Low Latency, Low Loss, Scalable
Throughput (L4S) Internet Service: ArchitectureIndependentUKietf@bobbriscoe.nethttp://bobbriscoe.net/Nokia Bell LabsAntwerpBelgiumkoen.de_schepper@nokia.comhttps://www.bell-labs.com/usr/koen.de_schepperUniversidad Carlos III de MadridAv. Universidad 30Leganes, Madrid 28911Spain34 91 6249500marcelo@it.uc3m.eshttp://www.it.uc3m.esCableLabsUSG.White@CableLabs.com
Transport
Transport Area Working GroupInternet-DraftI-DThis document describes the L4S architecture, which enables Internet
applications to achieve Low queuing Latency, Low Loss, and Scalable
throughput (L4S). The insight on which L4S is based is that the root
cause of queuing delay is in the congestion controllers of senders, not
in the queue itself. The L4S architecture is intended to enable all Internet applications to transition away from
congestion control algorithms that cause queuing delay, to a new class
of congestion controls that induce very little queuing, aided by
explicit congestion signaling from the network. This new class of
congestion control can provide low latency for capacity-seeking flows,
so applications can achieve both high bandwidth and low latency.The architecture primarily concerns incremental deployment. It
defines mechanisms that allow the new class of L4S congestion controls
to coexist with 'Classic' congestion controls in a shared network. These
mechanisms aim to ensure that the latency and throughput performance
using an L4S-compliant congestion controller is usually much better (and
never worse) than the performance would have been using a 'Classic'
congestion controller, and that competing flows continuing to use
'Classic' controllers are typically not impacted by the presence of L4S.
These characteristics are important to encourage adoption of L4S
congestion control algorithms and L4S compliant network elements.The L4S architecture consists of three components: network support to
isolate L4S traffic from classic traffic; protocol features that allow
network elements to identify L4S traffic; and host support for L4S
congestion controls.It is increasingly common for all of a
user's applications at any one time to require low delay: interactive
Web, Web services, voice, conversational video, interactive video,
interactive remote presence, instant messaging, online gaming, remote
desktop, cloud-based applications and video-assisted remote control of
machinery and industrial processes. In the last decade or so, much has
been done to reduce propagation delay by placing caches or servers
closer to users. However, queuing remains a major, albeit intermittent,
component of latency. For instance spikes of hundreds of milliseconds
are common, even with state-of-the-art active queue management (AQM).
During a long-running flow, queuing is typically configured to cause
overall network delay to roughly double relative to expected base
(unloaded) path delay. Low loss is also important because, for
interactive applications, losses translate into even longer
retransmission delays.It has been demonstrated that, once access network bit rates reach
levels now common in the developed world, increasing capacity offers
diminishing returns if latency (delay) is not addressed. Differentiated
services (Diffserv) offers Expedited Forwarding (EF ) for some packets at the expense of others, but this
is not sufficient when all (or most) of a user's applications require
low latency.Therefore, the goal is an Internet service with ultra-Low queueing
Latency, ultra-Low Loss and Scalable throughput (L4S). Ultra-low queuing
latency means less than 1 millisecond (ms) on average and less than
about 2 ms at the 99th percentile. L4S is potentially for all traffic - a service for all traffic needs none
of the configuration or management baggage (traffic policing, traffic
contracts) associated with favouring some traffic over others. This
document describes the L4S architecture for achieving these goals.It must be said that queuing delay only degrades performance
infrequently . It only occurs when a
large enough capacity-seeking (e.g. TCP) flow is running alongside
the user's traffic in the bottleneck link, which is typically in the
access network. Or when the low latency application is itself a large
capacity-seeking or adaptive rate (e.g. interactive video) flow. At
these times, the performance improvement from L4S must be sufficient
that network operators will be motivated to deploy it.Active Queue Management (AQM) is part of the solution to queuing
under load. AQM improves performance for all traffic, but there is a
limit to how much queuing delay can be reduced by solely changing the
network; without addressing the root of the problem.The root of the problem is the presence of standard TCP congestion
control (Reno ) or compatible variants
(e.g. TCP Cubic ). 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 . 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 , (for other link types,
see ). This compares with 5 to 20
ms on average with a Classic congestion
control and current state-of-the-art AQMs such as FQ-CoDel , PIE or DOCSIS
PIE and about 20-30 ms at the 99th
percentile .It has also been demonstrated , that it is possible to deploy such an L4S
service alongside the existing best efforts service so that all of a
user's applications can shift to it when their stack is updated. Access
networks are typically designed with one link as the bottleneck for each
site (which might be a home, small enterprise or mobile device), so
deployment at each end of this link should give nearly all the benefit
in each direction. The L4S approach also requires component mechanisms
at the endpoints to fulfill its goal. This document presents the L4S
architecture, by describing the different components and how they
interact to provide the scalable, low latency, low loss Internet
service.There are three main components to the L4S architecture:L4S traffic needs to be isolated from the
queuing latency of Classic traffic. One queue per application flow
(FQ) is one way to achieve this, e.g. FQ-CoDel . However, just two queues is sufficient and does
not require inspection of transport layer headers in the network,
which is not always possible (see ).
