draft-ietf-tsvwg-aqm-dualq-coupled-16.txt   draft-ietf-tsvwg-aqm-dualq-coupled-17.txt 
Transport Area working group (tsvwg) K. De Schepper Transport Area working group (tsvwg) K. De Schepper
Internet-Draft Nokia Bell Labs Internet-Draft Nokia Bell Labs
Intended status: Experimental B. Briscoe, Ed. Intended status: Experimental B. Briscoe, Ed.
Expires: January 7, 2022 Independent Expires: 7 April 2022 Independent
G. White G. White
CableLabs CableLabs
July 6, 2021 4 October 2021
DualQ Coupled AQMs for Low Latency, Low Loss and Scalable Throughput DualQ Coupled AQMs for Low Latency, Low Loss and Scalable Throughput
(L4S) (L4S)
draft-ietf-tsvwg-aqm-dualq-coupled-16 draft-ietf-tsvwg-aqm-dualq-coupled-17
Abstract Abstract
The Low Latency Low Loss Scalable Throughput (L4S) architecture The Low Latency Low Loss Scalable Throughput (L4S) architecture
allows data flows over the public Internet to achieve consistent low allows data flows over the public Internet to achieve consistent low
queuing latency, generally zero congestion loss and scaling of per- queuing latency, generally zero congestion loss and scaling of per-
flow throughput without the scaling problems of standard TCP Reno- flow throughput without the scaling problems of standard TCP Reno-
friendly congestion controls. To achieve this, L4S data flows have friendly congestion controls. To achieve this, L4S data flows have
to use one of the family of 'Scalable' congestion controls (TCP to use one of the family of 'Scalable' congestion controls (TCP
Prague and Data Center TCP are examples) and a form of Explicit Prague and Data Center TCP are examples) and a form of Explicit
skipping to change at page 2, line 20 skipping to change at page 2, line 20
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This Internet-Draft will expire on January 7, 2022. This Internet-Draft will expire on 7 April 2022.
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Table of Contents Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
1.1. Outline of the Problem . . . . . . . . . . . . . . . . . 3 1.1. Outline of the Problem . . . . . . . . . . . . . . . . . 4
1.2. Scope . . . . . . . . . . . . . . . . . . . . . . . . . . 6 1.2. Scope . . . . . . . . . . . . . . . . . . . . . . . . . . 6
1.3. Terminology . . . . . . . . . . . . . . . . . . . . . . . 7 1.3. Terminology . . . . . . . . . . . . . . . . . . . . . . . 8
1.4. Features . . . . . . . . . . . . . . . . . . . . . . . . 9 1.4. Features . . . . . . . . . . . . . . . . . . . . . . . . 9
2. DualQ Coupled AQM . . . . . . . . . . . . . . . . . . . . . . 10 2. DualQ Coupled AQM . . . . . . . . . . . . . . . . . . . . . . 11
2.1. Coupled AQM . . . . . . . . . . . . . . . . . . . . . . . 11 2.1. Coupled AQM . . . . . . . . . . . . . . . . . . . . . . . 11
2.2. Dual Queue . . . . . . . . . . . . . . . . . . . . . . . 12 2.2. Dual Queue . . . . . . . . . . . . . . . . . . . . . . . 12
2.3. Traffic Classification . . . . . . . . . . . . . . . . . 12 2.3. Traffic Classification . . . . . . . . . . . . . . . . . 13
2.4. Overall DualQ Coupled AQM Structure . . . . . . . . . . . 13 2.4. Overall DualQ Coupled AQM Structure . . . . . . . . . . . 13
2.5. Normative Requirements for a DualQ Coupled AQM . . . . . 16 2.5. Normative Requirements for a DualQ Coupled AQM . . . . . 17
2.5.1. Functional Requirements . . . . . . . . . . . . . . . 16 2.5.1. Functional Requirements . . . . . . . . . . . . . . . 17
2.5.1.1. Requirements in Unexpected Cases . . . . . . . . 18 2.5.1.1. Requirements in Unexpected Cases . . . . . . . . 18
2.5.2. Management Requirements . . . . . . . . . . . . . . . 19 2.5.2. Management Requirements . . . . . . . . . . . . . . . 19
