Internet DRAFT - draft-ietf-tsvwg-l4s-arch
draft-ietf-tsvwg-l4s-arch
Transport Area Working Group B. Briscoe, Ed.
Internet-Draft Independent
Intended status: Informational K. De Schepper
Expires: 2 March 2023 Nokia Bell Labs
M. Bagnulo Braun
Universidad Carlos III de Madrid
G. White
CableLabs
29 August 2022
Low Latency, Low Loss, Scalable Throughput (L4S) Internet Service:
Architecture
draft-ietf-tsvwg-l4s-arch-20
Abstract
This document describes the L4S architecture, which enables Internet
applications to achieve Low queuing Latency, Low Loss, and Scalable
throughput (L4S). L4S is based on the insight that the root cause of
queuing delay is in the capacity-seeking congestion controllers of
senders, not in the queue itself. With the L4S architecture all
Internet applications could (but do not have to) transition away from
congestion control algorithms that cause substantial queuing delay,
to a new class of congestion controls that can seek capacity with
very little queuing. These are aided by a modified form of explicit
congestion notification (ECN) from the network. With this new
architecture, applications can have both low latency and high
throughput.
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. The aim is for L4S latency and throughput to be usually
much better (and rarely worse), while typically not impacting Classic
performance.
Status of This Memo
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Document Roadmap . . . . . . . . . . . . . . . . . . . . 5
2. L4S Architecture Overview . . . . . . . . . . . . . . . . . . 5
3. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 7
4. L4S Architecture Components . . . . . . . . . . . . . . . . . 9
4.1. Protocol Mechanisms . . . . . . . . . . . . . . . . . . . 9
4.2. Network Components . . . . . . . . . . . . . . . . . . . 10
4.3. Host Mechanisms . . . . . . . . . . . . . . . . . . . . . 13
5. Rationale . . . . . . . . . . . . . . . . . . . . . . . . . . 15
5.1. Why These Primary Components? . . . . . . . . . . . . . . 15
5.2. What L4S adds to Existing Approaches . . . . . . . . . . 18
6. Applicability . . . . . . . . . . . . . . . . . . . . . . . . 21
6.1. Applications . . . . . . . . . . . . . . . . . . . . . . 21
6.2. Use Cases . . . . . . . . . . . . . . . . . . . . . . . . 22
6.3. Applicability with Specific Link Technologies . . . . . . 24
6.4. Deployment Considerations . . . . . . . . . . . . . . . . 25
6.4.1. Deployment Topology . . . . . . . . . . . . . . . . . 25
6.4.2. Deployment Sequences . . . . . . . . . . . . . . . . 26
6.4.3. L4S Flow but Non-ECN Bottleneck . . . . . . . . . . . 29
6.4.4. L4S Flow but Classic ECN Bottleneck . . . . . . . . . 30
6.4.5. L4S AQM Deployment within Tunnels . . . . . . . . . . 30
7. IANA Considerations (to be removed by RFC Editor) . . . . . . 30
8. Security Considerations . . . . . . . . . . . . . . . . . . . 31
8.1. Traffic Rate (Non-)Policing . . . . . . . . . . . . . . . 31
8.1.1. (Non-)Policing Rate per Flow . . . . . . . . . . . . 31
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8.1.2. (Non-)Policing L4S Service Rate . . . . . . . . . . . 31
8.2. 'Latency Friendliness' . . . . . . . . . . . . . . . . . 32
8.3. Interaction between Rate Policing and L4S . . . . . . . . 34
8.4. ECN Integrity . . . . . . . . . . . . . . . . . . . . . . 35
8.5. Privacy Considerations . . . . . . . . . . . . . . . . . 35
9. Informative References . . . . . . . . . . . . . . . . . . . 36
Acknowledgements . . . . . . . . . . . . . . . . . . . . . . . . 45
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 45
1. Introduction
At any one time, it is increasingly common for all of the traffic in
a bottleneck link (e.g. a household's Internet access) to come from
applications that prefer 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 not uncommon, even with state-of-the-art active
queue management (AQM) [COBALT], [DOCSIS3AQM]. Queuing in access
network bottlenecks is typically configured to cause overall network
delay to roughly double during a long-running flow, relative to
expected base (unloaded) path delay [BufferSize]. 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 link capacity
offers diminishing returns if latency (delay) is not addressed
[Dukkipati06], [Rajiullah15]. 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. End-to-end delay above 50 ms [Raaen14] or even above
20 ms [NASA04] starts to feel unnatural for more demanding
interactive applications. So removing unnecessary delay variability
increases the reach of these applications (the distance over which
they are comfortable to use). This document describes the L4S
architecture for achieving these goals.
Differentiated services (Diffserv) offers Expedited Forwarding
(EF [RFC3246]) for some packets at the expense of others, but this
makes no difference when all (or most) of the traffic at a bottleneck
at any one time requires low latency. In contrast, L4S still works
well when all traffic is L4S - a service that gives without taking
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needs none of the configuration or management baggage (traffic
policing, traffic contracts) associated with favouring some traffic
flows over others.
Queuing delay degrades performance intermittently [Hohlfeld14]. It
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 congestion
control (Reno [RFC5681]) or compatible variants
(e.g. CUBIC [RFC8312]) that are used in TCP and in other transports
such as QUIC [RFC9000]. 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], [DCttH19] (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].
L4S is designed for incremental deployment. It is possible to deploy
the L4S service at a bottleneck link alongside the existing best
efforts service [DualPI2Linux] so that unmodified applications can
start using it as soon as the sender's stack is updated. Access
networks are typically designed with one link as the bottleneck for
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each site (which might be a home, small enterprise or mobile device),
so deployment at either or both ends of this link should give nearly
all the benefit in the respective direction. With some transport
protocols, namely TCP and SCTP, the sender has to check that the
receiver has been suitably updated to give more accurate feedback,
whereas with more recent transport protocols such as QUIC and DCCP,
all receivers have always been suitable.