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. gives a high level
explanation of how FQ and DualQ solutions work, and gives a full explanation
of the DualQ Coupled AQM framework.A host needs to distinguish L4S and
Classic packets with an identifier so that the network can classify
them into their separate treatments. considers various alternative
identifiers for L4S, and concludes that all alternatives involve
compromises, but the ECT(1) and CE codepoints of the ECN field
represent a workable solution.Scalable congestion controls already exist.
They solve the scaling problem with Reno congestion control that was
explained in . The one used most widely (in
controlled environments) is Data Center TCP (DCTCP ), which has been implemented and deployed in
Windows Server Editions (since 2012), in Linux and in FreeBSD.
Although DCTCP as-is 'works' well over the public Internet, most
implementations lack certain safety features that will be necessary
once it is used outside controlled environments like data centres
(see and ). Scalable congestion control will
also need to be implemented in protocols other than TCP (QUIC, SCTP,
RTP/RTCP, RMCAT, etc.). Indeed, between the present document being
drafted and published, the following scalable congestion controls
were implemented: TCP Prague , QUIC
Prague, an L4S variant of the RMCAT SCReAM controller and the L4S ECN part of BBRv2 intended for
TCP and QUIC transports.A congestion control
behaviour that can co-exist with standard TCP Reno without causing significantly negative impact on
its flow rate . With Classic congestion
controls, as flow rate scales, the number of round trips between
congestion signals (losses or ECN marks) rises with the flow rate.
So it takes longer and longer to recover after each congestion
event. Therefore control of queuing and utilization becomes very
slack, and the slightest disturbance prevents a high rate from being
attained .For
instance, with 1500 byte packets and an end-to-end round trip time
(RTT) of 36 ms, over the years, as Reno flow rate scales from 2 to
100 Mb/s the number of round trips taken to recover from a
congestion event rises proportionately, from 4 to 200.
Cubic was developed to be less
unscalable, but it is approaching its scaling limit; with the same
RTT of 36 ms, at 100Mb/s it takes about 106 round trips to recover,
and at 800 Mb/s its recovery time triples to over 340 round trips,
or still more than 12 seconds (Reno would take 57 seconds).A congestion control
where the average time from one congestion signal to the next (the
recovery time) remains invariant as the flow rate scales, all other
factors being equal. This maintains the same degree of control over
queueing and utilization whatever the flow rate, as well as ensuring
that high throughput is more robust to disturbances (e.g. from
new flows starting). For instance, DCTCP averages 2 congestion
signals per round-trip whatever the flow rate, as do other recently
developed scalable congestion controls, e.g. Relentless
TCP , TCP Prague and the L4S variant of SCReAM for real-time
media ).See Section 4.3 of for more explanation.The Classic service is intended for
all the congestion control behaviours that co-exist with
Reno (e.g. Reno itself,
Cubic , Compound , TFRC ). The term 'Classic queue' means a queue
providing the Classic service.The
'L4S' service is intended for traffic from scalable congestion
control algorithms, such as Data Center TCP . The L4S service is for more general traffic than
just DCTCP—it allows the set of congestion controls with
similar scaling properties to DCTCP to evolve, such as the examples
listed above (Relentless, Prague, 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, as long as it does not build a
queue (e.g. DNS, VoIP, game sync datagrams, etc).The subset of Classic traffic that
excludes unresponsive traffic and excludes experimental congestion
controls intended to coexist with Reno but without always being
strictly friendly to it (as allowed by ).
