One document matched: draft-briscoe-tsvwg-aqm-dualq-coupled-00.xml
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<rfc category="exp" docName="draft-briscoe-tsvwg-aqm-dualq-coupled-00"
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<!-- ***** FRONT MATTER ***** -->
<front>
<!-- The abbreviated title is used in the page header - it is only necessary if the
full title is longer than 39 characters -->
<title abbrev="DualQ Coupled AQM">DualQ Coupled AQM for Low Latency, Low
Loss and Scalable Throughput</title>
<author fullname="Koen De Schepper" initials="K." surname="De Schepper">
<organization>Nokia Bell Labs</organization>
<address>
<postal>
<street/>
<city>Antwerp</city>
<country>Belgium</country>
</postal>
<email>koen.de_schepper@nokia.com</email>
<uri>https://www.bell-labs.com/usr/koen.de_schepper</uri>
</address>
</author>
<author fullname="Bob Briscoe" initials="B." role="editor"
surname="Briscoe">
<organization>Simula Research Lab</organization>
<address>
<postal>
<street/>
</postal>
<email>ietf@bobbriscoe.net</email>
<uri>http://bobbriscoe.net/</uri>
</address>
</author>
<author fullname="Olga Bondarenko" initials="O." surname="Bondarenko">
<organization>Simula Research Lab</organization>
<address>
<postal>
<street/>
<city>Lysaker</city>
<country>Norway</country>
</postal>
<email>olgabnd@gmail.com</email>
<uri>https://www.simula.no/people/olgabo</uri>
</address>
</author>
<author fullname="Ing-jyh Tsang" initials="I." surname="Tsang">
<organization>Nokia Bell Labs</organization>
<address>
<postal>
<street/>
<city>Antwerp</city>
<country>Belgium</country>
</postal>
<email>ing-jyh.tsang@nokia.com</email>
</address>
</author>
<date day="" month="" year="2016"/>
<area>Transport</area>
<workgroup>Active Queue Management (aqm)</workgroup>
<keyword>Internet-Draft</keyword>
<keyword>I-D</keyword>
<abstract>
<t>Data Centre TCP (DCTCP) was designed to provide predictably low
queuing latency, near-zero loss, and throughput scalability using
explicit congestion notification (ECN) and an extremely simple marking
behaviour on switches. However, DCTCP does not co-exist with existing
TCP traffic---throughput starves. So, until now, DCTCP could only be
deployed where a clean-slate environment could be arranged, such as in
private data centres. This specification defines `DualQ Coupled Active
Queue Management (AQM)' to allow scalable congestion controls like DCTCP
to safely co-exist with classic Internet traffic. The Coupled AQM
ensures that a flow runs at about the same rate whether it uses DCTCP or
TCP Reno/Cubic, but without inspecting transport layer flow identifiers.
When tested in a residential broadband setting, DCTCP achieved
sub-millisecond average queuing delay and zero congestion loss under a
wide range of mixes of DCTCP and `Classic' broadband Internet traffic,
without compromising the performance of the Classic traffic. The
solution also reduces network complexity and eliminates network
configuration.</t>
</abstract>
</front>
<middle>
<section anchor="dualq_intro" title="Introduction">
<t/>
<section anchor="dualq_problem" title="Problem and Scope">
<t>Latency is becoming the critical performance factor for many
(most?) applications on the public Internet, e.g. Web, voice,
conversational video, gaming, finance apps, remote desktop and
cloud-based applications. In the developed world, further increases in
access network bit-rate offer diminishing returns, whereas latency is
still a multi-faceted problem. In the last decade or so, much has been
done to reduce propagation time by placing caches or servers closer to
users. However, queuing remains a major component of latency.</t>
<t>The Diffserv architecture provides Expedited Forwarding <xref
target="RFC3246"/>, so that low latency traffic can jump the queue of
other traffic. However, on access links dedicated to individual sites
(homes, small enterprises or mobile devices), often all traffic at any
one time will be latency-sensitive. Then Diffserv is of little use.
Instead, we need to remove the causes of any unnecessary delay.</t>
<t>The bufferbloat project has shown that excessively-large buffering
(`bufferbloat') has been introducing significantly more delay than the
underlying propagation time. These delays appear only
intermittently—only when a capacity-seeking (e.g. TCP) flow is
long enough for the queue to fill the buffer, making every packet in
other flows sharing the buffer sit through the queue.</t>
<t>Active queue management (AQM) was originally developed to solve
this problem (and others). Unlike Diffserv, which gives low latency to
some traffic at the expense of others, AQM controls latency for <spanx
style="emph">all</spanx> traffic in a class. In general, AQMs
introduce an increasing level of discard from the buffer the longer
the queue persists above a shallow threshold. This gives sufficient
signals to capacity-seeking (aka. greedy) flows to keep the buffer
empty for its intended purpose: absorbing bursts. However,
RED <xref target="RFC2309"/> and other algorithms from the 1990s
were sensitive to their configuration and hard to set correctly. So,
AQM was not widely deployed.</t>
<t>More recent state-of-the-art AQMs, e.g. fq_CoDel <xref
target="I-D.ietf-aqm-fq-codel"/>, PIE <xref
target="I-D.ietf-aqm-pie"/>, Adaptive RED <xref
target="ARED01"/>, are easier to configure, because they define the
queuing threshold in time not bytes, so it is invariant for different
link rates. However, no matter how good the AQM, the sawtoothing rate
of TCP will either cause queuing delay to vary or cause the link to be
under-utilized. Even with a perfectly tuned AQM, the additional
queuing delay will be of the same order as the underlying
speed-of-light delay across the network. Flow-queuing can isolate one
flow from another, but it cannot isolate a TCP flow from the delay
variations it inflicts on itself, and it has other problems - it
overrides the flow rate decisions of variable rate video applications,
it does not recognise the flows within IPSec VPN tunnels and it is
relatively expensive to implement.</t>
<t>It seems that further changes to the network alone will now yield
diminishing returns. Data Centre TCP (DCTCP <xref
target="I-D.ietf-tcpm-dctcp"/>) teaches us that a small but radical
change to TCP is needed to cut two major outstanding causes of queuing
delay variability: <list counter="ctr:problem" style="format %d.">
<t>the `sawtooth' varying rate of TCP itself;</t>
<t>the smoothing delay deliberately introduced into AQMs to permit
bursts without triggering losses.</t>
</list>The former causes a flow's round trip time (RTT) to vary from
about 1 to 2 times the base RTT between the machines in question. The
latter delays the system's response to change by a worst-case
(transcontinental) RTT, which could be hundreds of times the actual
RTT of typical traffic from localized CDNs.</t>
<t>Latency is not our only concern:<list counter="ctr:problem"
style="format %d.">
<t>It was known when TCP was first developed that it would not
scale to high bandwidth-delay products.</t>
</list>Given regular broadband bit-rates over WAN distances are
already <xref target="RFC3649"/> beyond the scaling range of
`classic' TCP Reno, `less unscalable' Cubic <xref
target="I-D.ietf-tcpm-cubic"/> and Compound <xref
target="I-D.sridharan-tcpm-ctcp"/> variants of TCP have been
successfully deployed. However, these are now approaching their
scaling limits. Unfortunately, fully scalable TCPs such as DCTCP cause
`classic' TCP to starve itself, which is why they have been confined
to private data centres or research testbeds (until now).</t>