This document presents the L4S architecture. It 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. The
protocol is defined separately [I-D.ietf-tsvwg-ecn-l4s-id] as an
experimental change to Explicit Congestion Notification (ECN). This
document describes and justifies the component parts and how they
interact to provide the scalable, low latency, low loss Internet
service. It also details the approach to incremental deployment, as
briefly summarized above.
1.1. Document Roadmap
This document describes the L4S architecture in three passes. First
this brief overview gives the very high level idea and states the
main components with minimal rationale. This is only intended to
give some context for the terminology definitions that follow in
Section 3, and to explain the structure of the rest of the document.
Then Section 4 goes into more detail on each component with some
rationale, but still mostly stating what the architecture is, rather
than why. Finally, Section 5 justifies why each element of the
solution was chosen (Section 5.1) and why these choices were
different from other solutions (Section 5.2).
Having described the architecture, Section 6 clarifies its
applicability; that is, the applications and use-cases that motivated
the design, the challenges applying the architecture to various link
technologies, and various incremental deployment models: including
the two main deployment topologies, different sequences for
incremental deployment and various interactions with pre-existing
approaches. The document ends with the usual tailpieces, including
extensive discussion of traffic policing and other security
considerations in Section 8.
2. L4S Architecture Overview
Below we outline the three main components to the L4S architecture;
1) the scalable congestion control on the sending host; 2) the AQM at
the network bottleneck; and 3) the protocol between them.
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But first, the main point to grasp is that low latency is not
provided by the network - low latency results from the careful
behaviour of the scalable congestion controllers used by L4S senders.
The network does have a role - primarily to isolate the low latency
of the carefully behaving L4S traffic from the higher queuing delay
needed by traffic with pre-existing Classic behaviour. The network
also alters the way it signals queue growth to the transport - It
uses the Explicit Congestion Notification (ECN) protocol, but it
signals the very start of queue growth - immediately without the
smoothing delay typical of Classic AQMs. Because ECN support is
essential for L4S, senders use the ECN field as the protocol that
allows the network to identify which packets are L4S and which are
Classic.
1) Host: Scalable congestion controls already exist. They solve the
scaling problem with Classic congestion controls, such as Reno or
Cubic. Because flow rate has scaled since TCP congestion control
was first designed in 1988, assuming the flow lasts long enough,
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.
With a scalable congestion control, 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. The scalable control
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 functions well over wide-area round trip
times, most implementations lack certain safety features that
would be necessary for use outside controlled environments like
data centres (see Section 6.4.3). So scalable congestion control
needs to be implemented in TCP and other transport protocols
(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 [SCReAM] and the L4S ECN part of BBRv2 [BBRv2] intended
for TCP and QUIC transports.
2) Network: L4S traffic needs to be isolated from the queuing
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latency of Classic traffic. One queue per application flow (FQ)
is one way to achieve this, e.g. FQ-CoDel [RFC8290]. However,
using 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 the per-flow-queue
(FQ) and DualQ variants of L4S work, and
[I-D.ietf-tsvwg-aqm-dualq-coupled] gives a full explanation of the
DualQ Coupled AQM framework. A specific marking algorithm is not
mandated for L4S AQMs. Appendices of
[I-D.ietf-tsvwg-aqm-dualq-coupled] give non-normative examples
that have been implemented and evaluated, and give recommended
default parameter settings. It is expected that L4S experiments
will improve knowledge of parameter settings and whether the set
of marking algorithms needs to be limited.
3) Protocol: A sending host needs to distinguish L4S and Classic
packets with an identifier so that the network can classify them
into their separate treatments. The L4S identifier
spec. [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. As already explained, the
network also uses ECN to immediately signal the very start of
queue growth to the transport.
3. Terminology
[Note to the RFC Editor (to be removed before publication as an RFC):
The following definitions are copied from the L4S ECN
spec [I-D.ietf-tsvwg-ecn-l4s-id] for the reader's convenience.
Except, here, Classic CC and Scalable CC are condensed because they
refer to Section 5.1 later. Also the definition of Traffic Policing
is not needed in [I-D.ietf-tsvwg-ecn-l4s-id].]
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]. The
scaling problem with Classic congestion control is explained, with
examples, in Section 5.1 and in [RFC3649].
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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. 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],
[I-D.cardwell-iccrg-bbr-congestion-control] 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 Prague -- it allows the set of
congestion controls with similar scaling properties to Prague to
evolve, such 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 to 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].
The TFRC spec. [RFC5348] indirectly implies that 'friendly' is
defined as "generally within a factor of two of the sending rate
of a TCP flow under the same conditions". Reno-friendly is used
here 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 [RFC9000].
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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.
L4S uses the ECN field as an
identifier [I-D.ietf-tsvwg-ecn-l4s-id] with the names for the four
codepoints of the 2-bit IP-ECN field unchanged from those defined
in the ECN spec [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.
Traffic policing: Limiting traffic by dropping packets or shifting
them to lower service class (as opposed to introducing delay,
which is termed traffic shaping). Policing can involve limiting
average rate and/or burst size. Policing focused on limiting
queuing but not average flow rate is termed congestion policing,
latency policing, burst policing or queue protection in this
document. Otherwise, the term rate policing is used.
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 the previous use of
the identifier; b) reassignment of the same identifier; and c)
optional further identifiers:
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;
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* can be signalled immediately, without the significant delay
required to smooth out fluctuations in the queue.