Reno-friendly is used in place of 'TCP-friendly', given that
friendliness is a property of the congestion controller (Reno), not
the wire protocol (TCP), which is used with many different
congestion control behaviours.The original Explicit Congestion
Notification (ECN) protocol , which
requires ECN signals to be treated as equivalent to drops, both when
generated in the network and when responded to by the sender.The names used for the four codepoints of the 2-bit
IP-ECN field are as defined in : Not ECT,
ECT(0), ECT(1) and CE, where ECT stands for ECN-Capable Transport
and CE stands for Congestion Experienced.A home, mobile device, small enterprise or
campus, where the network bottleneck is typically the access link to
the site. Not all network arrangements fit this model but it is a
useful, widely applicable generalization.The L4S architecture is composed of the following elements.Protocols: The L4S architecture encompasses two identifier changes
(an unassignment and an assignment) and optional further identifiers:
An essential aspect of a scalable congestion control is the use
of explicit congestion signals rather than losses, because the
signals need to be sent frequently and immediately. In contrast,
'Classic' ECN requires an ECN signal
to be treated as equivalent to drop, both when it is generated in
the network and when it is responded to by hosts. L4S needs networks
and hosts to support a different meaning for ECN:much more frequent signals—too often to require an
equivalent excessive degree of drop from non-ECN flows;immediately tracking every fluctuation of the queue—too
soon to warrant dropping packets from non-ECN flows.So the standards track has had to
be updated to allow L4S packets to depart from the 'same as drop'
constraint. 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 reclassifies the
original experimental assignment of the ECT(1) codepoint as an ECN
nonce as historic. recommends ECT(1) is
used as the identifier to classify L4S packets into a separate
treatment from Classic packets. This satisfies the requirements for
identifying an alternative ECN treatment in .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. explains why 5 unlikely
eventualities all have to coincide for this to have any detrimental
effect, which even then would only involve a vanishingly small
likelihood of a spurious retransmission.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 ), Non-Queue-Building (NQB ), or operator-specific
identifiers.Network components: The L4S architecture aims to provide low latency
without the need for per-flow operations in
network components. Nonetheless, the architecture does not preclude
per-flow solutions - it encompasses the following combinations:The Dual Queue Coupled AQM (illustrated in ) achieves the 'semi-permeable'
membrane property mentioned earlier as follows. The obvious part is
that using two separate queues isolates the queuing delay of one
from the other. The less obvious part is how the two queues act as if they are a
single pool of bandwidth without the scheduler needing to decide
between them. This is achieved by having the Classic AQM provide a
congestion signal to both queues in a manner that ensures a
consistent response from the two types of congestion control. In
other words, the Classic AQM generates a drop/mark probability based
on congestion in the Classic queue, uses this probability to
drop/mark packets in that queue, and also uses this probability to
affect the marking probability in the L4S queue. This coupling of
the congestion signaling between the two queues makes the L4S flows
slow down to leave the right amount of capacity for the Classic
traffic (as they would if they were the same type of traffic sharing
the same queue). Then the scheduler can serve the L4S queue with
priority, because the L4S traffic isn't offering up enough traffic
to use all the priority that it is given. Therefore, on short
time-scales (sub-round-trip) the prioritization of the L4S queue
protects its low latency by allowing bursts to dissipate quickly;
but on longer time-scales (round-trip and longer) the Classic queue
creates an equal and opposite pressure against the L4S traffic to
ensure that neither has priority when it comes to bandwidth. The
tension between prioritizing L4S and coupling marking from Classic
results in per-flow fairness. To protect against unresponsive
traffic in the L4S queue taking advantage of the prioritization and
starving the Classic queue, it is advisable not to use strict
priority, but instead to use a weighted scheduler (see Appendix A of
). When there is no Classic traffic, the L4S
queue’s AQM comes into play, and it sets an appropriate
marking rate to maintain ultra-low queuing delay.The Dual Queue Coupled AQM has been specified as
generically as possible 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) 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 .A scheduler with per-flow queues can be used for L4S. It is
simple to modify an existing design such as FQ-CoDel or FQ-PIE. For
instance within each queue of an FQ-CoDel system, as well as a CoDel
AQM, immediate (unsmoothed) shallow threshold ECN marking has been
added (see Sec.5.2.7 of ). Then the Classic
AQM such as CoDel or PIE is applied to non-ECN or ECT(0) packets,
while the shallow threshold is applied to ECT(1) packets, to give
sub-millisecond average queue delay.It would also be possible to use dual queues for isolation, but
with per-flow marking to control flow-rates (instead of the coupled
per-queue marking of the Dual Queue Coupled AQM). One of the two
queues would be for isolating L4S packets, which would be classified
by the ECN codepoint. Flow rates could be controlled by
flow-specific marking. The policy goal of the marking could be to
differentiate flow rates (e.g. , which
requires additional signalling of a per-flow 'value'), or to
equalize flow-rates (perhaps in a similar way to Approx Fair CoDel
, , 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.Host mechanisms: The L4S architecture includes two main mechanisms in
the end host that we enumerate next:Scalable Congestion Control: Data Center TCP is the most widely
used example. It has been documented as an informational record of
the protocol currently in use in controlled environments . 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 ). The subset that involve risk
of harm to others have been captured as normative requirements in
Section 4 of . TCP Prague
has been implemented in Linux as a reference implementation to
address these requirements .Transport protocols other than TCP use various
congestion controls that are designed to be friendly with Reno.
Before they can use the L4S service, it will be necessary to
implement scalable variants of each of these congestion control
behaviours. They will eventually need to be updated to implement a
scalable congestion response, which they will have to indicate by
using the ECT(1) codepoint. Scalable variants are under
consideration for some new transport protocols that are themselves
under development, e.g. QUIC. Also the L4S ECN part of
BBRv2 is a scalable
congestion control intended for the TCP and QUIC transports, amongst
others. Also an L4S variant of the RMCAT SCReAM
controller has been implemented for
media transported over RTP. ECN feedback is sufficient for L4S in some transport protocols
(specifically DCCP and QUIC ). 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 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 . Work to
standardize and implement more accurate ECN feedback for TCP
(AccECN) is in progress , .ECN feedback is only roughly sketched in an appendix of the
SCTP specification . A fuller
specification has been proposed in a long-expired
draft , which
would need to be implemented and deployed before SCTCP could
support L4S.For RTP, sufficient ECN feedback was defined in , but defines the
latest standards track improvements. Explicit
congestion signalling is a key part of the L4S approach. In
contrast, use of drop as a congestion signal creates a tension
because drop is both an impairment (less would be better) and a
useful signal (more would be better):Explicit congestion signals can be used many times per
round trip, to keep tight control, without any impairment.