<t>This document specifies a `DualQ Coupled AQM' extension that solves
the problem of coexistence between scalable and classic flows, without
having to inspect flow identifiers. The AQM is not like flow-queuing
approaches <xref target="I-D.ietf-aqm-fq-codel"/> that classify
packets by flow identifier into numerous separate queues in order to
isolate sparse flows from the higher latency in the queues assigned to
heavier flow. In contrast, the AQM exploits the behaviour of scalable
congestion controls like DCTCP so that every packet in every flow
sharing the queue for DCTCP-like traffic can be served with very low
latency.</t>
<t>This AQM extension can be combined with any single qeueu AQM that
generates a statistical or deterministic mark/drop probability driven
by the queue dynamics. In many cases it simplifies the basic control
algorithm, and requires little extra processing. Therefore it is
believed the Coupled AQM would be applicable and easy to deploy in all
types of buffers; buffers in cost-reduced mass-market residential
equipment; buffers in end-system stacks; buffers in carrier-scale
equipment including remote access servers, routers, firewalls and
Ethernet switches; buffers in network interface cards, buffers in
virtualized network appliances, hypervisors, and so on.</t>
<t>The supporting papers <xref target="PI216"/> and <xref
target="DCttH15"/> give the full rationale for the AQM's design, both
discursively and in more precise mathematical form.</t>
</section>
<section anchor="dualq_Terminology" title="Terminology">
<t>The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in <xref
target="RFC2119"/>. In this document, these words will appear with
that interpretation only when in ALL CAPS. Lower case uses of these
words are not to be interpreted as carrying RFC-2119 significance.</t>
<t>The DualQ Coupled AQM uses two queues for two services. Each of the
following terms identifies both the service and the queue that
provides the service:<list style="hanging">
<t hangText="Classic (denoted by subscript C):">The `Classic'
service is intended for all the behaviours that currently co-exist
with TCP Reno (TCP Cubic, Compound, SCTP, etc).</t>
<t
hangText="Low-Latency, Low-Loss and Scalable (L4S, denoted by subscript L):">The
`L4S' service is intended for a set of congestion controls with
scalable properties such as DCTCP (e.g. Relentless <xref
target="Mathis09"/>).</t>
</list></t>
<t>Either service can cope with a proportion of unresponsive or
less-responsive traffic as well (e.g. DNS, VoIP, etc), just as a
single queue AQM can. The DualQ Coupled AQM behaviour is similar to a
single FIFO queue with respect to unresponsive and overload
traffic.</t>
</section>
<section title="Features">
<t>The AQM couples marking and/or dropping across the two queues such
that a flow will get roughly the same throughput whichever it uses.
Therefore both queues can feed into the full capacity of a link and no
rates need to be configured for the queues. The L4S queue enables
scalable congestion controls like DCTCP to give stunningly low and
predictably low latency, without compromising the performance of
competing 'Classic' Internet traffic. Thousands of tests have been
conducted in a typical fixed residential broadband setting. Typical
experiments used base round trip delays up to 100ms between the data
centre and home network, and large amounts of background traffic in
both queues. For every L4S packet, the AQM kept the average queuing
delay below 1ms (or 2 packets if serialization delay is bigger for
slow links), and no losses at all were introduced by the AQM. Details
of the extensive experiments will be made available <xref
target="PI216"/> <xref target="DCttH15"/>.</t>
<t>Subjective testing was also conducted using a demanding panoramic
interactive video application run over a stack with DCTCP enabled and
deployed on the testbed. Each user could pan or zoom their own high
definition (HD) sub-window of a larger video scene from a football
match. Even though the user was also downloading large amounts of L4S
and Classic data, latency was so low that the picture appeared to
stick to their finger on the touchpad (all the L4S data achieved the
same ultra-low latency). With an alternative AQM, the video noticeably
lagged behind the finger gestures.</t>
<t>Unlike Diffserv Expedited Forwarding, the L4S queue does not have
to be limited to a small proportion of the link capacity in order to
achieve low delay. The L4S queue can be filled with a heavy load of
capacity-seeking flows like DCTCP and still achieve low delay. The L4S
queue does not rely on the presence of other traffic in the Classic
queue that can be 'overtaken'. It gives low latency to L4S traffic
whether or not there is Classic traffic, and the latency of Classic
traffic does not suffer when a proportion of the traffic is L4S. The
two queues are only necessary because DCTCP-like flows cannot keep
latency predictably low and keep utilization high if they are mixed
with legacy TCP flows,</t>
<t>The experiments used the Linux implementation of DCTCP that is
deployed in private data centres, without any modification despite its
known deficiencies. Nonetheless, certain modifications will be
necessary before DCTCP is safe to use on the Internet, which are
recorded for now in Appendix A of <xref
target="I-D.briscoe-tsvwg-aqm-tcpm-rmcat-l4s-problem"/>. However, the
focus of this specification is to get the network service in place.
Then, without any management intervention, applications can exploit it
by migrating to scalable controls like DCTCP, which can then evolve
<spanx style="emph">while</spanx> their benefits are being enjoyed by
everyone on the Internet.</t>
</section>
</section>
<section anchor="dualq_algo" title="DualQ Coupled AQM Algorithm">
<t>There are two main aspects to the algorithm:<list style="symbols">
<t>the Coupled AQM that addresses throughput equivalence between
Classic (e.g. Reno, Cubic) flows and L4S (e.g. DCTCP) flows</t>
<t>the Dual Queue structure that provides latency separation for L4S
flows to isolate them from the typically large Classic queue.</t>
</list></t>
<section anchor="dualq_coupled" title="Coupled AQM">
<t>In the 1990s, the `TCP formula' was derived for the relationship
between TCP's congestion window, cwnd, and its drop probability, p. To
a first order approximation, cwnd of TCP Reno is inversely
proportional to the square root of p. TCP Cubic implements a
Reno-compatibility mode, which is the only relevant mode for typical
RTTs under 20ms, while the throughput of a single flow is less than
about 500Mb/s. Therefore we can assume that Cubic traffic behaves
similar to Reno (but with a slightly different constant of
proportionality), and we shall use the term 'Classic' for the
collection of Reno and Cubic in Reno mode.</t>
<t>In our supporting paper <xref target="PI216"/>, we derive the
equivalent rate equation for DCTCP, for which cwnd is inversely
proportional to p (not the square root), where in this case p is the
ECN marking probability. DCTCP is not the only congestion control that
behaves like this, so we use the term 'L4S' traffic for all similar
behaviour.</t>
<t>In order to make a DCTCP flow run at roughly the same rate as a
Reno TCP flow (all other factors being equal), we make the drop or
marking probability for Classic traffic, p_C distinct from the marking
probability for L4S traffic, p_L (in contrast to RFC3168 which
requires them to be the same). We make the Classic drop probability
p_C proportional to the square of the L4S marking probability p_L.