To enable L4S, the standards track Classic ECN spec. [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. Also, the ECT(1)
codepoint was previously assigned as the experimental ECN
nonce [RFC3540], which RFC 8311 recategorizes as historic to make
the codepoint available again.
b. [I-D.ietf-tsvwg-ecn-l4s-id] specifies that ECT(1) is used as the
identifier to classify L4S packets into a separate treatment from
Classic packets. This satisfies the requirement 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 the L4S ECN
spec [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.
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. The following
bullets describe the known arrangements: a) the DualQ Coupled AQM
with an L4S AQM in one queue coupled from a Classic AQM in the other;
b) Per-Flow Queues with an instance of a Classic and an L4S AQM in
each queue; c) Dual queues with per-flow AQMs, but no per-flow
queues:
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a. The Dual Queue Coupled AQM (illustrated in Figure 1) achieves the
'semi-permeable' membrane property mentioned earlier as follows:
* Latency isolation: Two separate queues are used to isolate L4S
queuing delay from the larger queue that Classic traffic needs
to maintain full utilization.
* Bandwidth pooling: The two queues act as if they are a single
pool of bandwidth in which flows of either type get roughly
equal throughput without the scheduler needing to identify any
flows. This is achieved by having an AQM in each queue, but
the Classic AQM provides a congestion signal to both queues in
a manner that ensures a consistent response from the two
classes of congestion control. Specifically, the Classic AQM
generates a drop/mark probability based on congestion in its
own queue, which it uses both to drop/mark packets in its own
queue and to affect the marking probability in the L4S queue.
The strength of the coupling of the congestion signalling
between the two queues is enough to make the L4S flows slow
down to leave the right amount of capacity for the Classic
flows (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 (denoted
by the '1' on the higher priority input), because the L4S traffic
isn't offering up enough traffic to use all the priority that it
is given. Therefore:
* for latency isolation on short time-scales (sub-round-trip)
the prioritization of the L4S queue protects its low latency
by allowing bursts to dissipate quickly;
* but for bandwidth pooling 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 taking advantage of the
prioritization of the L4S queue and starving the Classic queue,
it is advisable for the priority to be conditional, not strict
(see Appendix A of the DualQ
spec [I-D.ietf-tsvwg-aqm-dualq-coupled]).
When there is no Classic traffic, the L4S queue's own AQM comes
into play. It starts congestion marking with a very shallow
queue, so L4S traffic maintains very low queuing delay.
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If either queue becomes persistently overloaded, drop of ECN-
capable packets is introduced, as recommended in Section 7 of the
ECN spec [RFC3168] and Section 4.2.1 of the AQM
recommendations [RFC7567]. Then both queues introduce the same
level of drop (not shown in the figure).
The Dual Queue Coupled AQM has been specified as generically as
possible [I-D.ietf-tsvwg-aqm-dualq-coupled] without specifying
the particular AQMs to use in the two queues so that designers
are free to implement diverse ideas. Informational appendices in
that draft give pseudocode examples of two different specific AQM
approaches: one called DualPI2 (pronounced Dual PI
Squared) [DualPI2Linux] that uses the PI2 variant of PIE, and a
zero-config variant of RED called Curvy RED. A DualQ Coupled AQM
based on PIE has also been specified and implemented for Low
Latency DOCSIS [DOCSIS3.1].
(3) (2)
.-------^------..------------^------------------.
,-(1)-----. _____
; ________ : L4S -------. | |
:|Scalable| : _\ ||__\_|mark |
:| sender | : __________ / / || / |_____|\ _________
:|________|\; | |/ -------' ^ \1|condit'nl|
`---------'\_| IP-ECN | Coupling : \|priority |_\
________ / |Classifier| : /|scheduler| /
|Classic |/ |__________|\ -------. __:__ / |_________|
| sender | \_\ || | ||__\_|mark/|/
|________| / || | || / |drop |
Classic -------' |_____|
Figure 1: Components of an L4S DualQ Coupled AQM Solution: 1)
Scalable Sending Host; 2) Isolation in separate network
queues; and 3) Packet Identification Protocol
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b. Per-Flow Queues and AQMs: 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 the option of ECN marking at an immediate
(unsmoothed) shallow threshold to support use in data centres
(see Sec.5.2.7 of the FQ-CoDel spec [RFC8290]). In Linux, this
has been modified so that the shallow threshold can be solely
applied to ECT(1) packets [FQ_CoDel_Thresh]. 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. Dual-queues, but per-flow AQMs: 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 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: Section 2 defines a
scalable congestion control as one 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.
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
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[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],
[I-D.cardwell-iccrg-bbr-congestion-control] is a scalable
congestion control intended for the TCP and QUIC transports,
amongst others. Also, an L4S variant of the RMCAT SCReAM
controller [RFC8298] has been implemented [SCReAM] for media
transported over RTP.
Section 4.3 of the L4S ECN spec [I-D.ietf-tsvwg-ecn-l4s-id]
defines scalable congestion control in more detail, and specifies
the requirements that an L4S scalable congestion control has to
comply with.
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
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 was only roughly sketched in an appendix of the
now obsoleted second specification of SCTP [RFC4960], while a
fuller specification was proposed in a long-expired
draft [I-D.stewart-tsvwg-sctpecn]. A new design would need to
be implemented and deployed before SCTP could support L4S.
* For RTP, sufficient ECN feedback was defined in [RFC6679], but
[RFC8888] defines the latest standards track improvements.
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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 that
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 any of 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 smoothing delay than strictly necessary
(usually only a few milliseconds). A host can also choose not
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
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the L4S ECN spec [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
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
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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 Cubic
is still fully in its Reno-friendly mode, so it takes about 4.3 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
12.2 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 24.3 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.