Under heavy load, even more explicit signals can be applied so
the queue can be kept short whatever the load. Whereas
state-of-the-art AQMs have to introduce very high packet drop
at high load to keep the queue short. Further, when using ECN,
the congestion control's sawtooth reduction can be smaller and
therefore return to the operating point more often, without
worrying that this causes more signals (one at the top of each
smaller sawtooth). The consequent smaller amplitude sawteeth
fit between a very shallow marking threshold and an empty
queue, so queue delay variation can be very low, without risk
of under-utilization.Explicit congestion signals can be sent immediately to
track fluctuations of the queue. L4S shifts smoothing from the
network (which doesn't know the round trip times of all the
flows) to the host (which knows its own round trip time).
Previously, the network had to smooth to keep a worst-case
round trip stable, which delayed congestion signals by 100-200
ms.All the above makes it clear that explicit congestion
signalling is only advantageous for latency if it does not have to
be considered 'equivalent to' drop (as was required with Classic
ECN ). Therefore, in an L4S AQM, the
L4S queue uses a new L4S variant of ECN that is not equivalent to
drop , while the
Classic queue uses either classic ECN 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."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).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 ).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.A scalable
congestion control in the host keeps the signalling frequency from
the network high so that rate variations can be small when
signalling is stable, and rate can track variations in available
capacity as rapidly as possible otherwise.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 .The "Scalable throughput" part
of the name denotes that the per-flow throughput of scalable
congestion controls should scale indefinitely, avoiding the
imminent scaling problems with Reno-friendly congestion control
algorithms . It was known when TCP
congestion avoidance was first developed that it would not scale
to high bandwidth-delay products (see footnote 6 in ). Today, regular broadband bit-rates over WAN
distances are already beyond the scaling range of Classic Reno
congestion control. So `less unscalable' Cubic and Compound variants of TCP have been
successfully deployed. However, these are now approaching their
scaling limits. As the examples in demonstrate, as flow rate scales
Classic congestion controls like Reno or Cubic induce a congestion
signal more and more infrequently (hundreds of round trips at
today's flow rates and growing), which makes dynamic control very
sloppy. In contrast on average a scalable congestion control like
DCTCP or TCP Prague induces 2 congestion signals per round trip,
which remains invariant for any flow rate, keeping dynamic control
very tight.Although work on scaling
congestion controls tends to start with TCP as the transport, the
above is not intended to exclude other transports (e.g. SCTP,
QUIC) or less elastic algorithms (e.g. RMCAT), which all tend
to adopt the same or similar developments.All the following approaches address some part of the same problem
space as L4S. In each case, it is shown that L4S complements them or
improves on them, rather than being a mutually exclusive
alternative:Diffserv addresses the problem of
bandwidth apportionment for important traffic as well as queuing
latency for delay-sensitive traffic. 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 .
Nonetheless, the L4S approach can provide low latency for all traffic within each Diffserv class
(including the case where there is only the one default Diffserv
class).Also, Diffserv only works for a
small subset of the traffic on a link. As already explained, it is
not applicable when all the applications in use at one time at a
single site (home, small business or mobile device) require low
latency. In contrast, because L4S is for all traffic, it needs
none of the management baggage (traffic policing, traffic
contracts) associated with favouring some packets over others.
This baggage has probably held Diffserv back from widespread
end-to-end deployment.In particular,
because networks tend not to trust end systems to identify which
packets should be favoured over others, where networks assign
packets to Diffserv classes they often use packet inspection of
application flow identifiers or deeper inspection of application
signatures. Thus, nowadays, Diffserv doesn't always sit well with
encryption of the layers above IP. So users have to choose between
privacy and QoS.As with Diffserv, the L4S
identifier is in the IP header. But, in contrast to Diffserv, the
L4S identifier does not convey a want or a need for a certain
level of quality. Rather, it promises a certain behaviour
(scalable congestion response), which networks can objectively
verify if they need to. This is because low delay depends on
collective host behaviour, whereas bandwidth priority depends on
network behaviour.AQMs such as PIE and FQ-CoDel
give a significant reduction in queuing delay relative to no AQM
at all. L4S is intended to complement these AQMs, and should not
distract from the need to deploy them as widely as possible.
Nonetheless, AQMs alone cannot reduce queuing delay too far
without significantly reducing link utilization, because the root
cause of the problem is on the host - where Classic congestion
controls use large saw-toothing rate variations. The L4S approach
resolves this tension by ensuring hosts can minimize the size of
their sawteeth without appearing so aggressive to Classic flows
that they starve them.Similarly, per-flow
approaches such as FQ-CoDel or Approx Fair CoDel are not incompatible with the L4S approach.