This is because we need to make the Reno flow rate equal the DCTCP
flow rate, so we have to square the square root of p_C in the Reno
rate equation to make it the same as the straight p_L in the DCTCP
rate equation.</t>
<t>There is a really simple way to implement the square of a
probability - by testing the queue against two random numbers not one.
This is the approach adopted in <xref target="dualq_Ex_algo_pi2"/> and
<xref target="dualq_Ex_algo"/>.</t>
<t>Stating this as a formula, the relation between Classic drop
probability, p_C, and L4S marking probability, p_L needs to take the
form:<figure>
<artwork><![CDATA[ p_C = ( p_L / k )^2 (1)]]></artwork>
</figure></t>
<t>where k is the constant of proportionality. Optionally, k can be
expressed as a power of 2, so k=2^k', where k' is another constant.
Then implementations can avoid costly division by shifting p_L by k'
bits to the right.</t>
</section>
<section title="Dual Queue">
<t>Classic traffic builds a large queue, so a separate queue is
provided for L4S traffic, and it is scheduled with strict priority.
Nonetheless, coupled marking ensures that giving priority to L4S
traffic still leaves the right amount of spare scheduling time for
Classic flows to each get equivalent throughput to DCTCP flows (all
other factors such as RTT being equal). The algorithm achieves this
without having to inspect flow identifiers.</t>
</section>
<section title="Traffic Classification">
<t>Both the Coupled AQM and DualQ mechanisms need an identifier to
distinguish L4S and C packets. A separate draft <xref
target="I-D.briscoe-tsvwg-ecn-l4s-id"/> recommends using the ECT(1)
codepoint of the ECN field as this identifier, having assessed various
alternatives.</t>
<t>Given L4S work is currently on the experimental track, but the
definition of the ECN field is on the standards track <xref
target="RFC3168"/>, another standards track document has proved
necessary to make the ECT(1) codepoint available for experimentation
<xref target="I-D.black-tsvwg-ecn-experimentation"/>.</t>
</section>
<section anchor="dualq_norm_reqs" title="Normative Requirements">
<t>In the Dual Queue, L4S packets MUST be given priority over Classic,
although strict priority MAY not be appropriate.</t>
<!--The above may need to be changed if/when L2S is specified.-->
<t>All L4S traffic MUST be ECN-capable, although some Classic traffic
MAY also be ECN-capable.</t>
<t>Whatever identifier is used for L4S traffic, it will still be
necessary to agree on the meaning of an ECN marking on L4S traffic,
relative to a drop of Classic traffic. In order to prevent starvation
of Classic traffic by scalable L4S traffic (e.g. DCTCP) the drop
probability of Classic traffic MUST be proportional to the square of
the marking probability of L4S traffic, In other words, the power to
which p_L is raised in Eqn. (1) MUST be 2.</t>
<t>The constant of proportionality, k, in Eqn (1) determines the
relative flow rates of Classic and L4S flows when the AQM concerned is
the bottleneck (all other factors being equal). k does not have to be
standardized because differences do not prevent interoperability.
However, k has to take some value, and each operator can make that
choice.</t>
<t>A value of k=2 is currently RECOMMENDED as the default for Internet
access networks. Assuming scalable congestion controls for the
Internet will be as aggressive as DCTCP, this will ensure their
congestion window will be roughly the same as that of a standards
track TCP congestion control (Reno) <xref target="RFC5681"/> and other
so-called TCP-friendly controls such as TCP Cubic in its TCP-friendly
mode.</t>
<t>The requirements for scalable congestion controls on the Internet
(termed the TCP Prague requirements) are only in initial draft form
<xref target="I-D.briscoe-tsvwg-aqm-tcpm-rmcat-l4s-problem"/> and
subject to change. If the aggressiveness of DCTCP is not defined as
the benchmark for scalable controls on the Internet, the recommended
value of k will also be subject to change.</t>
<t>Whatever value is recommended, the choice of k is a matter of
operator policy, and operators MAY choose a different value using
<xref target="dualq_tab_k_policy"/> and the guidelines in <xref
target="dualq_Choosing_k"/>.</t>
<t>Typically, access network operators isolate customers from each
other with some form of layer-2 multiplexing (TDM in DOCSIS, CDMA in
3G) or L3 scheduling (WRR in broadband), rather than relying on TCP to
share capacity between customers <xref target="RFC0970"/>. In such
cases, the choice of k will solely affect relative flow rates within
each customer's access capacity, not between customers. Also, k will
not affect relative flow rates at any times when all flows are Classic
or all L4S, and it will not affect small flows.</t>
<t>Example DualQ Coupled AQM algorithms called PI2 and Curvy RED are
given in <xref target="dualq_Ex_algo_pi2"/> and <xref
target="dualq_Ex_algo"/>. Either example AQM can be used to couple
packet marking and dropping across a dual Q. Curvy RED requires less
operations per packet than RED and can be used if the range of RTTs is
limited. PI2 is a simplification of PIE with stable
Proportional-Integral control for both Classic and L4S congestion
controls. Nonetheless, it would be possible to control the queues with
other alternative AQMs, as long as the above normative requirements
(those expressed in capitals) are observed, which are intended to be
independent of the specific AQM.</t>
<t>{ToDo: Add management and monitoring requirements}</t>
</section>
</section>
<section anchor="dualq_IANA" title="IANA Considerations">
<t>This specification contains no IANA considerations.</t>
</section>
<section anchor="dualq_Security_Considerations"
title="Security Considerations">
<t/>
<section anchor="dualq_Overload" title="Overload Handling">
<t>Where the interests of users or flows might conflict, it could be
necessary to police traffic to isolate any harm to performance. This
is a policy issue that needs to be separable from a basic AQM, but an
AQM does need to handle overload. A trade-off needs to be made between
complexity and the risk of either class harming the other. It is an
operator policy to define what must happen if the service time of the
classic queue becomes too great. In the following subsections three
optional non-exclusive overload protections are defined. Their
objective is for the overload behaviour of the DualQ AQM to be similar
to a single queue AQM. The example implementation in <xref
target="dualq_Ex_algo_pi2"/> implements the 'delay on overload'
policy. Other overload protections can be envisaged:<list
style="hanging">
<t anchor="dualq_Minimum_Service"
hangText="Minimum throughput service: ">By replacing the priority
scheduler with a weighted round robin scheduler, a minimum
throughput service can be guaranteed for Classic traffic.