For a feel of where the global average lone-flow download sits on
this scale at the time of writing (2021), according to [BDPdata]
globally averaged fixed access capacity was 103 Mb/s in 2020 and
averaged base RTT to a CDN was 25-34ms in 2019. Averaging of per-
country data was weighted by Internet user population (data
collected globally is necessarily of variable quality, but the
paper does double-check that the outcome compares well against a
second source). So a lone CUBIC flow would at best take about 200
round trips (5 s) to recover from each of its sawtooth reductions,
if the flow even lasted that long. This is described as 'at best'
because it assumes everyone uses an AQM, whereas in reality most
users still have a (probably bloated) tail-drop buffer. In the
tail-drop case, likely average recovery time would be at least 4x
5 s, if not more, because RTT under load would be at least double
that of an AQM, and recovery time depends on the square of RTT.
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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.
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 can only provide a latency benefit if a small
subset of the traffic on a bottleneck link requests low latency.
As already explained, it has no effect 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
works for all traffic, it needs none of the management baggage
(traffic policing, traffic contracts) associated with favouring
some packets over others. This lack of management baggage ought
to give L4S a better chance of 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 tend to 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
[RFC8404]. 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.
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State-of-the-art AQMs: AQMs such as PIE and FQ-CoDel give a
significant reduction in queuing delay relative to no AQM at all.
L4S is intended to complement these AQMs, and should not distract
from the need to deploy them as widely as possible. Nonetheless,
AQMs alone cannot reduce queuing delay too far without
significantly reducing link utilization, because the root cause of
the problem is on the host - where Classic congestion controls use
large saw-toothing rate variations. The L4S approach resolves
this tension between delay and utilization by enabling hosts to
minimize the amplitude of their sawteeth. A single-queue Classic
AQM is not sufficient to allow hosts to use small sawteeth for two
reasons: i) smaller sawteeth would not get lower delay in an AQM
designed for larger amplitude Classic sawteeth, because a queue
can only have one length at a time; and ii) much smaller sawteeth
implies much more frequent sawteeth, so L4S flows would drive a
Classic AQM into a high level of ECN-marking, which would appear
as heavy congestion to Classic flows, which in turn would greatly
reduce their rate as a result (see Section 6.4.4).
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 need to have support for
scalable congestion control added, which has already been done for
FQ-CoDel in Linux (see Sec.5.2.7 of [RFC8290] and
[FQ_CoDel_Thresh]). 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, as opposed to DTLS over UDP), 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].
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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
e2e scavenger behaviours [RFC6817] that use less than an equal
share of capacity [LEDBAT_AQM].
The L4S architecture does not require the IETF to commit to
one approach over the other, because it supports both, so that
the 'market' can decide. Nonetheless, in the spirit of 'Do
one thing and do it well' [McIlroy78], the DualQ option
provides low delay without prejudging the issue of flow-rate
control. Then, flow rate policing can be added separately if
desired. This allows application control up to a point, but
the network can still choose to set the point at which it
intervenes to prevent one flow completely starving another.
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 [RFC9113] 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 (for example see [lowat]). 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
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(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. 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 can use L4S ECN where
available and a scalable L4S congestion control behaviour in
response to any ECN signalling from the path [BBRv2]. The L4S ECN
signal complements the delay based congestion control aspects of
BBR with an explicit indication that hosts can use, both to
converge on a fair rate and to keep below a shallow queue target
set by the network. Without L4S ECN, both these aspects need to
be assumed or estimated.
6. Applicability
6.1. Applications
A transport layer that solves the current latency issues will provide
new service, product and application opportunities.
With the L4S approach, the following existing applications also
experience significantly better quality of experience under load:
* Gaming, including cloud based gaming;
* VoIP;
* Video conferencing;
* Web browsing;
* (Adaptive) video streaming;
* 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:
* Cloud based interactive video;
* Cloud based virtual and augmented reality.
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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). With an alternative AQM, the video noticeably
lagged behind the finger gestures and head movements.
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:
* Interactive remote presence;
* 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:
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* 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)
* 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)
* Different types of transport (or application) congestion control:
- elastic (TCP/SCTP);
- real-time (RTP, RMCAT);
- query (DNS/LDAP).
* 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 can give favourable
queuing to all traffic.
* 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.
* If delay jitter is minimized, it is possible to reduce the
dejitter buffers on the receive end of video streaming, which
should improve the interactive experience
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6.3. Applicability with Specific Link Technologies
Certain link technologies aggregate data from multiple packets into
bursts, and buffer incoming packets while building each burst. Wi-
Fi, 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:
* Radio links (cellular, Wi-Fi, 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;
* Cellular networks are further complicated by a perceived need to
buffer in order to make hand-overs imperceptible;
L4S cannot remove the need for all these different forms of
buffering. However, by removing 'the longest pole in the tent'
(buffering for the large sawteeth of Classic congestion controls),
L4S exposes all these 'shorter poles' to greater scrutiny.
Until now, the buffering needed for these additional reasons tended
to be over-specified - with the excuse that none were 'the longest
pole in the tent'. But having removed the 'longest pole', it becomes
worthwhile to minimize them, for instance reducing packet aggregation
burst sizes and MAC scheduling intervals.
Also certain link types, particularly radio-based links, are far more
prone to transmission losses. Section 6.4.3 explains how an L4S
response to loss has to be as drastic as a Classic response.
Nonetheless, research referred to in the same section has
demonstrated potential for considerably more effective loss repair at
the link layer, due to the relaxed ordering constraints of L4S
packets.
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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 can benefit anyone. Operators of public Internet access networks
typically design their networks so that the bottleneck will nearly
always occur at one known (logical) link. This confines the cost of
queue management technology to one place.
The case of mesh networks is different and will be discussed later in
this section. But the known bottleneck case is generally true for
Internet access to all sorts of different 'sites', where the word
'site' includes home networks, small- to medium-sized campus or
enterprise networks and even cellular devices (Figure 2). Also, this
known-bottleneck case tends to be applicable whatever the access link
technology; whether xDSL, cable, PON, cellular, line of sight
wireless or satellite.
