsvwg-ecn-l4s-id]) is intended to remove any tendency 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 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 standardization of dynamic behaviour (especially flow start-up) 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 service. However it may only be necessary to apply such policing reactively, e.g. punitively targeted at any deployments of new bursty malware.

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.

Such a queue protection function is not considered a necessary part of the L4S architecture, which works without it (in a similar way to how the Internet works without per-flow rate policing). Indeed, under normal circumstances, DOCSIS queue protection does not intervene, and if operators find it is not necessary they can disable it. Part of the L4S experiment will be to see whether such a function is necessary.

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 has to fall back to a Classic congestion control, thus losing the benefits of L4S. 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:

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

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 authors.

10. References

10.1. Normative References

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

10.2. Informative References

[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.
[DOCSIS3.1] CableLabs, "MAC and Upper Layer Protocols Interface (MULPI) Specification, CM-SP-MULPIv3.1", Data-Over-Cable Service Interface Specifications DOCSIS® 3.1 Version i17 or later, January 2019.
[DualPI2Linux] 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.
[Hohlfeld14] 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 2014.
[I-D.briscoe-conex-policing] Briscoe, B., "Network Performance Isolation using Congestion Policing", Internet-Draft draft-briscoe-conex-policing-01, February 2014.
[I-D.briscoe-docsis-q-protection] Briscoe, B. and G. White, "Queue Protection to Preserve Low Latency", Internet-Draft draft-briscoe-docsis-q-protection-00, July 2019.
[I-D.briscoe-tsvwg-l4s-diffserv] Briscoe, B., "Interactions between Low Latency, Low Loss, Scalable Throughput (L4S) and Differentiated Services", Internet-Draft draft-briscoe-tsvwg-l4s-diffserv-02, November 2018.
[I-D.cardwell-iccrg-bbr-congestion-control] Cardwell, N., Cheng, Y., Yeganeh, S. and V. Jacobson, "BBR Congestion Control", Internet-Draft draft-cardwell-iccrg-bbr-congestion-control-00, July 2017.
[I-D.ietf-quic-transport] Iyengar, J. and M. Thomson, "QUIC: A UDP-Based Multiplexed and Secure Transport", Internet-Draft draft-ietf-quic-transport-27, February 2020.
[I-D.ietf-tcpm-accurate-ecn] Briscoe, B., Kuehlewind, M. and R. Scheffenegger, "More Accurate ECN Feedback in TCP", Internet-Draft draft-ietf-tcpm-accurate-ecn-11, March 2020.
[I-D.ietf-tcpm-generalized-ecn] Bagnulo, M. and B. Briscoe, "ECN++: Adding Explicit Congestion Notification (ECN) to TCP Control Packets", Internet-Draft draft-ietf-tcpm-generalized-ecn-05, November 2019.
[I-D.ietf-tsvwg-aqm-dualq-coupled] Schepper, K., Briscoe, B. and G. White, "DualQ Coupled AQMs for Low Latency, Low Loss and Scalable Throughput (L4S)", Internet-Draft draft-ietf-tsvwg-aqm-dualq-coupled-10, July 2019.
[I-D.ietf-tsvwg-ecn-encap-guidelines] Briscoe, B., Kaippallimalil, J. and P. Thaler, "Guidelines for Adding Congestion Notification to Protocols that Encapsulate IP", Internet-Draft draft-ietf-tsvwg-ecn-encap-guidelines-13, May 2019.
[I-D.ietf-tsvwg-ecn-l4s-id] Schepper, K. and B. Briscoe, "Identifying Modified Explicit Congestion Notification (ECN) Semantics for Ultra-Low Queuing Delay (L4S)", Internet-Draft draft-ietf-tsvwg-ecn-l4s-id-09, February 2020.
[I-D.smith-encrypted-traffic-management] Smith, K., "Network management of encrypted traffic", Internet-Draft draft-smith-encrypted-traffic-management-05, May 2016.
[I-D.sridharan-tcpm-ctcp] Sridharan, M., Tan, K., Bansal, D. and D. Thaler, "Compound TCP: A New TCP Congestion Control for High-Speed and Long Distance Networks", Internet-Draft draft-sridharan-tcpm-ctcp-02, November 2008.
[I-D.stewart-tsvwg-sctpecn] Stewart, R., Tuexen, M. and X. Dong, "ECN for Stream Control Transmission Protocol (SCTP)", Internet-Draft draft-stewart-tsvwg-sctpecn-05, January 2014.
[I-D.white-tsvwg-nqb] White, G. and T. Fossati, "Identifying and Handling Non Queue Building Flows in a Bottleneck Link", Internet-Draft draft-white-tsvwg-nqb-02, June 2019.
[L4Sdemo16] 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.
[Mathis09] Mathis, M., "Relentless Congestion Control", PFLDNeT'09 , May 2009.
[NewCC_Proc] Eggert, L., "Experimental Specification of New Congestion Control Algorithms", IETF Operational Note ion-tsv-alt-cc, July 2007.
[PragueLinux] Briscoe, B., De Schepper, K., Albisser, O., Misund, J., Tilmans, O., Kühlewind, M. and A. Ahmed, "Implementing the `TCP Prague' Requirements for Low Latency Low Loss Scalable Throughput (L4S)", Proc. Linux Netdev 0x13 , March 2019.
[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., "Stream Control Transmission Protocol", RFC 4960, DOI 10.17487/RFC4960, September 2007.
[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.
[RFC7540] Belshe, M., Peon, R. and M. Thomson, "Hypertext Transfer Protocol Version 2 (HTTP/2)", RFC 7540, DOI 10.17487/RFC7540, May 2015.
[RFC7560] Kuehlewind, M., 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. and C. Pignataro, "Service Function Chaining (SFC) Architecture", RFC 7665, DOI 10.17487/RFC7665, October 2015.
[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.
[RFC8170] Thaler, D., "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.
[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.
[TCP-sub-mss-w] 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.
[UnorderedLTE] Austrheim, M., "Implementing immediate forwarding for 4G in a network simulator", Masters Thesis, Uni Oslo , June 2019.