Typically the scheduling weight of the Classic queue will be small
(e.g. 5%) to avoid interference with the coupling but big enough
to avoid complete starvation of Classic traffic.</t>
<t anchor="dualq_Delay_Overload" hangText="Delay on overload:">To
control milder overload of responsive traffic, particularly when
close to the maximum congestion signal, delay can be used as an
alternative congestion control mechanism. The Dual Queue Coupled
AQM can be made to behave like a single First-In First-Out (FIFO)
queue with different service times by replacing the priority
scheduler with a very simple scheduler that could be called a
"time-shifted FIFO", which is the same as the Modifier Earliest
Deadline First (MEDF) scheduler of <xref target="MEDF"/>. The
scheduler adds T_m to the queue delay of the next L4S packet,
before comparing it with the queue delay of the next Classic
packet, then it selects the packet with the greater adjusted queue
delay. Under regular conditions, this time-shifted FIFO scheduler
behaves just like a strict priority scheduler. But under moderate
or high overload it prevents starvation of the Classic queue,
because the time-shift defines the maximum extra queuing delay
(T_m) of Classic packets relative to L4S.</t>
<t anchor="dualq_Drop_Overload" hangText="Drop on overload:">On
severe overload, e.g. due to non responsive traffic, queues will
typically overflow and packet drop will be unavoidable. It is
important to avoid unresponsive ECN traffic (either Classic or
L4S) driving the AQM to 100% drop and mark probability. Congestion
controls that have a minimum congestion window will become
unresponsive to ECN marking when the marking probability is high.
This situation can be avoided by applying the drop probability to
all packets of all traffic types when it exceeds a certain
threshold or by limiting the drop and marking probabilities to a
lower maximum value (up to where fairnes between the different
traffic types is still guaranteed) and rely on delay to control
temporary high congestion and eventually queue overflow. If the
classic drop probability is applied to all types of traffic when
it is higher than a threshold probability the queueing delay can
be controlled up to any overload situation, and no further
measures are required. If a maximum classic and coupled L4S
probability of less than 100% is used, both queues need scheduling
opportunities and should eventually experience drop. This can be
achieved with a scheduler that guarantees a minimum throughput for
each queue, such as a weighted round robin or time-shifted FIFO
scheduler. In that case a common queue limit can be configured
that will drop packets of both types of traffic.</t>
</list>To keep the throughput of both L4S and Classic flows equal
over the full load range, a different control strategy needs to be
defined above the point where one congestion control first saturates
to a probability of 100% (if k>1, L4S will saturate first).
Possible strategies include: also dropping L4S; increasing the
queueing delay for both; or ensuring that L4S traffic still responds
to marking below a window of 2 segments (see Appendix A of <xref
target="I-D.briscoe-tsvwg-aqm-tcpm-rmcat-l4s-problem"/>).</t>
</section>
</section>
<section title="Acknowledgements">
<t>Thanks to Anil Agarwal for detailed review comments and suggestions
on how to make our explanation clearer.</t>
<t>The authors' contributions are part-funded by the European Community
under its Seventh Framework Programme through the Reducing Internet
Transport Latency (RITE) project (ICT-317700). The views expressed here
are solely those of the authors.</t>
</section>
</middle>
<!-- *****BACK MATTER ***** -->
<back>
<references title="Normative References">
<?rfc include='reference.RFC.2119'?>
</references>
<references title="Informative References">
<?rfc include='reference.RFC.0970'?>
<?rfc include='reference.RFC.2309'?>
<?rfc include='reference.RFC.3246'?>
<?rfc include='reference.RFC.3168'?>
<?rfc include='reference.RFC.3649'?>
<?rfc include='reference.RFC.5681'?>
<?rfc include='reference.I-D.ietf-aqm-pie'?>
<?rfc include='reference.I-D.ietf-aqm-fq-codel'?>
<reference anchor="ARED01" target="http://www.icir.org/floyd/red.html">
<front>
<title>Adaptive RED: An Algorithm for Increasing the Robustness of
RED's Active Queue Management</title>
<author fullname="Sally Floyd" initials="S." surname="Floyd">
<organization>ACIRI</organization>
</author>
<author fullname="Ramakrishna Gummadi" initials="R."
surname="Gummadi">
<organization>ACIRI</organization>
</author>
<author fullname="S. Shenker" initials="S." surname="Shenker">
<organization>ACIRI</organization>
</author>
<date month="August" year="2001"/>
</front>
<seriesInfo name="ACIRI Technical Report" value=""/>
<format target="http://www.icir.org/floyd/red.html" type="PDF"/>
</reference>
<?rfc include='reference.I-D.ietf-tcpm-dctcp'?>
<?rfc include='reference.I-D.ietf-tcpm-cubic'?>
<?rfc include='reference.I-D.sridharan-tcpm-ctcp'?>
<?rfc include='reference.I-D.briscoe-tsvwg-ecn-l4s-id'?>
<?rfc include='reference.I-D.black-tsvwg-ecn-experimentation'?>
<?rfc include='reference.I-D.briscoe-tsvwg-aqm-tcpm-rmcat-l4s-problem'?>
<reference anchor="Mathis09"
target="http://www.hpcc.jp/pfldnet2009/Program_files/1569198525.pdf">
<front>
<title>Relentless Congestion Control</title>
<author fullname="Matt Mathis" initials="M." surname="Mathis">
<organization>PSC</organization>
</author>
<date month="May" year="2009"/>
</front>
<seriesInfo name="PFLDNeT'09" value=""/>
<format target="http://www.hpcc.jp/pfldnet2009/Program_files/1569198525.pdf"
type="PDF"/>
</reference>
<!--{ToDo: DCttH ref will need to be updated, once stable}-->
<reference anchor="DCttH15"
target="http://www.bobbriscoe.net/projects/latency/dctth_preprint.pdf">
<front>
<title>`Data Centre to the Home': Ultra-Low Latency for All</title>
<author fullname="Koen De Schepper" initials="K."
surname="De Schepper">
<organization>Nokia Bell Labs</organization>
</author>
<author fullname="Olga Bondarenko" initials="O."
surname="Bondarenko">
<organization>Simula Research Lab</organization>
</author>
<author fullname="Bob Briscoe" initials="B." surname="Briscoe">
<organization>BT</organization>
</author>
<author fullname="Ing-jyh Tsang" initials="I." surname="Tsang">
<organization>Nokia Bell Labs</organization>
</author>
<date year="2015"/>
</front>
<annotation>(Under submission)</annotation>
</reference>
<reference anchor="PI216"
target="https://riteproject.files.wordpress.com/2015/10/pi2_conext.pdf">
<front>
<title>PI2: A Linearized AQM for both Classic and Scalable
TCP</title>
<author fullname="Koen De Schepper" initials="K."
surname="De Schepper">
<organization>Nokia Bell Labs</organization>
</author>
<author fullname="Olga Bondarenko" initials="O."