Therefore, the full benefit of the L4S service should be available in
the downstream direction when an L4S AQM is deployed at the ingress
to this bottleneck link. And similarly, the full upstream service
will be available once an L4S AQM is deployed at the ingress into the
upstream link. (Of course, multi-homed sites would only see the full
benefit once all their access links were covered.)
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______
( )
__ __ ( )
|DQ\________/DQ|( enterprise )
___ |__/ \__| ( /campus )
( ) (______)
( ) ___||_
+----+ ( ) __ __ / \
| DC |-----( Core )|DQ\_______________/DQ|| home |
+----+ ( ) |__/ \__||______|
(_____) __
|DQ\__/\ __ ,===.
|__/ \ ____/DQ||| ||mobile
\/ \__|||_||device
| o |
`---'
Figure 2: Likely location of DualQ (DQ) Deployments in common
access topologies
Deployment in mesh topologies depends on how overbooked 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 often next be needed where the Wi-Fi links in a home
sometimes become the bottleneck. And 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 provide benefit, it requires three (or
sometimes two) parts to have been deployed: i) the congestion control
at the sender; ii) the AQM at the bottleneck; and iii) older
transports (namely TCP) need upgraded receiver feedback too. This
was the same deployment problem that ECN faced [RFC8170] so we have
learned from that experience.
Firstly, L4S deployment exploits the fact that DCTCP already exists
on many Internet hosts (Windows, FreeBSD and Linux); both servers and
clients. Therefore, an L4S AQM can be deployed at a network
bottleneck to immediately give a working deployment of all the L4S
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parts for testing, as long as the ECT(0) codepoint is switched to
ECT(1). DCTCP needs some safety concerns to be fixed for general use
over the public Internet (see Section 4.3 of the L4S ECN
spec [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.
+-+--------------------+----------------------+---------------------+
| | 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 |
+-+--------------------+----------------------+---------------------+
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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, preceded by
a presumption that DCTCP is already installed at both ends:
1. DCTCP is not applicable for use over the public Internet, so it
is emphasized here that any DCTCP flow has to be completely
contained within a controlled trial environment.
Within this trial environment, once an L4S AQM has been deployed,
the trial DCTCP flow will experience immediate benefit, without
any other deployment being needed. 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 designed to be used in a
production Internet environment (that is, it has to comply with
all the requirements in Section 4 of the L4S ECN
spec [I-D.ietf-tsvwg-ecn-l4s-id], which then means it can be used
over the public Internet). If the application is primarily
unidirectional, 'TCP Prague' at one end will provide all the
benefit needed.
For TCP transports, Accurate ECN feedback
(AccECN) [I-D.ietf-tcpm-accurate-ecn] is needed at the other end,
but it is a generic ECN feedback facility that is already planned
to be deployed for other purposes, e.g. DCTCP, BBR. The two ends
can be deployed in either order, because, in TCP, an L4S
congestion control only enables itself if it has negotiated the
use of AccECN feedback with the other end during the connection
handshake. Thus, deployment of TCP Prague on a server enables
L4S trials to move to a production service in one direction,
wherever AccECN is deployed at the other end. This stage might
be further motivated by the performance improvements of TCP
Prague relative to DCTCP (see Appendix A.2 of the L4S ECN
spec [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.
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For QUIC, if a proxy sits in the path between multiple origin
servers and the access bottlenecks to multiple clients, then
upgrading the proxy with a Scalable congestion control would
provide the benefits of L4S over all the clients' downstream
bottlenecks in one go --- whether or not all the origin servers
were upgraded. Conversely, where a proxy has not been upgraded,
the clients served by it will not benefit from L4S at all in the
downstream, even when any origin server behind the proxy has been
upgraded to support L4S.
For TCP, a proxy upgraded to support 'TCP Prague' would provide
the benefits of L4S downstream to all clients that support AccECN
(whether or not they support L4S as well). And in the upstream,
the proxy would also support AccECN as a receiver, so that any
client deploying its own L4S support would benefit in the
upstream direction, irrespective of whether any origin server
beyond the proxy supported AccECN.
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
the L4S ECN spec [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.:
* congestion loss at other transient bottlenecks, e.g. due to bursts
in shallower queues;
* transmission errors, e.g. due to electrical interference;
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* rate policing.
Three complementary approaches are in progress to address this issue,
but they are all currently research:
* In Prague congestion control, ignore certain losses deemed
unlikely to be due to congestion (using some ideas from
BBR [I-D.cardwell-iccrg-bbr-congestion-control] regarding isolated
losses). This could mask any of the above types of loss while
still coexisting with drop-based congestion controls.
* 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];
* 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 implementations of FQ-
CoDel and/or FQ-COBALT, which is not generally problematic, because
flow-queue (FQ) scheduling inherently prevents a flow from exceeding
the 'fair' rate 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 the L4S ECN
spec [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.
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8. Security Considerations
8.1. Traffic Rate (Non-)Policing
8.1.1. (Non-)Policing Rate per Flow
In the current Internet, ISPs usually enforce separation between the
capacity of shared links assigned to different 'sites'
(e.g. households, businesses or mobile users - see terminology in
Section 3) using some form of scheduler [RFC0970]. And they use
various techniques like redirection to traffic scrubbing facilities
to deal with flooding attacks. However, there has never been a
universal need to police the rate of individual application flows -
the Internet has generally always relied on self-restraint of
congestion controls at senders for sharing intra-'site' capacity.
L4S has been designed not to upset this status quo. If a DualQ is
used to provide L4S service, section 4.2 of
[I-D.ietf-tsvwg-aqm-dualq-coupled] explains how it is designed to
give no more rate advantage to unresponsive flows than a single-queue
AQM would, whether or not there is traffic overload.