However, per-flow queuing alone is not enough - it only isolates
the queuing of one flow from others; not from itself. Per-flow
implementations still need to have support for scalable congestion
control added, which has already been done in FQ-CoDel (see
Sec.5.2.7 of ). Without this simple
modification, per-flow AQMs like FQ-CoDel would still not be able
to support applications that need both ultra-low delay and high
bandwidth, e.g. video-based control of remote procedures, or
interactive cloud-based video (see Note
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:Per-flow forms of L4S like FQ-CoDel are incompatible with
full end-to-end encryption of transport layer identifiers for
privacy and confidentiality (e.g. IPSec or encrypted VPN
tunnels), because they require packet inspection to access the
end-to-end transport flow identifiers. In contrast, the DualQ form of L4S requires no
deeper inspection than the IP layer. So, as long as operators
take the DualQ approach, their users can have both ultra-low
queuing delay and full end-to-end encryption .With per-flow forms of L4S, the network takes over control
of the relative rates of each application flow. Some see it as
an advantage that the network will prevent some flows running
faster than others. Others consider it an inherent part of the
Internet's appeal that applications can control their rate
while taking account of the needs of others via congestion
signals. They maintain that this has allowed applications with
interesting rate behaviours to evolve, for instance, variable
bit-rate video that varies around an equal share rather than
being forced to remain equal at every instant, or scavenger
services that use less than an equal share of
capacity .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' , 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: 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
or some interactive media applications (see ), can keep low latency objects at the
front of their local send queue by shuffling priorities of
other objects dependent on the progress of other transfers.
They cannot shuffle objects once they have released them into
the network.Here again, L4S is
not an alternative to ABE but a complement that introduces much
lower queuing delay. ABE 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).Bottleneck Bandwidth and Round-trip propagation
time (BBR ) controls
queuing delay end-to-end without needing any special logic in the
network, such as an AQM. So it works pretty-much on any path
(although it has not been without problems, particularly capacity
sharing in BBRv1). BBR keeps queuing delay reasonably low, but
perhaps not quite as low as with state-of-the-art AQMs such as PIE
or FQ-CoDel, and certainly nowhere near as low as with L4S.
Queuing delay is also not consistently low, due to BBR's regular
bandwidth probing spikes and its aggressive flow start-up
phase.L4S complements BBR. Indeed BBRv2
uses L4S ECN and a scalable L4S congestion control behaviour in
response to any ECN signalling from the path. The L4S ECN signal
complements the delay based congestion control aspects of BBR with
an explicit indication that hosts can use, both to converge on a
fair rate and to keep below a shallow queue target set by the
network. Without L4S ECN, both these aspects need to be assumed or
estimated.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.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 . For
the former, a panoramic video of a football stadium could be swiped
and pinched so that, on the fly, a proxy in the cloud could generate a
sub-window of the match video under the finger-gesture control of each
user. For the latter, a virtual reality headset displayed a viewport
taken from a 360 degree camera in a racing car. The user's head
movements controlled the viewport extracted by a cloud-based proxy. In
both cases, with 7 ms end-to-end base delay, the additional queuing
delay of roughly 1 ms was so low that it seemed the video was
generated locally.Using a swiping finger gesture or head movement to pan a video are
extremely latency-demanding actions—far more demanding than
VoIP. Because human vision can detect extremely low delays of the
order of single milliseconds when delay is translated into a visual
lag between a video and a reference point (the finger or the
orientation of the head sensed by the balance system in the inner ear
--- the vestibular system).Without the low queuing delay of L4S, cloud-based applications like
these would not be credible without significantly more access
bandwidth (to deliver all possible video that might be viewed) and
more local processing, which would increase the weight and power
consumption of head-mounted displays. When all interactive processing
can be done in the cloud, only the data to be rendered for the end
user needs to be sent.Other low latency high bandwidth applications such as: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.The following use-cases for L4S are being considered by various
interested parties:Where the bottleneck is one of various types of access network:
e.g. DSL, Passive Optical Networks (PON), DOCSIS cable,
mobile, satellite (see 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
companya 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 :mobile and other networks have tended to inspect higher
layers in order to guess application QoS requirements.
However, with growing demand for support of privacy and
encryption, L4S offers an alternative. There is no need to
select which traffic to favour for queuing, when L4S gives
favourable queuing to all traffic.If queuing delay is minimized, applications with a fixed delay
budget can communicate over longer distances, or via a longer
chain of service functions 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 experienceCertain link technologies aggregate data from multiple packets into
bursts, and buffer incoming packets while building each burst. WiFi,
PON and cable all involve such packet aggregation, whereas fixed
Ethernet and DSL do not. No sender, whether L4S or not, can do
anything to reduce the buffering needed for packet aggregation. So an
AQM should not count this buffering as part of the queue that it
controls, given no amount of congestion signals will reduce it.Certain link technologies also add buffering for other reasons,
specifically:Radio links (cellular, WiFi, satellite) that are distant from
the source are particularly challenging. The radio link capacity
can vary rapidly by orders of magnitude, so it is considered
desirable to hold a standing queue that can utilize sudden
increases of capacity;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.L4S AQMs, whether DualQ or FQ, e.g. are, in themselves, an incremental deployment
mechanism for L4S - so that L4S traffic can coexist with existing
Classic (Reno-friendly) traffic.
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 suggests some typical sequences to
deploy each part, and why there will be an immediate and significant
benefit after deploying just one part. and 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.L4S AQMs will not have to be deployed throughout the Internet
before L4S will work for anyone. Operators of public Internet access
networks typically design their networks so that the bottleneck will
nearly always occur at one known (logical) link. This confines the
cost of queue management technology to one place.The case of mesh networks is different and will be discussed
later in this section. But the known bottleneck case is generally
true for Internet access to all sorts of different 'sites', where
the word 'site' includes home networks, small- to medium-sized
campus or enterprise networks and even cellular devices (). 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.)Deployment in mesh topologies depends on how over-booked the core
is. If the core is non-blocking, or at least generously provisioned
so that the edges are nearly always the bottlenecks, it would only
be necessary to deploy an L4S AQM at the edge bottlenecks. For
example, some data-centre networks are designed with the bottleneck
in the hypervisor or host NICs, while others bottleneck at the
top-of-rack switch (both the output ports facing hosts and those
facing the core).An L4S AQM would eventually also need to be deployed at any other
persistent bottlenecks such as network interconnections,
e.g. some public Internet exchange points and the ingress and
egress to WAN links interconnecting data-centres.For any one L4S flow to work, it requires 3 parts to have been
deployed. This was the same deployment problem that ECN
faced so we have learned from that
experience.Firstly, L4S deployment exploits the fact that DCTCP already
exists on many Internet hosts (Windows, FreeBSD and Linux); both
servers and clients. Therefore, just deploying an L4S AQM at a
network bottleneck immediately gives a working deployment of all the
L4S parts. DCTCP needs some safety concerns to be fixed for general
use over the public Internet (see Section 2.3 of ), 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 .
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. illustrates some example
sequences in which the parts of L4S might be deployed. It consists
of the following stages:Here, the immediate benefit of a single AQM deployment can be
seen, but limited to a controlled trial or controlled
deployment. In this example downstream deployment is first, but
in other scenarios the upstream might be deployed first. If no
AQM at all was previously deployed for the downstream access, an
L4S AQM greatly improves the Classic service (as well as adding
the L4S service). If an AQM was already deployed, the Classic
service will be unchanged (and L4S will add an improvement on
top).In this stage, the name 'TCP Prague' is used to represent a variant of DCTCP
that is safe to use in a production Internet environment. If the
application is primarily unidirectional, 'TCP Prague' at one end
will provide all the benefit needed. For TCP transports,
Accurate ECN feedback (AccECN) is needed at the other
end, but it is a generic ECN feedback facility that is already
planned to be deployed for other purposes, e.g. DCTCP, BBR.
The two ends can be deployed in either order, because, in TCP,
an L4S congestion control only enables itself if it has
negotiated the use of AccECN feedback with the other end during
the connection handshake. Thus, deployment of TCP Prague on a
server enables L4S trials to move to a production service in one
direction, wherever AccECN is deployed at the other end. This
stage might be further motivated by the performance improvements
of TCP Prague relative to DCTCP (see Appendix A.2 of ).Unlike TCP, from the outset, QUIC ECN
feedback has
supported L4S. Therefore, if the transport is QUIC, one-ended
deployment of a Prague congestion control at this stage is
simple and sufficient.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.If L4S is enabled between two hosts, the L4S sender is required
to coexist safely with Reno in response to any drop (see Section 4.3
of ).Unfortunately, as well as protecting Classic traffic, this rule
degrades the L4S service whenever there is any loss, even if the
cause is not persistent congestion at a bottleneck, e.g.:congestion loss at other transient bottlenecks, e.g. due
to bursts in shallower queues;transmission errors, e.g. due to electrical
interference;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 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 , ;Hybrid ECN/drop rate policers (see ).L4S deployment scenarios that minimize these issues
(e.g. over wireline networks) can proceed in parallel to this
research, in the expectation that research success could continually
widen L4S applicability.Classic ECN support is starting to materialize on the Internet as
an increased level of CE marking. It is hard to detect whether this
is all due to the addition of support for ECN in the Linux
implementation of FQ-CoDel, which is not problematic, because FQ
inherently forces the throughput of each flow to be equal
irrespective of its aggressiveness. However, some of this Classic
ECN marking might be due to single-queue ECN deployment. This case
is discussed in Section 4.3 of ).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 , , .This specification contains no IANA considerations.Because the L4S service can serve all traffic that is using the
capacity of a link, it should not be necessary to rate-police access