surname="Bondarenko">
<organization>Simula Research Lab</organization>
</author>
<author fullname="Bob Briscoe" initials="B." surname="Briscoe">
<organization>BT</organization>
</author>
<author fullname="Ing-jyh Tsang" initials="I." surname="Tsang">
<organization>Nokia Bell Labs</organization>
</author>
<date month="December" year="2016"/>
</front>
<seriesInfo name="ACM CoNEXT'16" value=""/>
<format type="https://riteproject.files.wordpress.com/2015/10/pi2_conext.pdf"/>
<annotation>(To appear)</annotation>
</reference>
<!-- <reference anchor="DCTCP_Pitfalls"
target="http://blogs.usenix.org/conference/nsdi15/technical-sessions/presentation/judd">
<front>
<title>Attaining the Promise and Avoiding the Pitfalls of TCP in the
Datacenter</title>
<author fullname="Glenn Judd" initials="G." surname="Judd">
<organization>Morgan Stanley</organization>
</author>
<date month="May" year="2015"/>
</front>
<seriesInfo name="12th USENIX Symposium on Networked Systems Design and Implementation (NSDI 15)"
value="145-157"/>
<format target="http://blogs.usenix.org/conference/nsdi15/technical-sessions/presentation/judd"
type="PDF"/>
</reference>
-->
<reference anchor="CRED_Insights"
target="http://www.bobbriscoe.net/projects/latency/credi_tr.pdf">
<front>
<title>Insights from Curvy RED (Random Early Detection)</title>
<author fullname="Bob Briscoe" initials="B." surname="Briscoe">
<organization>BT</organization>
</author>
<date day="" month="July" year="2015"/>
</front>
<seriesInfo name="BT Technical Report" value="TR-TUB8-2015-003"/>
<format target="http://www.bobbriscoe.net/projects/latency/credi_tr.pdf"
type="PDF"/>
</reference>
<reference anchor="CoDel"
target="http://queue.acm.org/issuedetail.cfm?issue=2208917">
<front>
<title>Controlling Queue Delay</title>
<author fullname="Kathleen Nichols" initials="K." surname="Nichols">
<organization>PARC</organization>
</author>
<author fullname="Van Jacobson" initials="V." surname="Jacobson">
<organization>Pollere Inc</organization>
</author>
<date month="May" year="2012"/>
</front>
<seriesInfo name="ACM Queue" value="10(5)"/>
<format target="http://queue.acm.org/issuedetail.cfm?issue=2208917"
type="HTML"/>
</reference>
<reference anchor="MEDF">
<front>
<title>MEDF - a simple scheduling algorithm for two real-time
transport service classes with application in the UTRAN</title>
<author fullname="Michael Menth " initials="M." surname="Menth">
<organization>University of Wuerzburg</organization>
</author>
<author fullname="Matthias Schmid " initials="M." surname="Schmid">
<organization>Infosim AG</organization>
</author>
<author fullname="Herbert Heiss" initials="H." surname="Heiss">
<organization>Siemens</organization>
</author>
<author fullname="Thomas Reim" initials="T." surname="Reim">
<organization>Siemens</organization>
</author>
<date month="March" year="2003"/>
</front>
<seriesInfo name="Proc. IEEE Conference on Computer Communications (INFOCOM'03)"
value="Vol.2 pp.1116-1122"/>
<format target="http://infocom2003.ieee-infocom.org/papers/27_04.PDF"
type="PDF"/>
</reference>
</references>
<section anchor="dualq_Ex_algo_pi2"
title="Example DualQ Coupled PI2 Algorithm">
<t>As a first concrete example, the pseudocode below gives the DualQ
Coupled AQM algorithm based on the PI2 Classic AQM, we used and tested.
For this example only the pseudo code is given. An open source
implementation for Linux is available at:
https://github.com/olgabo/dualpi2.</t>
<figure anchor="dualq_fig_Algo_pi2_enqueue"
title="Example Enqueue Pseudocode for DualQ Coupled PI2 AQM">
<artwork><![CDATA[1: dualpi2_enqueue(lq, cq, pkt) { % Test limit and classify lq or cq
2: stamp(pkt) % attach arrival time to packet
3: if ( lq.len() + cq.len() > limit )
4: drop(pkt) % drop packet if q is full
5: else {
6: if ( ecn(pkt) modulo 2 == 0 ) % ECN bits = not-ect or ect(0)
7: cq.enqueue(pkt)
8: else % ECN bits = ect(1) or ce
9: lq.enqueue(pkt)
10: }
11: }
]]></artwork>
</figure>
<figure anchor="dualq_fig_Algo_pi2_dequeue"
title="Example Dequeue Pseudocode for DualQ Coupled PI2 AQM">
<artwork><![CDATA[1: dualpi2_dequeue(lq, cq) { % Couples L4S & Classic queues, lq & cq
2: while ( lq.len() + cq.len() > 0 )
3: if ( lq.time() + tshift >= cq.time() ) {
4: lq.dequeue(pkt)
5: if ( (pkt.time() > T) or (p > rand()) )
6: mark(pkt)
7: return(pkt) % return the packet and stop here
8: } else {
9: cq.dequeue(pkt)
10: if ( p/k > max(rand(), rand()) ) % same as testing (p/k)^2
11: if ( ecn(pkt) == 0 ) % ECN field = not-ect
12: drop(pkt) % squared drop, redo loop
13: else {
14: mark(pkt) % squared mark
15: return(pkt) % return the packet and stop here
16: }
17: else
18: return(pkt) % return the packet and stop here
19: }
20: }
21: return(NULL) % no packet to dequeue
22: }
]]></artwork>
</figure>
<figure anchor="dualq_fig_Algo_pi2_core"
title="Example PI-Update Pseudocode for DualQ Coupled PI2 AQM">
<artwork><![CDATA[1: dualpi2_update(lq, cq) { % Update p every Tupdate
2: curq = cq.time() % use queuing time of first-in Classic packet
3: alpha_U = alpha * Tupdate % done once when parameters are set
4: beta_U = beta * Tupdate % done once when parameters are set
5: p = p + alpha_U * (curq - target) + beta_U * (curq - prevq)
6: prevq = curq
7: }
]]></artwork>
</figure>
<t>When packets arrive, first a common queue limit is checked as shown
in line 3 of the enqueuing pseudocode in <xref
target="dualq_fig_Algo_pi2_enqueue"/>. Note that the limit is
deliberately tested before enqueue to avoid any bias against larger
packets (so the actual buffer has to be one packet larger than limit).
If limit is not exceeded, the packet will be classified and enqueued to
the Classic or L4S queue dependent on the least significant bit of the
ECN field in the IP header (line 6). Packets with a codepoint having an
LSB of 0 (Not-ECT and ECT(0)) will be enqueued in the Classic queue.