Also, in case per-flow rate policing is ever required, it can be
added because it is orthogonal to the distinction between L4S and
Classic. As explained in Section 5.2, the DualQ variant of L4S
provides low delay without prejudging the issue of flow-rate control.
So, if flow-rate control is needed, per-flow-queuing (FQ) with L4S
support can be used instead, or flow rate policing can be added as a
modular addition to a DualQ. However, per-flow rate control is not
usually deployed as a security mechanism, because an active attacker
can just shard its traffic over more flow IDs if the rate of each is
restricted.
8.1.2. (Non-)Policing L4S Service Rate
Section 5.2 explains how Diffserv only makes a difference if some
packets get less favourable treatment than others, which typically
requires traffic rate policing for a low latency class. In contrast,
it should not be necessary to rate-police access to the L4S service
to protect the Classic service, because L4S is designed to reduce
delay without harming the delay or rate of any Classic traffic.
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 (by both the ECN
spec [RFC3168] and the L4S ECN spec [I-D.ietf-tsvwg-ecn-l4s-id]) not
to change the L4S identifier, which would interfere with end-to-end
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congestion control. If they already treat ECN traffic as Not-ECT,
they can merely treat L4S traffic as Not-ECT too. 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 cases that are expected to be rare, networks that solely support
Classic ECN [RFC3168] in a single queue bottleneck might opt to
police L4S traffic so as to protect competing Classic ECN traffic
(for instance, see Section 6.1.3 of the L4S operational
guidance [I-D.ietf-tsvwg-l4sops]). However, Section 4.3 of the L4S
ECN spec [I-D.ietf-tsvwg-ecn-l4s-id] recommends that the sender
adapts its congestion response to properly coexist with Classic ECN
flows, i.e. reverting to the self-restraint approach.
Certain network operators might choose to restrict access to the L4S
service, 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 classifying on the ECN field. 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 additional
local classifiers (see section 5.4 of the L4S ECN
spec [I-D.ietf-tsvwg-ecn-l4s-id]) is intended to remove any
motivation to clear 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-restraint -
limiting rate in response to congestion. In addition, the L4S
service requires self-restraint 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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Because the L4S service can reduce delay without discernibly
increasing the delay of any Classic traffic, it should not be
necessary to police L4S traffic to protect the delay of Classic.
However, whether burst policing becomes necessary to protect other
L4S traffic 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 intercommunicating 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] 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
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similar to Diffserv [RFC2475] may be preferred, where traffic is
proactively conditioned on entry to a domain, rather than
reactively policed only if it 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
[Nadas20], which is in turn similar to the idea behind core
stateless fair queuing.
No single one of these possible queue protection capabilities is
considered an essential part of the L4S architecture, which works
without any of them under non-attack conditions (much as the Internet
normally works without per-flow rate policing). Indeed, even where
latency policers are deployed, under normal circumstances they 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 sometimes 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 can 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.
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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. For instance the two-rate three-colour
marker [RFC2698] or a PCN threshold and excess-rate marker [RFC5670]
could mark ECN at the lower rate and drop at the higher. Or an
existing rate policer could have congestion-rate policing added,
e.g. using the 'local' (non-ConEx) variant of the ConEx aggregate
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
Various ways have been developed to protect the integrity of the
congestion feedback loop (whether signalled by loss, Classic ECN or
L4S ECN) against misbehaviour by the receiver, sender or network (or
all three). Brief details of each including applicability, pros and
cons is given in Appendix C.1 of the L4S ECN
spec [I-D.ietf-tsvwg-ecn-l4s-id].
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, L4S support has been added to FQ-CoDel, which classifies by
application flow ID in the network. However, the main innovation of
L4S is the DualQ AQM framework that does not need to inspect any
deeper than the outermost IP header, because the L4S identifier is in
the IP-ECN field.
Thus, the L4S architecture enables 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
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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. 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,
<https://doi.org/10.1016/j.jnca.2016.03.021>.
[BBRv2] Cardwell, N., "TCP BBR v2 Alpha/Preview Release", GitHub
repository; Linux congestion control module,
<https://github.com/google/bbr/blob/v2alpha/README.md>.
[BDPdata] Briscoe, B., "PI2 Parameters", Technical Report TR-BB-
2021-001 arXiv:2107.01003 [cs.NI], July 2021,
<https://arxiv.org/abs/2107.01003>.
[BufferSize]
Appenzeller, G., Keslassy, I., and N. McKeown, "Sizing
Router Buffers", In Proc. SIGCOMM'04 34(4):281--292,
September 2004, <https://doi.org/10.1145/1015467.1015499>.
[COBALT] Palmei, J., Gupta, S., Imputato, P., Morton, J.,
Tahiliani, M. P., Avallone, S., and D. Täht, "Design and
Evaluation of COBALT Queue Discipline", In Proc. IEEE
Int'l Symp. Local and Metropolitan Area Networks
(LANMAN'19) 2019:1-6, July 2019,
<https://ieeexplore.ieee.org/abstract/document/8847054>.
[DCttH19] De Schepper, K., Bondarenko, O., Tilmans, O., and B.
Briscoe, "`Data Centre to the Home': Ultra-Low Latency for
All", Updated RITE project Technical Report , July 2019,
<https://bobbriscoe.net/pubs.html#DCttH_TR>.
[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, 21 January 2019, <https://specification-
search.cablelabs.com/CM-SP-MULPIv3.1>.
[DOCSIS3AQM]
White, G., "Active Queue Management Algorithms for DOCSIS
3.0; A Simulation Study of CoDel, SFQ-CoDel and PIE in
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DOCSIS 3.0 Networks", CableLabs Technical Report , April
2013, <{https://www.cablelabs.com/wp-
content/uploads/2013/11/
Active_Queue_Management_Algorithms_DOCSIS_3_0.pdf>.
[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>.
[Dukkipati06]
Dukkipati, N. and N. McKeown, "Why Flow-Completion Time is
the Right Metric for Congestion Control", ACM CCR
36(1):59--62, January 2006,
<https://dl.acm.org/doi/10.1145/1111322.1111336>.
[FQ_CoDel_Thresh]
Høiland-Jørgensen, T., "fq_codel: generalise ce_threshold
marking for subset of traffic", Linux Patch Commit ID:
dfcb63ce1de6b10b, 20 October 2021,
<https://git.kernel.org/pub/scm/linux/kernel/git/netdev/
net-next.git/commit/?id=dfcb63ce1de6b10b>.
[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, <https://doi.acm.org/10.1145/2663716.2663730>.
[I-D.briscoe-conex-policing]
Briscoe, B., "Network Performance Isolation using
Congestion Policing", Work in Progress, Internet-Draft,
draft-briscoe-conex-policing-01, 14 February 2014,
<https://www.ietf.org/archive/id/draft-briscoe-conex-
policing-01.txt>.
[I-D.briscoe-docsis-q-protection]
Briscoe, B. and G. White, "The DOCSIS(r) Queue Protection
Algorithm to Preserve Low Latency", Work in Progress,
Internet-Draft, draft-briscoe-docsis-q-protection-06, 13
May 2022,
<https://datatracker.ietf.org/api/v1/doc/document/draft-
briscoe-docsis-q-protection/>.
Briscoe, et al. Expires 2 March 2023 [Page 37]
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[I-D.briscoe-iccrg-prague-congestion-control]
Schepper, K. D., Tilmans, O., and B. Briscoe, "Prague
Congestion Control", Work in Progress, Internet-Draft,
draft-briscoe-iccrg-prague-congestion-control-01, 11 July
2022, <https://datatracker.ietf.org/api/v1/doc/document/
draft-briscoe-iccrg-prague-congestion-control/>.
[I-D.briscoe-tsvwg-l4s-diffserv]
Briscoe, B., "Interactions between Low Latency, Low Loss,
Scalable Throughput (L4S) and Differentiated Services",
Work in Progress, Internet-Draft, draft-briscoe-tsvwg-l4s-
diffserv-02, 2 July 2018,
<https://datatracker.ietf.org/api/v1/doc/document/draft-
briscoe-tsvwg-l4s-diffserv/>.
[I-D.cardwell-iccrg-bbr-congestion-control]
Cardwell, N., Cheng, Y., Yeganeh, S. H., Swett, I., and V.
Jacobson, "BBR Congestion Control", Work in Progress,
Internet-Draft, draft-cardwell-iccrg-bbr-congestion-
control-02, 7 March 2022,
<https://datatracker.ietf.org/api/v1/doc/document/draft-
cardwell-iccrg-bbr-congestion-control/>.
[I-D.ietf-tcpm-accurate-ecn]
Briscoe, B., Kühlewind, M., and R. Scheffenegger, "More
Accurate ECN Feedback in TCP", Work in Progress, Internet-
Draft, draft-ietf-tcpm-accurate-ecn-20, 25 July 2022,
<https://datatracker.ietf.org/api/v1/doc/document/draft-
ietf-tcpm-accurate-ecn/>.
[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)", Work in Progress, Internet-Draft, draft-ietf-
tsvwg-aqm-dualq-coupled-24, 7 July 2022,
<https://datatracker.ietf.org/api/v1/doc/document/draft-
ietf-tsvwg-aqm-dualq-coupled/>.
[I-D.ietf-tsvwg-ecn-encap-guidelines]
Briscoe, B. and J. Kaippallimalil, "Guidelines for Adding
Congestion Notification to Protocols that Encapsulate IP",
Work in Progress, Internet-Draft, draft-ietf-tsvwg-ecn-
encap-guidelines-17, 11 July 2022,
<https://datatracker.ietf.org/api/v1/doc/document/draft-
ietf-tsvwg-ecn-encap-guidelines/>.
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[I-D.ietf-tsvwg-ecn-l4s-id]
Schepper, K. D. and B. Briscoe, "Explicit Congestion
Notification (ECN) Protocol for Very Low Queuing Delay
(L4S)", Work in Progress, Internet-Draft, draft-ietf-
tsvwg-ecn-l4s-id-28, 8 August 2022,
<https://datatracker.ietf.org/api/v1/doc/document/draft-
ietf-tsvwg-ecn-l4s-id/>.
[I-D.ietf-tsvwg-l4sops]
White, G., "Operational Guidance for Deployment of L4S in
the Internet", Work in Progress, Internet-Draft, draft-
ietf-tsvwg-l4sops-03, 28 April 2022,
<https://datatracker.ietf.org/api/v1/doc/document/draft-
ietf-tsvwg-l4sops/>.
[I-D.ietf-tsvwg-nqb]
White, G. and T. Fossati, "A Non-Queue-Building Per-Hop
Behavior (NQB PHB) for Differentiated Services", Work in
Progress, Internet-Draft, draft-ietf-tsvwg-nqb-10, 4 March
2022, <https://datatracker.ietf.org/api/v1/doc/document/
draft-ietf-tsvwg-nqb/>.
[I-D.ietf-tsvwg-rfc6040update-shim]
Briscoe, B., "Propagating Explicit Congestion Notification
Across IP Tunnel Headers Separated by a Shim", Work in
Progress, Internet-Draft, draft-ietf-tsvwg-rfc6040update-
shim-15, 11 July 2022,
<https://datatracker.ietf.org/api/v1/doc/document/draft-
ietf-tsvwg-rfc6040update-shim/>.