2.5.2.1. Configuration . . . . . . . . . . . . . . . . . . 19 2.5.2.1. Configuration . . . . . . . . . . . . . . . . . . 19
2.5.2.2. Monitoring . . . . . . . . . . . . . . . . . . . 20 2.5.2.2. Monitoring . . . . . . . . . . . . . . . . . . . 21
2.5.2.3. Anomaly Detection . . . . . . . . . . . . . . . . 21 2.5.2.3. Anomaly Detection . . . . . . . . . . . . . . . . 21
2.5.2.4. Deployment, Coexistence and Scaling . . . . . . . 21 2.5.2.4. Deployment, Coexistence and Scaling . . . . . . . 22
3. IANA Considerations (to be removed by RFC Editor) . . . . . . 22 3. IANA Considerations (to be removed by RFC Editor) . . . . . . 22
4. Security Considerations . . . . . . . . . . . . . . . . . . . 22 4. Security Considerations . . . . . . . . . . . . . . . . . . . 22
4.1. Overload Handling . . . . . . . . . . . . . . . . . . . . 22 4.1. Overload Handling . . . . . . . . . . . . . . . . . . . . 22
4.1.1. Avoiding Classic Starvation: Sacrifice L4S Throughput 4.1.1. Avoiding Classic Starvation: Sacrifice L4S Throughput
or Delay? . . . . . . . . . . . . . . . . . . . . . . 22 or Delay? . . . . . . . . . . . . . . . . . . . . . . 23
4.1.2. Congestion Signal Saturation: Introduce L4S Drop or 4.1.2. Congestion Signal Saturation: Introduce L4S Drop or
Delay? . . . . . . . . . . . . . . . . . . . . . . . 24 Delay? . . . . . . . . . . . . . . . . . . . . . . . 24
4.1.3. Protecting against Unresponsive ECN-Capable Traffic . 25 4.1.3. Protecting against Unresponsive ECN-Capable
5. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 25 Traffic . . . . . . . . . . . . . . . . . . . . . . . 25
6. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 25 5. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 26
6. Contributors . . . . . . . . . . . . . . . . . . . . . . . . 26
7. References . . . . . . . . . . . . . . . . . . . . . . . . . 26 7. References . . . . . . . . . . . . . . . . . . . . . . . . . 26
7.1. Normative References . . . . . . . . . . . . . . . . . . 26 7.1. Normative References . . . . . . . . . . . . . . . . . . 26
7.2. Informative References . . . . . . . . . . . . . . . . . 26 7.2. Informative References . . . . . . . . . . . . . . . . . 27
Appendix A. Example DualQ Coupled PI2 Algorithm . . . . . . . . 32 Appendix A. Example DualQ Coupled PI2 Algorithm . . . . . . . . 32
A.1. Pass #1: Core Concepts . . . . . . . . . . . . . . . . . 32 A.1. Pass #1: Core Concepts . . . . . . . . . . . . . . . . . 33
A.2. Pass #2: Overload Details . . . . . . . . . . . . . . . . 42 A.2. Pass #2: Overload Details . . . . . . . . . . . . . . . . 43
Appendix B. Example DualQ Coupled Curvy RED Algorithm . . . . . 46 Appendix B. Example DualQ Coupled Curvy RED Algorithm . . . . . 47
B.1. Curvy RED in Pseudocode . . . . . . . . . . . . . . . . . 46 B.1. Curvy RED in Pseudocode . . . . . . . . . . . . . . . . . 47
B.2. Efficient Implementation of Curvy RED . . . . . . . . . . 52 B.2. Efficient Implementation of Curvy RED . . . . . . . . . . 53
Appendix C. Choice of Coupling Factor, k . . . . . . . . . . . . 54 Appendix C. Choice of Coupling Factor, k . . . . . . . . . . . . 55
C.1. RTT-Dependence . . . . . . . . . . . . . . . . . . . . . 54 C.1. RTT-Dependence . . . . . . . . . . . . . . . . . . . . . 55
C.2. Guidance on Controlling Throughput Equivalence . . . . . 55 C.2. Guidance on Controlling Throughput Equivalence . . . . . 56
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 56 Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 57
1. Introduction 1. Introduction
This document specifies a framework for DualQ Coupled AQMs, which is This document specifies a framework for DualQ Coupled AQMs, which is
the network part of the L4S architecture [I-D.ietf-tsvwg-l4s-arch]. the network part of the L4S architecture [I-D.ietf-tsvwg-l4s-arch].