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 left.

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

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];
Applicable to all forms of TCP congestion control;
Applicable to Data Center TCP as currently used (in controlled environments);
DCTCP bis:
Applicable to an 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
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].
4-1 Fall back to Reno/Cubic on loss [I-D.ietf-tsvwg-ecn-l4s-id] S.2.3, [RFC8257]
4-2 Fall back to Reno/Cubic if classic ECN bottleneck detected [I-D.ietf-tsvwg-ecn-l4s-id] S.2.3
4-3 Reduce RTT-dependence [I-D.ietf-tsvwg-ecn-l4s-id] S.2.3
4-4 Scaling TCP's Congestion Window for Small Round Trip Times [I-D.ietf-tsvwg-ecn-l4s-id] S.2.3, [TCP-sub-mss-w]
5-1 Setting ECT in TCP Control Packets and Retransmissions [I-D.ietf-tcpm-generalized-ecn]
5-2 Faster-than-additive increase [I-D.ietf-tsvwg-ecn-l4s-id] (Appx A.2.2)
5-3 Faster Convergence at Flow Start [I-D.ietf-tsvwg-ecn-l4s-id] (Appx A.2.2)
# WG TCP DCTCP DCTCP-bis TCP Prague SCTP Prague RMCAT 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/ iccrg? Y Y ?
4-3 tcpm/ iccrg? Y Y Y ?
4-4 tcpm Y Y Y Y Y ?
5-1 tcpm Y Y Y Y n/a n/a
5-2 tcpm/ iccrg? Y Y Y ?
5-3 tcpm/ iccrg? Y Y Y ?

Authors' Addresses

Bob Briscoe (editor) Independent UK EMail: URI:
Koen De Schepper Nokia Bell Labs Antwerp, Belgium EMail: URI:
Marcelo Bagnulo Universidad Carlos III de Madrid Av. Universidad 30 Leganes, Madrid 28911, Spain Phone: 34 91 6249500 EMail: URI:
Greg White CableLabs US EMail: