Transport Area Working Group B. Briscoe, Ed.
Internet-Draft Independent
Intended status: Informational K. De Schepper
Expires: January 2, 2022 Nokia Bell Labs
M. Bagnulo Braun
Universidad Carlos III de Madrid
G. White
CableLabs
July 1, 2021
Low Latency, Low Loss, Scalable Throughput (L4S) Internet Service:
Architecture
draft-ietf-tsvwg-l4s-arch-10
Abstract
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
latency.
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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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. L4S Architecture Overview . . . . . . . . . . . . . . . . . . 5
3. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 6
4. L4S Architecture Components . . . . . . . . . . . . . . . . . 7
4.1. Protocol Mechanisms . . . . . . . . . . . . . . . . . . . 7
4.2. Network Components . . . . . . . . . . . . . . . . . . . 9
4.3. Host Mechanisms . . . . . . . . . . . . . . . . . . . . . 11
5. Rationale . . . . . . . . . . . . . . . . . . . . . . . . . . 12
5.1. Why These Primary Components? . . . . . . . . . . . . . . 12
5.2. What L4S adds to Existing Approaches . . . . . . . . . . 15
6. Applicability . . . . . . . . . . . . . . . . . . . . . . . . 18
6.1. Applications . . . . . . . . . . . . . . . . . . . . . . 18
6.2. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . 19
6.3. Applicability with Specific Link Technologies . . . . . . 20
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6.4. Deployment Considerations . . . . . . . . . . . . . . . . 21
6.4.1. Deployment Topology . . . . . . . . . . . . . . . . . 21
6.4.2. Deployment Sequences . . . . . . . . . . . . . . . . 22
6.4.3. L4S Flow but Non-ECN Bottleneck . . . . . . . . . . . 25
6.4.4. L4S Flow but Classic ECN Bottleneck . . . . . . . . . 26
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 . . . . . . . . . . . . . . . . . . . . . . 30
8.5. Privacy Considerations . . . . . . . . . . . . . . . . . 30
9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 31
10. Informative References . . . . . . . . . . . . . . . . . . . 31
Appendix A. Standardization items . . . . . . . . . . . . . . . 39
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 41
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 very Low queueing
Latency, very Low Loss and Scalable throughput (L4S). Very 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
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_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 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 5-20 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,
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small enterprise or mobile device), so deployment at each end of this
link should give nearly all the benefit in each direction. 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; the AQM in
the network, the congestion control on the host, and the protocol
between them:
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] 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,
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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 [SCReAM] and the L4S ECN part of BBRv2 [BBRv2]
intended for TCP and QUIC transports.
3. Terminology
Classic Congestion Control: A congestion control behaviour that can
co-exist with standard Reno [RFC5681] without causing
significantly negative impact on its flow rate [RFC5033]. With
Classic congestion controls, such as Reno or Cubic, because flow
rate has scaled since TCP congestion control was first designed in
1988, it now takes hundreds of round trips (and growing) to
recover after a congestion signal (whether a loss or an ECN mark)
as shown in the examples in Section 5.1 and [RFC3649]. Therefore
control of queuing and utilization becomes very slack, and the
slightest disturbances (e.g. from new flows starting) prevent a
high rate from being attained.
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. 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
[I-D.briscoe-iccrg-prague-congestion-control], [PragueLinux],
BBRv2 [BBRv2] and the L4S variant of SCReAM for real-time
media [SCReAM], [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 the Prague congestion control
[I-D.briscoe-iccrg-prague-congestion-control], which was derived
from DCTCP [RFC8257]. The L4S service is for more general
traffic than just TCP Prague--it allows the set of congestion
controls with similar scaling properties to Prague to evolve, such
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as the examples listed above (Relentless, SCReAM). 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, but in the L4S
case its rate has to be smooth enough or low enough not build a
queue (e.g. DNS, VoIP, game sync datagrams, etc).
Reno-friendly: The subset of Classic traffic that is friendly to the
standard Reno congestion control defined for TCP in [RFC5681].
Reno-friendly is used in place of 'TCP-friendly', given the latter
has become imprecise, because the TCP protocol is now used with so
many different congestion control behaviours, and Reno is used in
non-TCP transports such as QUIC.
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.
For L4S, the names used for the four codepoints of the 2-bit IP-
ECN field are unchanged from those 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 packet marked with
the CE codepoint is termed 'ECN-marked' or sometimes just 'marked'
where the context makes ECN obvious.
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 elements in the following
three subsections.
4.1. Protocol Mechanisms
The L4S architecture involves: a) unassignment of an identifier; b)
reassignment of the same identifier; and c) optional further
identifiers:
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a. An essential aspect of a scalable congestion control is the use
of explicit congestion signals. '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 more fine-grained
meaning for each ECN signal that is less severe than a drop, so
that the L4S signals:
* can be much more frequent;
* can be signalled immediately, without the signficant delay
required to smooth out fluctuations in the queue.
To enable L4S, the standards track [RFC3168] has had to be
updated to allow L4S packets to depart from the 'equivalent to
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.
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. Appendix B of [I-D.ietf-tsvwg-ecn-l4s-id]
explains why five 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.ietf-tsvwg-nqb]), or operator-specific identifiers.
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4.2. 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:
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 the
marking from the Classic AQM results in approximate 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
[I-D.ietf-tsvwg-aqm-dualq-coupled]).
When there is no Classic traffic, the L4S queue's AQM comes into
play. It starts congestion marking with a very shallow queue, so
L4S traffic maintains very 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
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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].
(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 such as FQ-CoDel or FQ-PIE can
be used for L4S. For instance within each queue of an FQ-CoDel
system, as well as a CoDel AQM, there is typically also ECN
marking at an immediate (unsmoothed) shallow threshold to support
use in data centres (see Sec.5.2.7 of [RFC8290]). This can be
modified so that the shallow threshold is solely applied to
ECT(1) packets. Then if there is a flow of non-ECN or ECT(0)
packets in the per-flow-queue, the Classic AQM (e.g. CoDel) is
applied; while if there is a flow of ECT(1) packets in the queue,
the shallower (typically sub-millisecond) threshold is applied.
In addition, ECT(0) and not-ECT packets could potentially be
classified into a separate flow-queue from ECT(1) and CE packets
to avoid them mixing if they share a common flow-identifier (e.g.
in a VPN).
c. It should 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
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flow-rates (perhaps in a similar way to Approx Fair CoDel [AFCD],
[I-D.morton-tsvwg-codel-approx-fair], but with two queues not
one).
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.
4.3. Host Mechanisms
The L4S architecture includes two main mechanisms in the end host
that we enumerate next:
a. Scalable Congestion Control at the sender: 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 [I-D.briscoe-iccrg-prague-congestion-control] has been
implemented in Linux as a reference implementation to address
these requirements [PragueLinux].
Transport protocols other than TCP use various congestion
controls that are designed to be friendly with Reno. Before they
can use the L4S service, they will 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 more recent transport protocols,
e.g. QUIC, and the L4S ECN part of BBRv2 [BBRv2] 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 [SCReAM] for media
transported over RTP.
b. The ECN feedback in some transport protocols is already
sufficiently fine-grained for L4S (specifically DCCP [RFC4340]
and QUIC [RFC9000]). But others either require update or are in
the process of being updated:
* 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
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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.
* For RTP, sufficient ECN feedback was defined in [RFC6679], but
[RFC8888] 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. In contrast,
Classic AQMs have to introduce very high packet drop at high
load to keep the queue short. By using ECN, an L4S congestion
control's sawtooth reduction can be smaller and therefore
return to the operating point more often, without worrying that
more sawteeth will cause more signals. The consequent smaller
amplitude sawteeth fit between an empty queue and a very
shallow marking threshold (~1 ms in the public Internet), so
queue delay variation can be very low, without risk of under-
utilization.
* Explicit congestion signals can be emitted immediately to track
fluctuations of the queue. L4S shifts smoothing from the
network to the host. The network doesn't know the round trip
times of all the flows. So if the network is responsible for
smoothing (as in the Classic approach), it has to assume a
worst case RTT, otherwise long RTT flows would become unstable.
This delays Classic congestion signals by 100-200 ms. In
contrast, each host knows its own round trip time. So, in the
L4S approach, the host can smooth each flow over its own RTT,
introducing no more soothing delay than strictly necessary
(usually only a few milliseconds). A host can also choose not
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to introduce any smoothing delay if appropriate, e.g. during
flow start-up.
Neither of the above are feasible if explicit congestion
signalling has to be considered 'equivalent to drop' (as was
required with Classic ECN [RFC3168]), because drop is an
impairment as well as a signal. So drop cannot be excessively
frequent, and drop cannot be immediate, otherwise too many drops
would turn out to have been due to only a transient fluctuation in
the queue that would not have warranted dropping a packet in
hindsight. Therefore, in an L4S AQM, the L4S queue uses a new L4S
variant of ECN that is not equivalent to drop (see section 5.2 of
[I-D.ietf-tsvwg-ecn-l4s-id]), while the Classic queue uses either
Classic ECN [RFC3168] or drop, which are equivalent to each other.
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 '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
whatever the flow rate, so that queue delay variations can be
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small when conditions are 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 in 1988 that it would not scale to high
bandwidth-delay products (see footnote 6 in [TCP-CA]). Today,
regular broadband flow 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, we will consider a scenario with a maximum RTT of
30 ms at the peak of each sawtooth. As Reno packet rate scales 8x
from 1,250 to 10,000 packet/s (from 15 to 120 Mb/s with 1500 B
packets), the time to recover from a congestion event rises
proportionately by 8x as well, from 422 ms to 3.38 s. It is
clearly problematic for a congestion control to take multiple
seconds to recover from each congestion event. Cubic [RFC8312]
was developed to be less unscalable, but it is approaching its
scaling limit; with the same max RTT of 30 ms, at 120 Mb/s the
Linux implementation of Cubic is still in its Reno-friendly mode,
so it takes about 2.3 s to recover. However, once the flow rate
scales by 8x again to 960 Mb/s it enters true Cubic mode, with a
recovery time of 10.6 s. From then on, each further scaling by 8x
doubles Cubic's recovery time (because the cube root of 8 is 2),
e.g. at 7.68 Gb/s the recovery time is 21.3 s. In contrast a
scalable congestion control like DCTCP or TCP Prague induces 2
congestion signals per round trip on average, which remains
invariant for any flow rate, keeping dynamic control very tight.
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
developments.
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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
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
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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 very 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.
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 very 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].
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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.
Note:
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
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 [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
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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:
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
locally.
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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
processes.
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:
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)
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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
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,
specifically:
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
capacity;
o Cellular networks are further complicated by a perceived need to
buffer in order to make hand-overs imperceptible;
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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
part.
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.
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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.)
______
( )
__ __ ( )
|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 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
core).
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.
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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 4.3 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 (see
section 5.4 of [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.
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+-+--------------------+----------------------+---------------------+
| | Servers or proxies | Access link | Clients |
+-+--------------------+----------------------+---------------------+
|0| DCTCP (existing) | | DCTCP (existing) |
+-+--------------------+----------------------+---------------------+
|1| |Add L4S AQM downstream| |
| | WORKS DOWNSTREAM FOR CONTROLLED DEPLOYMENTS/TRIALS |
+-+--------------------+----------------------+---------------------+
|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
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' [I-D.briscoe-iccrg-prague-congestion-control] 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
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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]).
Unlike TCP, from the outset, QUIC ECN feedback [RFC9000] 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
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, RTP; a body such as the 3GPP might require L4S
to be implemented in 5G user equipment, or other random acts of
kindness.
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
[I-D.ietf-tsvwg-ecn-l4s-id]).
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
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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
applicability.
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
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],
[I-D.ietf-tsvwg-rfc6040update-shim],
[I-D.ietf-tsvwg-ecn-encap-guidelines].
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
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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
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 section
5.4 of [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.
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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.
If needed, various arrangements could be used to address this
concern:
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
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
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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.
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
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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
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.
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Thus, the L4S architecture enables very 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
privacy.
9. Acknowledgements
Thanks to Richard Scheffenegger, Wes Eddy, Karen Nielsen, David
Black, Jake Holland and Vidhi Goel 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. 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.
[BBRv2] Cardwell, N., "TCP BBR v2 Alpha/Preview Release", github
repository; Linux congestion control module,
<https://github.com/google/bbr/blob/v2alpha/README.md>.
[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,
<http://riteproject.eu/publications/>.
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[DOCSIS3.1]
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-
search.cablelabs.com/CM-SP-MULPIv3.1>.
[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,
<https://www.netdevconf.org/0x13/session.html?talk-
DUALPI2-AQM>.
[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", draft-briscoe-conex-policing-01
(work in progress), February 2014.
[I-D.briscoe-docsis-q-protection]
Briscoe, B. and G. White, "Queue Protection to Preserve
Low Latency", draft-briscoe-docsis-q-protection-00 (work
in progress), July 2019.
[I-D.briscoe-iccrg-prague-congestion-control]
Schepper, K. D., Tilmans, O., and B. Briscoe, "Prague
Congestion Control", draft-briscoe-iccrg-prague-
congestion-control-00 (work in progress), March 2021.
[I-D.briscoe-tsvwg-l4s-diffserv]
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.
[I-D.cardwell-iccrg-bbr-congestion-control]
Cardwell, N., Cheng, Y., Yeganeh, S. H., and V. Jacobson,
"BBR Congestion Control", draft-cardwell-iccrg-bbr-
congestion-control-00 (work in progress), July 2017.
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[I-D.ietf-tcpm-accurate-ecn]
Briscoe, B., Kuehlewind, M., and R. Scheffenegger, "More
Accurate ECN Feedback in TCP", draft-ietf-tcpm-accurate-
ecn-14 (work in progress), February 2021.
[I-D.ietf-tcpm-generalized-ecn]
Bagnulo, M. and B. Briscoe, "ECN++: Adding Explicit
Congestion Notification (ECN) to TCP Control Packets",
draft-ietf-tcpm-generalized-ecn-07 (work in progress),
February 2021.
[I-D.ietf-tsvwg-aqm-dualq-coupled]
Schepper, K. D., Briscoe, B., and G. White, "DualQ Coupled
AQMs for Low Latency, Low Loss and Scalable Throughput
(L4S)", draft-ietf-tsvwg-aqm-dualq-coupled-14 (work in
progress), March 2021.
[I-D.ietf-tsvwg-ecn-encap-guidelines]
Briscoe, B. and J. Kaippallimalil, "Guidelines for Adding
Congestion Notification to Protocols that Encapsulate IP",
draft-ietf-tsvwg-ecn-encap-guidelines-15 (work in
progress), March 2021.
[I-D.ietf-tsvwg-ecn-l4s-id]
Schepper, K. D. and B. Briscoe, "Explicit Congestion
Notification (ECN) Protocol for Ultra-Low Queuing Delay
(L4S)", draft-ietf-tsvwg-ecn-l4s-id-14 (work in progress),
March 2021.
[I-D.ietf-tsvwg-nqb]
White, G. and T. Fossati, "A Non-Queue-Building Per-Hop
Behavior (NQB PHB) for Differentiated Services", draft-
ietf-tsvwg-nqb-05 (work in progress), March 2021.
[I-D.ietf-tsvwg-rfc6040update-shim]
Briscoe, B., "Propagating Explicit Congestion Notification
Across IP Tunnel Headers Separated by a Shim", draft-ietf-
tsvwg-rfc6040update-shim-13 (work in progress), March
2021.
[I-D.morton-tsvwg-codel-approx-fair]
Morton, J. and P. G. Heist, "Controlled Delay Approximate
Fairness AQM", draft-morton-tsvwg-codel-approx-fair-01
(work in progress), March 2020.
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[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", draft-sridharan-tcpm-ctcp-02
(work in progress), November 2008.
[I-D.stewart-tsvwg-sctpecn]
Stewart, R. R., Tuexen, M., and X. Dong, "ECN for Stream
Control Transmission Protocol (SCTP)", draft-stewart-
tsvwg-sctpecn-05 (work in progress), January 2014.
[L4Sdemo16]
Bondarenko, O., De Schepper, K., Tsang, I., and B.
Briscoe, "Ultra-Low Delay for All: Live Experience, Live
Analysis", Proc. MMSYS'16 pp33:1--33:4, May 2016,
<http://dl.acm.org/citation.cfm?doid=2910017.2910633
(videos of demos:
https://riteproject.eu/dctth/#1511dispatchwg )>.
[LEDBAT_AQM]
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, <https://ieeexplore.ieee.org/document/8109367>.
[Mathis09]
Mathis, M., "Relentless Congestion Control", PFLDNeT'09 ,
May 2009, <https://www.gdt.id.au/~gdt/
presentations/2010-07-06-questnet-tcp/reference-
materials/papers/mathis-relentless-congestion-
control.pdf>.
[McIlroy78]
McIlroy, M., Pinson, E., and B. Tague, "UNIX Time-Sharing
System: Foreword", The Bell System Technical Journal
57:6(1902--1903), July 1978,
<https://archive.org/details/bstj57-6-1899>.
[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.
[NewCC_Proc]
Eggert, L., "Experimental Specification of New Congestion
Control Algorithms", IETF Operational Note ion-tsv-alt-cc,
July 2007.
Briscoe, et al. Expires January 2, 2022 [Page 34]
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[PragueLinux]
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, <https://www.netdevconf.org/0x13/
session.html?talk-tcp-prague-l4s>.
[QDyn] Briscoe, B., "Rapid Signalling of Queue Dynamics",
bobbriscoe.net Technical Report TR-BB-2017-001;
arXiv:1904.07044 [cs.NI], September 2017,
<https://arxiv.org/abs/1904.07044>.
[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,
<https://www.rfc-editor.org/info/rfc2475>.
[RFC2697] Heinanen, J. and R. Guerin, "A Single Rate Three Color
Marker", RFC 2697, DOI 10.17487/RFC2697, September 1999,
<https://www.rfc-editor.org/info/rfc2697>.
[RFC2698] Heinanen, J. and R. Guerin, "A Two Rate Three Color
Marker", RFC 2698, DOI 10.17487/RFC2698, September 1999,
<https://www.rfc-editor.org/info/rfc2698>.
[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,
<https://www.rfc-editor.org/info/rfc2884>.
[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,
<https://www.rfc-editor.org/info/rfc3168>.
[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,
<https://www.rfc-editor.org/info/rfc3246>.
[RFC3540] Spring, N., Wetherall, D., and D. Ely, "Robust Explicit
Congestion Notification (ECN) Signaling with Nonces",
RFC 3540, DOI 10.17487/RFC3540, June 2003,
<https://www.rfc-editor.org/info/rfc3540>.
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[RFC3649] Floyd, S., "HighSpeed TCP for Large Congestion Windows",
RFC 3649, DOI 10.17487/RFC3649, December 2003,
<https://www.rfc-editor.org/info/rfc3649>.
[RFC4340] Kohler, E., Handley, M., and S. Floyd, "Datagram
Congestion Control Protocol (DCCP)", RFC 4340,
DOI 10.17487/RFC4340, March 2006,
<https://www.rfc-editor.org/info/rfc4340>.
[RFC4774] Floyd, S., "Specifying Alternate Semantics for the
Explicit Congestion Notification (ECN) Field", BCP 124,
RFC 4774, DOI 10.17487/RFC4774, November 2006,
<https://www.rfc-editor.org/info/rfc4774>.
[RFC4960] Stewart, R., Ed., "Stream Control Transmission Protocol",
RFC 4960, DOI 10.17487/RFC4960, September 2007,
<https://www.rfc-editor.org/info/rfc4960>.
[RFC5033] Floyd, S. and M. Allman, "Specifying New Congestion
Control Algorithms", BCP 133, RFC 5033,
DOI 10.17487/RFC5033, August 2007,
<https://www.rfc-editor.org/info/rfc5033>.
[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,
<https://www.rfc-editor.org/info/rfc5348>.
[RFC5681] Allman, M., Paxson, V., and E. Blanton, "TCP Congestion
Control", RFC 5681, DOI 10.17487/RFC5681, September 2009,
<https://www.rfc-editor.org/info/rfc5681>.
[RFC5925] Touch, J., Mankin, A., and R. Bonica, "The TCP
Authentication Option", RFC 5925, DOI 10.17487/RFC5925,
June 2010, <https://www.rfc-editor.org/info/rfc5925>.
[RFC6040] Briscoe, B., "Tunnelling of Explicit Congestion
Notification", RFC 6040, DOI 10.17487/RFC6040, November
2010, <https://www.rfc-editor.org/info/rfc6040>.
[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, <https://www.rfc-editor.org/info/rfc6679>.
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[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,
<https://www.rfc-editor.org/info/rfc6973>.
[RFC7540] Belshe, M., Peon, R., and M. Thomson, Ed., "Hypertext
Transfer Protocol Version 2 (HTTP/2)", RFC 7540,
DOI 10.17487/RFC7540, May 2015,
<https://www.rfc-editor.org/info/rfc7540>.
[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,
<https://www.rfc-editor.org/info/rfc7560>.
[RFC7665] Halpern, J., Ed. and C. Pignataro, Ed., "Service Function
Chaining (SFC) Architecture", RFC 7665,
DOI 10.17487/RFC7665, October 2015,
<https://www.rfc-editor.org/info/rfc7665>.
[RFC7713] Mathis, M. and B. Briscoe, "Congestion Exposure (ConEx)
Concepts, Abstract Mechanism, and Requirements", RFC 7713,
DOI 10.17487/RFC7713, December 2015,
<https://www.rfc-editor.org/info/rfc7713>.
[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,
<https://www.rfc-editor.org/info/rfc8033>.
[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, <https://www.rfc-editor.org/info/rfc8034>.
[RFC8170] Thaler, D., Ed., "Planning for Protocol Adoption and
Subsequent Transitions", RFC 8170, DOI 10.17487/RFC8170,
May 2017, <https://www.rfc-editor.org/info/rfc8170>.
[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, <https://www.rfc-editor.org/info/rfc8257>.
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[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,
<https://www.rfc-editor.org/info/rfc8290>.
[RFC8298] Johansson, I. and Z. Sarker, "Self-Clocked Rate Adaptation
for Multimedia", RFC 8298, DOI 10.17487/RFC8298, December
2017, <https://www.rfc-editor.org/info/rfc8298>.
[RFC8311] Black, D., "Relaxing Restrictions on Explicit Congestion
Notification (ECN) Experimentation", RFC 8311,
DOI 10.17487/RFC8311, January 2018,
<https://www.rfc-editor.org/info/rfc8311>.
[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,
<https://www.rfc-editor.org/info/rfc8312>.
[RFC8404] Moriarty, K., Ed. and A. Morton, Ed., "Effects of
Pervasive Encryption on Operators", RFC 8404,
DOI 10.17487/RFC8404, July 2018,
<https://www.rfc-editor.org/info/rfc8404>.
[RFC8511] Khademi, N., Welzl, M., Armitage, G., and G. Fairhurst,
"TCP Alternative Backoff with ECN (ABE)", RFC 8511,
DOI 10.17487/RFC8511, December 2018,
<https://www.rfc-editor.org/info/rfc8511>.
[RFC8888] Sarker, Z., Perkins, C., Singh, V., and M. Ramalho, "RTP
Control Protocol (RTCP) Feedback for Congestion Control",
RFC 8888, DOI 10.17487/RFC8888, January 2021,
<https://www.rfc-editor.org/info/rfc8888>.
[RFC9000] Iyengar, J., Ed. and M. Thomson, Ed., "QUIC: A UDP-Based
Multiplexed and Secure Transport", RFC 9000,
DOI 10.17487/RFC9000, May 2021,
<https://www.rfc-editor.org/info/rfc9000>.
[SCReAM] Johansson, I., "SCReAM", github repository; ,
<https://github.com/EricssonResearch/scream/blob/master/
README.md>.
[TCP-CA] Jacobson, V. and M. Karels, "Congestion Avoidance and
Control", Laurence Berkeley Labs Technical Report ,
November 1988, <http://ee.lbl.gov/papers/congavoid.pdf>.
Briscoe, et al. Expires January 2, 2022 [Page 38]
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[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,
<http://www.bobbriscoe.net/projects/latency/sub-mss-
w.pdf>.
[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:
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);
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.
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+-----+------------------------+------------------------------------+
| Req | Requirement | Reference |
| # | | |
+-----+------------------------+------------------------------------+
| 0 | ARCHITECTURE | |
| 1 | L4S IDENTIFIER | [I-D.ietf-tsvwg-ecn-l4s-id] S.3 |
| 2 | DUAL QUEUE AQM | [I-D.ietf-tsvwg-aqm-dualq-coupled] |
| 3 | Suitable ECN Feedback | [I-D.ietf-tcpm-accurate-ecn] |
| | | S.4.2, |
| | | [I-D.stewart-tsvwg-sctpecn]. |
| | | |
| | SCALABLE TRANSPORT - | |
| | SAFETY ADDITIONS | |
| 4-1 | Fall back to | [I-D.ietf-tsvwg-ecn-l4s-id] S.4.3, |
| | Reno/Cubic on loss | [RFC8257] |
| 4-2 | Fall back to | [I-D.ietf-tsvwg-ecn-l4s-id] S.4.3 |
| | Reno/Cubic if classic | |
| | ECN bottleneck | |
| | detected | |
| | | |
| 4-3 | Reduce RTT-dependence | [I-D.ietf-tsvwg-ecn-l4s-id] S.4.3 |
| | | |
| 4-4 | Scaling TCP's | [I-D.ietf-tsvwg-ecn-l4s-id] S.4.3, |
| | 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)
Independent
UK
Email: ietf@bobbriscoe.net
URI: http://bobbriscoe.net/
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Koen De Schepper
Nokia Bell Labs
Antwerp
Belgium
Email: koen.de_schepper@nokia.com
URI: https://www.bell-labs.com/usr/koen.de_schepper
Marcelo Bagnulo
Universidad Carlos III de Madrid
Av. Universidad 30
Leganes, Madrid 28911
Spain
Phone: 34 91 6249500
Email: marcelo@it.uc3m.es
URI: http://www.it.uc3m.es
Greg White
CableLabs
US
Email: G.White@CableLabs.com
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