[I-D.morton-tsvwg-codel-approx-fair]
Morton, J. and P. G. Heist, "Controlled Delay Approximate
Fairness AQM", Work in Progress, Internet-Draft, draft-
morton-tsvwg-codel-approx-fair-01, 9 March 2020,
<https://www.ietf.org/archive/id/draft-morton-tsvwg-codel-
approx-fair-01.txt>.
[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", Work in Progress, Internet-
Draft, draft-sridharan-tcpm-ctcp-02, 29 October 2007,
<https://datatracker.ietf.org/api/v1/doc/document/draft-
sridharan-tcpm-ctcp/>.
[I-D.stewart-tsvwg-sctpecn]
Stewart, R. R., Tuexen, M., and X. Dong, "ECN for Stream
Control Transmission Protocol (SCTP)", Work in Progress,
Briscoe, et al. Expires 2 March 2023 [Page 39]
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Internet-Draft, draft-stewart-tsvwg-sctpecn-05, 15 January
2014, <https://www.ietf.org/archive/id/draft-stewart-
tsvwg-sctpecn-05.txt>.
[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,
<https://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>.
[lowat] Meenan, P., "Optimizing HTTP/2 prioritization with BBR and
tcp_notsent_lowat", Cloudflare Blog , 12 October 2018,
<https://blog.cloudflare.com/http-2-prioritization-with-
nginx/>.
[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.D., Pinson, E. N., and B. A. 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] Nádas, 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, <https://doi.org/10.1145/3404868.3406669>.
[NASA04] Bailey, R.R., Trey Arthur III, J.J., and S.P. Williams,
"Latency Requirements for Head-Worn Display S/EVS
Applications", SPIE Defense and Security
Symposium LF99-1955, April 2004,
<https://ntrs.nasa.gov/api/citations/20120009198/
downloads/20120009198.pdf?attachment=true>.
Briscoe, et al. Expires 2 March 2023 [Page 40]
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[PragueLinux]
Briscoe, B., De Schepper, K., Albisser, O., Misund, J.,
Tilmans, O., Kühlewind, M., and A.S. 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>.
[Raaen14] Raaen, K. and T-M. Grønli, "Latency thresholds for
usability in games: A survey", Norsk IKT-konferanse for
forskning og utdanning , 2014,
<http://ojs.bibsys.no/index.php/NIK/article/view/9/6>.
[Rajiullah15]
Rajiullah, M., "Towards a Low Latency Internet:
Understanding and Solutions", Master's Thesis; Karlstad
Uni, Dept of Maths & CS 2015:41, 2015, <https://www.diva-
portal.org/smash/get/diva2:846109/FULLTEXT01.pdf>.
[RFC0970] Nagle, J., "On Packet Switches With Infinite Storage",
RFC 970, DOI 10.17487/RFC0970, December 1985,
<https://www.rfc-editor.org/info/rfc970>.
[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>.
[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>.
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[RFC3246] Davie, B., Charny, A., Bennet, J.C.R., Benson, K., Le
Boudec, J.Y., 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>.
[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>.
[RFC5670] Eardley, P., Ed., "Metering and Marking Behaviour of PCN-
Nodes", RFC 5670, DOI 10.17487/RFC5670, November 2009,
<https://www.rfc-editor.org/info/rfc5670>.
[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>.
Briscoe, et al. Expires 2 March 2023 [Page 42]
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[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>.
[RFC6817] Shalunov, S., Hazel, G., Iyengar, J., and M. Kuehlewind,
"Low Extra Delay Background Transport (LEDBAT)", RFC 6817,
DOI 10.17487/RFC6817, December 2012,
<https://www.rfc-editor.org/info/rfc6817>.
[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>.
[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>.
[RFC7567] Baker, F., Ed. and G. Fairhurst, Ed., "IETF
Recommendations Regarding Active Queue Management",
BCP 197, RFC 7567, DOI 10.17487/RFC7567, July 2015,
<https://www.rfc-editor.org/info/rfc7567>.
[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>.
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[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>.
[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>.
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[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>.
[RFC9113] Thomson, M., Ed. and C. Benfield, Ed., "HTTP/2", RFC 9113,
DOI 10.17487/RFC9113, June 2022,
<https://www.rfc-editor.org/info/rfc9113>.
[SCReAM] Johansson, I., "SCReAM", GitHub repository; ,
<https://github.com/EricssonResearch/scream/blob/master/
README.md>.
[TCP-CA] Jacobson, V. and M.J. Karels, "Congestion Avoidance and
Control", Laurence Berkeley Labs Technical Report ,
November 1988, <https://ee.lbl.gov/papers/congavoid.pdf>.
[UnorderedLTE]
Austrheim, M.V., "Implementing immediate forwarding for 4G
in a network simulator", Master's Thesis, Uni Oslo , June
2019.
Acknowledgements
Thanks to Richard Scheffenegger, Wes Eddy, Karen Nielsen, David
Black, Jake Holland, Vidhi Goel, Ermin Sakic, Praveen
Balasubramanian, Gorry Fairhurst, Mirja Kuehlewind, Philip Eardley,
Neal Cardwell, Pete Heist and Martin Duke for their useful review
comments. Thanks also to the area reviewers: Marco Tiloca, Lars
Eggert, Roman Danyliw and Eric Vyncke.
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). The
contribution of Koen De Schepper was also part-funded by the 5Growth
and DAEMON EU H2020 projects. 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.
Authors' Addresses
Briscoe, et al. Expires 2 March 2023 [Page 45]
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Bob Briscoe (editor)
Independent
United Kingdom
Email: ietf@bobbriscoe.net
URI: https://bobbriscoe.net/
Koen De Schepper
Nokia Bell Labs
Antwerp
Belgium
Email: koen.de_schepper@nokia.com
URI: https://www.bell-labs.com/about/researcher-profiles/
koende_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: https://www.it.uc3m.es
Greg White
CableLabs
United States of America
Email: G.White@CableLabs.com
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