to the L4S service. In contrast, Diffserv only works if some packets
get less favourable treatment than others. So Diffserv has to use
traffic rate policers to limit how much traffic can be favoured. In
turn, traffic policers require traffic contracts between users and
networks as well as pairwise between networks. Because L4S will lack
all this management complexity, it is more likely to work
end-to-end.During early deployment (and perhaps always), some networks will
not offer the L4S service. In general, these networks should not need
to police L4S traffic - they are required not to change the L4S
identifier, merely treating the traffic as best efforts traffic, as
they already treat traffic with ECT(1) today. At a bottleneck, such
networks will introduce some queuing and dropping. When a scalable
congestion control detects a drop it will have to respond safely with
respect to Classic congestion controls (as required in Section 4.3 of
). 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 ).In some cases, networks that solely support Classic ECN in a single queue bottleneck might opt to police
L4S traffic in order to protect competing Classic ECN traffic.Certain network operators might choose to restrict access to the
L4S class, perhaps only to selected premium customers as a value-added
service. Their packet classifier (item 2 in ) could identify such customers against
some other field (e.g. source address range) as well as ECN. If
only the ECN L4S identifier matched, but not the source address (say),
the classifier could direct these packets (from non-premium customers)
into the Classic queue. Explaining clearly how operators can use an
additional local classifiers (see ) is intended to remove any
motivation to bleach the L4S identifier. Then at least the L4S ECN
identifier will be more likely to survive end-to-end even though the
service may not be supported at every hop. Such local arrangements
would only require simple registered/not-registered packet
classification, rather than the managed, application-specific traffic
policing against customer-specific traffic contracts that Diffserv
uses.Like the Classic service, the L4S service relies on self-constraint
- limiting rate in response to congestion. In addition, the L4S
service requires self-constraint in terms of limiting latency
(burstiness). It is hoped that self-interest and guidance on dynamic
behaviour (especially flow start-up, which might need to be
standardized) will be sufficient to prevent transports from sending
excessive bursts of L4S traffic, given the application's own latency
will suffer most from such behaviour.Whether burst policing becomes necessary remains to be seen.
Without it, there will be potential for attacks on the low latency of
the L4S service.If needed, various arrangements could be used to address this
concern:A per-flow
(5-tuple) queue protection function 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.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.Per-flow
scheduling should inherently isolate non-bursty flows from bursty
(see for discussion of the merits
of per-flow scheduling relative to per-flow policing).Per-flow
queue protection could be arranged for a queue structure
distributed across a subnet inter-communicating using lower layer
control messages (see Section 2.1.4 of ). 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.The
Congestion Exposure (ConEx) architecture which uses egress audit to motivate senders to
truthfully signal path congestion in-band where it can be used by
ingress policers. An edge-to-edge variant of this architecture is
also possible.An
architecture similar to Diffserv may
be preferred, where traffic is proactively conditioned on entry to
a domain, rather than reactively policed only if it is leads to
queuing once combined with other traffic at a bottleneck.The
policing function could be divided between per-flow mechanisms at
the network ingress that characterize the burstiness of each flow
into a signal carried with the traffic, and per-class mechanisms
at bottlenecks that act on these signals if queuing actually
occurs once the traffic converges. This would be somewhat similar
to the idea behind core stateless fair queuing, which is in turn
similar to .None of these possible queue protection capabilities are considered
a necessary part of the L4S architecture, which works without them (in
a similar way to how the Internet works without per-flow rate
policing). Indeed, under normal circumstances, latency policers would
not intervene, and if operators found they were not necessary they
could disable them. Part of the L4S experiment will be to see whether
such a function is necessary, and which arrangements are most
appropriate to the size of the problem.As mentioned in , L4S should remove
the need for low latency Diffserv classes. However, those Diffserv
classes that give certain applications or users priority over
capacity, would still be applicable in certain scenarios
(e.g. corporate networks). Then, within such Diffserv classes,
L4S would often be applicable to give traffic low latency and low loss
as well. Within such a Diffserv class, the bandwidth available to a
user or application is often limited by a rate policer. Similarly, in
the default Diffserv class, rate policers are used to partition shared
capacity.A classic rate policer drops any packets exceeding a set rate,
usually also giving a burst allowance (variants exist where the
policer re-marks non-compliant traffic to a discard-eligible Diffserv
codepoint, so they may be dropped elsewhere during contention).