Otherwise, ECT(1) and CE packets will be enqueued in the L4S queue.</t>
<t>The pseudocode in <xref target="dualq_fig_Algo_pi2_dequeue"/>
summarises the per packet dequeue implementation of the DualPI2 code.
Line 3 implements the time-shifted FIFO scheduling. It takes the packet
that waited the longest, biased by a time-shift of tshift for the
Classic traffic. If an L4S packet is scheduled, lines 5 and 6 mark the
packet if either the L4S threshold T is exceeded, or if a random marking
decision is drawn according to the probability p (maintained by the
dualpi2_update() function discussed below). If a Classic packet is
scheduled, lines 10 to 16 drop or mark the packet based on 2 random
decisions resulting in the squared probability (p/k)^2 (hence the name
PI2 for Classic traffic). Note that p is reduced by the factor k here.
This has 2 effects; first the steady state probability is halved as
required to give Classic TCP and DCTCP traffic equal throughput;
secondly, the effect of the dynamic gain parameters alpha and beta are
halved as well, which is also needed give Classic TCP and DCTCP control
the same stability.</t>
<t>The probability p is kept up to date by the core PI algorithm in
<xref target="dualq_fig_Algo_pi2_core"/> which is executed every Tupdate
(<xref target="I-D.ietf-aqm-pie"/> now recommends 16ms, but in our
testing so far we have used the earlier recommendation of 32ms). Note
that p solely depends on the queuing time in the Classic queue. In line
2, the current queuing delay is evaluated by inspecting the timestamp of
the next packet to schedule in the Classic queue. The function cq.time()
subtracts the time stamped at enqueue from the current time and
implicitly takes the current queuing delay as 0 if the queue is empty.
Line 3 and 4 only need to be executed when the configuration parameters
are changed. Alpha and beta in Hz are gain factors per 1 second. If a
briefer update time is configured, alpha_U and beta_U (_U = per Tupdate)
also have to be reduced, to ensure that the same response is given over
time. As such, a smaller Tupdate will only result in a response with
smaller and finer steps, not a more aggressive response. The new
probability is calculated in line 5, where target is the target queuing
delay, as defined in <xref target="I-D.ietf-aqm-pie"/>. In corner cases,
p can overflow the range [0,1] so the resulting value of p has to be
bounded (omitted from the pseudocode). Unlike PIE, alpha_U and beta_U
are not tuned dependent on p, every Tupdate. Instead, in PI2 alpha_U and
beta_U can be constants because the squaring applied to Classic traffic
tunes them inherently, as explained in <xref target="PI216"/>.</t>
<t>In our experiments so far (building on experiments with PIE) on
broadband access links ranging from 4 Mb/s to 200 Mb/s with base RTTs
from 5 ms to 100 ms, PI2 achieves good results with the following
parameters:<list style="empty">
<t>tshift = 40ms</t>
<t>T = max(1ms, serialization time of 2 MTU)</t>
<t>target = 20ms</t>
<t>Tupdate = 32ms</t>
<t>k = 2</t>
<t>alpha = 20Hz (alpha/k = 10Hz for Classic)</t>
<t>beta = 200Hz (beta/k = 100Hz for Classic)</t>
</list></t>
</section>
<section anchor="dualq_Ex_algo"
title="Example DualQ Coupled Curvy RED Algorithm">
<t>As another example, the pseudocode below gives the Curvy RED based
DualQ Coupled AQM algorithm we used and tested. Although we designed the
AQM to be efficient in integer arithmetic, to aid understanding it is
first given using real-number arithmetic. Then, one possible
optimization for integer arithmetic is given, also in pseudocode. To aid
comparison, the line numbers are kept in step between the two by using
letter suffixes where the longer code needs extra lines.</t>
<!--alpha ought to be set once outside the loop.
We need to make this pseudocode consistent with PI2:
-->
<!--a) PI2 tests for L4S packets between Classic drops, while CRED only tests for an L4S packet once it has eventually forwarded a Classic packet.-->
<!-- Easiest way to resolve this would be to copy the structure of PI2, then just replace the lines that actually calculate the marking and dropping.
b) FIXED
PI2 uses
if condition
statements
end if
while CRED uses
if (condition) {
statements
}
c) No fix needed. PI2 only used to check if packets or bytes are available (checks >0), so any length is ok (byte packets)
CRED, is very dependent on the values for both len and time, so I kept byt and sec. PI2 can have any consistent set, that's also why I moved the units of the parameters after the values...
PI2 uses cq.len and cq.time
CRED uses cq.byt and cq.sec
because it also uses cq.ns (for the integer version).
-->
<figure anchor="dualq_fig_Algo_Real"
title="Example Dequeue Pseudocode for DualQ Coupled Curvy RED AQM">
<artwork><![CDATA[1: dualq_dequeue(lq, cq) { % Couples L4S & Classic queues, lq & cq
2: if ( lq.dequeue(pkt) ) {
3a: p_L = cq.sec() / 2^S_L
3b: if ( lq.byt() > T )
3c: mark(pkt)
3d: elif ( p_L > maxrand(U) )
4: mark(pkt)
5: return(pkt) % return the packet and stop here
6: }
7: while ( cq.dequeue(pkt) ) {
8a: alpha = 2^(-f_C)
8b: Q_C = alpha * pkt.sec() + (1-alpha)* Q_C % Classic Q EWMA
9a: sqrt_p_C = Q_C / 2^S_C
9b: if ( sqrt_p_C > maxrand(2*U) )
10: drop(pkt) % Squared drop, redo loop
11: else
12: return(pkt) % return the packet and stop here
13: }
14: return(NULL) % no packet to dequeue
15: }
16: maxrand(u) { % return the max of u random numbers
17: maxr=0
18: while (u-- > 0)
19: maxr = max(maxr, rand()) % 0 <= rand() < 1
20: return(maxr)
21: }
]]></artwork>
</figure>
<t>Packet classification code is not shown, as it is no different from
<xref target="dualq_fig_Algo_pi2_enqueue"/>. Potential classification
schemes are discussed in <xref target="dualq_algo"/>. Overload
protection code will be included in a future draft {ToDo}.</t>
<t>At the outer level, the structure of dualq_dequeue() implements
strict priority scheduling. The code is written assuming the AQM is
applied on dequeue (Note <xref format="counter"
target="dualq_note_dequeue"/>) . Every time dualq_dequeue() is called,
the if-block in lines 2-6 determines whether there is an L4S packet to
dequeue by calling lq.dequeue(pkt), and otherwise the while-block in
lines 7-13 determines whether there is a Classic packet to dequeue, by
calling cq.dequeue(pkt). (Note <xref format="counter"
target="dualq_note_strict_priority"/>)</t>
<t>In the lower priority Classic queue, a while loop is used so that, if
the AQM determines that a classic packet should be dropped, it continues
to test for classic packets deciding whether to drop each until it
actually forwards one. Thus, every call to dualq_dequeue() returns one
packet if at least one is present in either queue, otherwise it returns
NULL at line 14. (Note <xref format="counter"
target="dualq_note_while_loop"/>)</t>
<t>Within each queue, the decision whether to drop or mark is taken as
follows (to simplify the explanation, it is assumed that U=1):<list
style="hanging">
<t hangText="L4S:">If the test at line 2 determines there is an L4S
packet to dequeue, the tests at lines 3a and 3c determine whether to
mark it. The first is a simple test of whether the L4S queue
(lq.byt() in bytes) is greater than a step threshold T in bytes
(Note <xref format="counter" target="dualq_note_step"/>). The second
test is similar to the random ECN marking in RED, but with the
following differences: i) the marking function does not start with a
plateau of zero marking until a minimum threshold, rather the
marking probability starts to increase as soon as the queue is
positive; ii) marking depends on queuing time, not bytes, in order
to scale for any link rate without being reconfigured; iii) marking
of the L4S queue does not depend on itself, it depends on the
queuing time of the <spanx style="emph">other</spanx> (Classic)
queue, where cq.sec() is the queuing time of the packet at the head
of the Classic queue (zero if empty); iv) marking depends on the
instantaneous queuing time (of the other Classic queue), not a
smoothed average; v) the queue is compared with the maximum of U
random numbers (but if U=1, this is the same as the single random
number used in RED).<vspace blankLines="1"/>Specifically, in line 3a
the marking probability p_L is set to the Classic queueing time
qc.sec() in seconds divided by the L4S scaling parameter 2^S_L,
which represents the queuing time (in seconds) at which marking
probability would hit 100%. Then in line 3d (if U=1) the result is
compared with a uniformly distributed random number between 0 and 1,
which ensures that marking probability will linearly increase with
queueing time. The scaling parameter is expressed as a power of 2 so
that division can be implemented as a right bit-shift (>>) in
line 3 of the integer variant of the pseudocode (<xref
target="dualq_fig_Algo_Int"/>).</t>
<t hangText="Classic:">If the test at line 7 determines that there
is at least one Classic packet to dequeue, the test at line 9b
determines whether to drop it. But before that, line 8b updates Q_C,
which is an exponentially weighted moving average (Note <xref
format="counter" target="dualq_note_non-EWMA"/>) of the queuing time
in the Classic queue, where pkt.sec() is the instantaneous queueing
time of the current Classic packet and alpha is the EWMA constant
for the classic queue. In line 8a, alpha is represented as an
integer power of 2, so that in line 8 of the integer code the
division needed to weight the moving average can be implemented by a
right bit-shift (>> f_C).<vspace blankLines="1"/>Lines 9a and
9b implement the drop function. In line 9a the averaged queuing time
Q_C is divided by the Classic scaling parameter 2^S_C, in the same
way that queuing time was scaled for L4S marking. This scaled
queuing time is given the variable name sqrt_p_C because it will be
squared to compute Classic drop probability, so before it is squared
it is effectively the square root of the drop probability. The
squaring is done by comparing it with the maximum out of two random
numbers (assuming U=1). Comparing it with the maximum out of two is
the same as the logical `AND' of two tests, which ensures drop
probability rises with the square of queuing time (Note <xref
format="counter" target="dualq_note_classic_ecn"/>). Again, the
scaling parameter is expressed as a power of 2 so that division can
be implemented as a right bit-shift in line 9 of the integer
pseudocode.</t>
</list></t>
<t>The marking/dropping functions in each queue (lines 3 & 9) are
two cases of a new generalization of RED called Curvy RED, motivated as
follows. When we compared the performance of our AQM with fq_CoDel and
PIE, we came to the conclusion that their goal of holding queuing delay
to a fixed target is misguided <xref target="CRED_Insights"/>. As the
number of flows increases, if the AQM does not allow TCP to increase
queuing delay, it has to introduce abnormally high levels of loss. Then
loss rather than queuing becomes the dominant cause of delay for short
flows, due to timeouts and tail losses.</t>
<t>Curvy RED constrains delay with a softened target that allows some
increase in delay as load increases. This is achieved by increasing drop
probability on a convex curve relative to queue growth (the square curve
in the Classic queue, if U=1). Like RED, the curve hugs the zero axis
while the queue is shallow. Then, as load increases, it introduces a
growing barrier to higher delay. But, unlike RED, it requires only one
parameter, the scaling, not three. The diadvantage of Curvy RED is that
it is not adapted to a wide range of RTTs. Curvy RED can be used as is
when the RTT range to support is limited otherwise an adaptation
mechanism is required.</t>
<t>There follows a summary listing of the two parameters used for each
of the two queues:<list style="hanging">
<t hangText="Classic:"><list style="hanging">
<t hangText="S_C : ">The scaling factor of the dropping function
scales Classic queuing times in the range [0, 2^(S_C)] seconds
into a dropping probability in the range [0,1]. To make division
efficient, it is constrained to be an integer power of two;</t>
<t hangText="f_C :">To smooth the queuing time of the Classic
queue and make multiplication efficient, we use a negative
integer power of two for the dimensionless EWMA constant, which
we define as 2^(-f_C).</t>
</list></t>
<t hangText="L4S : "><list style="hanging">
<t hangText="S_L (and k): ">As for the Classic queue, the
scaling factor of the L4S marking function scales Classic
queueing times in the range [0, 2^(S_L)] seconds into a
probability in the range [0,1]. Note that S_L = S_C + k, where k
is the coupling between the queues (<xref
target="dualq_coupled"/>). So S_L and k count as only one
parameter;</t>
<t hangText="T :">The queue size in bytes at which step
threshold marking starts in the L4S queue.</t>
</list></t>
</list>{ToDo: These are the raw parameters used within the algorithm.