Whenever L4S traffic encounters one of these rate policers, it will
experience drops and the source will have to fall back to a Classic
congestion control, thus losing the benefits of L4S (). So, in networks that already use
rate policers and plan to deploy L4S, it will be preferable to
redesign these rate policers to be more friendly to the L4S
service.L4S-friendly rate policing is currently a research area (note that
this is not the same as latency policing). It might be achieved by
setting a threshold where ECN marking is introduced, such that it is
just under the policed rate or just under the burst allowance where
drop is introduced. This could be applied to various types of rate
policer, e.g. ,
or the 'local' (non-ConEx) variant of the ConEx congestion
policer . 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 .Receiving hosts can fool a sender into downloading faster by
suppressing feedback of ECN marks (or of losses if retransmissions are
not necessary or available otherwise). Various ways to protect
transport feedback integrity have been developed. For instance:The sender can test the integrity of the receiver's feedback by
occasionally setting the IP-ECN field to the congestion
experienced (CE) codepoint, which is normally only set by a
congested link. Then the sender can test whether the receiver's
feedback faithfully reports what it expects (see 2nd para of
Section 20.2 of ).A network can enforce a congestion response to its ECN markings
(or packet losses) by auditing congestion exposure
(ConEx) .The TCP authentication option (TCP-AO ) can be used to detect tampering with TCP
congestion feedback.The ECN Nonce was proposed to
detect tampering with congestion feedback, but it has been
reclassified as historic .Appendix C.1 of gives
more details of these techniques including their applicability and
pros and cons.As discussed in , the L4S
architecture does not preclude approaches that inspect end-to-end
transport layer identifiers. For instance it is simple to add L4S
support to FQ-CoDel, which classifies by application flow ID in the
network. However, the main innovation of L4S is the DualQ AQM
framework that does not need to inspect any deeper than the outermost
IP header, because the L4S identifier is in the IP-ECN field.Thus, the L4S architecture enables ultra-low queuing delay without
requiring inspection of information above
the IP layer. This means that users who want to encrypt application
flow identifiers, e.g. in IPSec or other encrypted VPN tunnels,
don't have to sacrifice low delay .Because L4S can provide low delay for a broad set of applications
that choose to use it, there is no need for individual applications or
classes within that broad set to be distinguishable in any way while
traversing networks. This removes much of the ability to correlate
between the delay requirements of traffic and other identifying
features . 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.Thanks to Richard Scheffenegger, Wes Eddy, Karen Nielsen, David Black
and Jake Holland for their useful review comments.Bob Briscoe and Koen De Schepper were part-funded by the European
Community under its Seventh Framework Programme through the Reducing
Internet Transport Latency (RITE) project (ICT-317700). Bob Briscoe was
also part-funded by the Research Council of Norway through the TimeIn
project, partly by CableLabs and partly by the Comcast Innovation Fund.
The views expressed here are solely those of the authors.A QoE Perspective on Sizing Network BuffersRelentless Congestion ControlPSC`Data Centre to the Home': Ultra-Low Latency for AllNokia Bell LabsSimula Research LabBTNokia Bell LabsScaling TCP's Congestion Window for Small Round Trip
TimesBTBell LabsExperimental Specification of New Congestion Control
AlgorithmsNokia Research CentreorderedUltra-Low Delay for All: Live Experience, Live
AnalysisSimula Research LabBell LabsBell LabsBTCongestion Avoidance and ControlImplementing immediate forwarding for 4G in a network
simulatorImplementing the `TCP Prague' Requirements for Low Latency
Low Loss Scalable Throughput (L4S)IndependentNokia Bell LabsSimula Research LabSimula Research LabNokia Bell LabsETH ZurichSimula Research LabDUALPI2 - Low Latency, Low Loss and Scalable (L4S)
AQMSimula Research LabNokia Bell LabsIndependentNokia Bell LabsSimula Research LabMAC and Upper Layer Protocols Interface (MULPI)
Specification, CM-SP-MULPIv3.1CableLabsTowards fair and low latency next generation high speed
networks: AFCD queuingA Congestion Control Independent L4S SchedulerRapid Signalling of Queue Dynamicsbobbriscoe.net LtdUNIX Time-Sharing System: ForewordCharacterising LEDBAT Performance Through Bottlenecks Using
PIE, FQ-CoDel and FQ-PIE Active Queue ManagementThe following table includes all the items that will need to be
standardized to provide a full L4S architecture.The table is too wide for the ASCII draft format, so it has been
split into two, with a common column of row index numbers on the
left.The columns in the second part of the table have the following
meanings:The IETF WG most relevant to this requirement. The
"tcpm/iccrg" combination refers to the procedure typically used for
congestion control changes, where tcpm owns the approval decision,
but uses the iccrg for expert review ;Applicable to all forms of TCP congestion
control;Applicable to Data Center TCP as currently used
(in controlled environments);Applicable to any future Data Center TCP
congestion control intended for controlled environments;Applicable to a Scalable variant of XXX
(TCP/SCTP/RMCAT) congestion control.Req #RequirementReference0ARCHITECTURE1L4S IDENTIFIER2DUAL QUEUE AQM3Suitable ECN Feedback, .SCALABLE TRANSPORT - SAFETY ADDITIONS4-1Fall back to Reno/Cubic on loss S.2.3, 4-2Fall back to Reno/Cubic if classic ECN bottleneck detected S.2.34-3Reduce RTT-dependence S.2.34-4Scaling TCP's Congestion Window for Small Round Trip Times S.2.3, SCALABLE TRANSPORT - PERFORMANCE ENHANCEMENTS5-1Setting ECT in TCP Control Packets and Retransmissions5-2Faster-than-additive increase (Appx A.2.2)5-3Faster Convergence at Flow Start (Appx A.2.2)#WGTCPDCTCPDCTCP-bisTCP PragueSCTP PragueRMCAT Prague0tsvwgYYYYYY1tsvwgYYYY2tsvwgn/an/an/an/an/an/a3tcpmYYYYn/an/a4-1tcpmYYYYY4-2tcpm/ iccrg?YY?4-3tcpm/ iccrg?YYY?4-4tcpmYYYYY?5-1tcpmYYYYn/an/a5-2tcpm/ iccrg?YYY?5-3tcpm/ iccrg?YYY?