A configuration front-end could accept more meaningful parameters and
convert them into these raw parameters.}</t>
<t>From our experiments so far, recommended values for these parameters
are: S_C = -1; f_C = 5; T = 5 * MTU for the range of base RTTs typical
on the public Internet. <xref target="CRED_Insights"/> explains why
these parameters are applicable whatever rate link this AQM
implementation is deployed on and how the parameters would need to be
adjusted for a scenario with a different range of RTTs (e.g. a data
centre) {ToDo incorporate a summary of that report into this draft}. The
setting of k depends on policy (see <xref target="dualq_norm_reqs"/> and
<xref target="dualq_Choosing_k"/> respectively for its recommended
setting and guidance on alternatives).</t>
<t>There is also a cUrviness parameter, U, which is a small positive
integer. It is likely to take the same hard-coded value for all
implementations, once experiments have determined a good value. We have
solely used U=1 in our experiments so far, but results might be even
better with U=2 or higher.</t>
<t>Note that the dropping function at line 9 calls maxrand(2*U), which
gives twice as much curviness as the call to maxrand(U) in the marking
function at line 3. This is the trick that implements the square rule in
equation (1) (<xref target="dualq_coupled"/>). This is based on the fact
that, given a number X from 1 to 6, the probability that two dice throws
will both be less than X is the square of the probability that one throw
will be less than X. So, when U=1, the L4S marking function is linear
and the Classic dropping function is squared. If U=2, L4S would be a
square function and Classic would be quartic. And so on.</t>
<t>The maxrand(u) function in lines 16-21 simply generates u random
numbers and returns the maximum (Note <xref format="counter"
target="dualq_note_integer_scaling"/>). Typically, maxrand(u) could be
run in parallel out of band. For instance, if U=1, the Classic queue
would require the maximum of two random numbers. So, instead of calling
maxrand(2*U) in-band, the maximum of every pair of values from a
pseudorandom number generator could be generated out-of-band, and held
in a buffer ready for the Classic queue to consume.</t>
<figure anchor="dualq_fig_Algo_Int"
title="Optimised Example Dequeue Pseudocode for Coupled DualQ AQM using Integer Arithmetic">
<artwork><![CDATA[1: dualq_dequeue(lq, cq) { % Couples L4S & Classic queues, lq & cq
2: if ( lq.dequeue(pkt) ) {
3: if ((lq.byt() > T) || ((cq.ns() >> (S_L-2)) > maxrand(U)))
4: mark(pkt)
5: return(pkt) % return the packet and stop here
6: }
7: while ( cq.dequeue(pkt) ) {
8: Q_C += (pkt.ns() - Q_C) >> f_C % Classic Q EWMA
9: if ( (Q_C >> (S_C-2) ) > maxrand(2*U) )
10: drop(pkt) % Squared drop, redo loop
11: else
12: return(pkt) % return the packet and stop here
13: }
14: return(NULL) % no packet to dequeue
15: }
]]></artwork>
</figure>
<t>Notes:<list style="numbers">
<t anchor="dualq_note_dequeue">The drain rate of the queue can vary
if it is scheduled relative to other queues, or to cater for
fluctuations in a wireless medium. To auto-adjust to changes in
drain rate, the queue must be measured in time, not bytes or packets
<xref target="CoDel"/>. In our Linux implementation, it was easiest
to measure queuing time at dequeue. Queuing time can be estimated
when a packet is enqueued by measuring the queue length in bytes and
dividing by the recent drain rate.</t>
<t anchor="dualq_note_strict_priority">An implementation has to use
priority queueing, but it need not implement strict priority.</t>
<t anchor="dualq_note_while_loop">If packets can be enqueued while
processing dequeue code, an implementer might prefer to place the
while loop around both queues so that it goes back to test again
whether any L4S packets arrived while it was dropping a Classic
packet.</t>
<t anchor="dualq_note_step">In order not to change too many factors
at once, for now, we keep the marking function for DCTCP-only
traffic as similar as possible to DCTCP. However, unlike DCTCP, all
processing is at dequeue, so we determine whether to mark a packet
at the head of the queue by the byte-length of the queue <spanx
style="emph">behind</spanx> it. We plan to test whether using
queuing time will work in all circumstances, and if we find that the
step can cause oscillations, we will investigate replacing it with a
steep random marking curve.</t>
<t anchor="dualq_note_non-EWMA">An EWMA is only one possible way to
filter bursts; other more adaptive smoothing methods could be valid
and it might be appropriate to decrease the EWMA faster than it
increases.</t>
<t anchor="dualq_note_classic_ecn">In practice at line 10 the
Classic queue would probably test for ECN capability on the packet
to determine whether to drop or mark the packet. However, for
brevity such detail is omitted. All packets classified into the L4S
queue have to be ECN-capable, so no dropping logic is necessary at
line 3. Nonetheless, L4S packets could be dropped by overload code
(see <xref target="dualq_Overload"/>).</t>
<t anchor="dualq_note_integer_scaling">In the integer variant of the
pseudocode (<xref target="dualq_fig_Algo_Int"/>) real numbers are
all represented as integers scaled up by 2^32. In lines 3 & 9
the function maxrand() is arranged to return an integer in the range
0 <= maxrand() < 2^32. Queuing times are also scaled up by
2^32, but in two stages: i) In lines 3 and 8 queuing times cq.ns()
and pkt.ns() are returned in integer nanoseconds, making the values
about 2^30 times larger than when the units were seconds, ii) then
in lines 3 and 9 an adjustment of -2 to the right bit-shift
multiplies the result by 2^2, to complete the scaling by 2^32.</t>
</list></t>
</section>
<section anchor="dualq_Choosing_k"
title="Guidance on Controlling Throughput Equivalence">
<texttable align="center" anchor="dualq_tab_k_policy"
title="Value of k for which DCTCP throughput is roughly the same as Reno or Cubic, for some example RTT ratios">
<ttcol align="right">RTT_C / RTT_L</ttcol>
<ttcol>Reno</ttcol>
<ttcol>Cubic</ttcol>
<c>1</c>
<c>k=1</c>
<c>k=0</c>
<c>2</c>
<c>k=2</c>
<c>k=1</c>
<c>3</c>
<c>k=2</c>
<c>k=2</c>
<c>4</c>
<c>k=3</c>
<c>k=2</c>
<c>5</c>
<c>k=3</c>
<c>k=3</c>
</texttable>
<t>To determine the appropriate policy, the operator first has to judge
whether it wants DCTCP flows to have roughly equal throughput with Reno
or with Cubic (because, even in its Reno-compatibility mode, Cubic is
about 1.4 times more aggressive than Reno). Then the operator needs to
decide at what ratio of RTTs it wants DCTCP and Classic flows to have
roughly equal throughput. For example choosing the recommended value of
k=0 will make DCTCP throughput roughly the same as Cubic, <spanx
style="emph">if their RTTs are the same</spanx>.</t>
<t>However, even if the base RTTs are the same, the actual RTTs are
unlikely to be the same, because Classic (Cubic or Reno) traffic needs a
large queue to avoid under-utilization and excess drop, whereas L4S
(DCTCP) does not. The operator might still choose this policy if it
judges that DCTCP throughput should be rewarded for keeping its own
queue short.</t>
<t>On the other hand, the operator will choose one of the higher values
for k, if it wants to slow DCTCP down to roughly the same throughput as
Classic flows, to compensate for Classic flows slowing themselves down
by causing themselves extra queuing delay.</t>
<t>The values for k in the table are derived from the formulae, which
was developed in <xref target="DCttH15"/>:</t>
<figure>
<artwork><![CDATA[ 2^k = 1.64 (RTT_reno / RTT_dc) (2)
2^k = 1.19 (RTT_cubic / RTT_dc ) (3)
]]></artwork>
</figure>
<t>For localized traffic from a particular ISP's data centre, we used
the measured RTTs to calculate that a value of k=3 would achieve
throughput equivalence, and our experiments verified the formula very
closely.</t>
</section>
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</rfc>
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