L4S enables both very low queuing latency (sub-millisecond on L4S enables both very low queuing latency (sub-millisecond on
average) and high throughput at the same time, for ad hoc numbers of average) and high throughput at the same time, for ad hoc numbers of
capacity-seeking applications all sharing the same capacity. capacity-seeking applications all sharing the same capacity.
1.1. Outline of the Problem 1.1. Outline of the Problem
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now it has not been possible to allow any number of low latency, high now it has not been possible to allow any number of low latency, high
throughput applications to seek to fully utilize available capacity, throughput applications to seek to fully utilize available capacity,
because the capacity-seeking process itself causes too much queuing because the capacity-seeking process itself causes too much queuing
delay. delay.
To reduce this queuing delay caused by the capacity seeking process, To reduce this queuing delay caused by the capacity seeking process,
changes either to the network alone or to end-systems alone are in changes either to the network alone or to end-systems alone are in
progress. L4S involves a recognition that both approaches are progress. L4S involves a recognition that both approaches are
yielding diminishing returns: yielding diminishing returns:
o Recent state-of-the-art active queue management (AQM) in the * Recent state-of-the-art active queue management (AQM) in the
network, e.g. FQ-CoDel [RFC8290], PIE [RFC8033], Adaptive network, e.g. FQ-CoDel [RFC8290], PIE [RFC8033], Adaptive
RED [ARED01] ) has reduced queuing delay for all traffic, not just RED [ARED01] ) has reduced queuing delay for all traffic, not just
a select few applications. However, no matter how good the AQM, a select few applications. However, no matter how good the AQM,
the capacity-seeking (sawtoothing) rate of TCP-like congestion the capacity-seeking (sawtoothing) rate of TCP-like congestion
controls represents a lower limit that will either cause queuing controls represents a lower limit that will either cause queuing
delay to vary or cause the link to be under-utilized. These AQMs delay to vary or cause the link to be under-utilized. These AQMs
are tuned to allow a typical capacity-seeking Reno-friendly flow are tuned to allow a typical capacity-seeking Reno-friendly flow
to induce an average queue that roughly doubles the base RTT, to induce an average queue that roughly doubles the base RTT,
adding 5-15 ms of queuing on average (cf. 500 microseconds with adding 5-15 ms of queuing on average (cf. 500 microseconds with
L4S for the same mix of long-running and web traffic). However, L4S for the same mix of long-running and web traffic). However,
for many applications low delay is not useful unless it is for many applications low delay is not useful unless it is
consistently low. With these AQMs, 99th percentile queuing delay consistently low. With these AQMs, 99th percentile queuing delay
is 20-30 ms (cf. 2 ms with the same traffic over L4S). is 20-30 ms (cf. 2 ms with the same traffic over L4S).
o Similarly, recent research into using e2e congestion control * Similarly, recent research into using e2e congestion control
without needing an AQM in the network (e.g.BBR [BBRv1], without needing an AQM in the network (e.g.BBR [BBRv1],
[I-D.cardwell-iccrg-bbr-congestion-control]) seems to have hit a [I-D.cardwell-iccrg-bbr-congestion-control]) seems to have hit a
similar lower limit to queuing delay of about 20ms on average (and similar lower limit to queuing delay of about 20ms on average (and
any additional BBRv1 flow adds another 20ms of queuing) but there any additional BBRv1 flow adds another 20ms of queuing) but there
are also regular 25ms delay spikes due to bandwidth probes and are also regular 25ms delay spikes due to bandwidth probes and
60ms spikes due to flow-starts. 60ms spikes due to flow-starts.
L4S learns from the experience of Data Center TCP [RFC8257], which L4S learns from the experience of Data Center TCP [RFC8257], which
shows the power of complementary changes both in the network and on shows the power of complementary changes both in the network and on
end-systems. DCTCP teaches us that two small but radical changes to end-systems. DCTCP teaches us that two small but radical changes to
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For the public Internet, nearly all the benefit will typically be For the public Internet, nearly all the benefit will typically be
achieved by deploying the Coupled AQM into either end of the access achieved by deploying the Coupled AQM into either end of the access
link between a 'site' and the Internet, which is invariably the link between a 'site' and the Internet, which is invariably the
bottleneck (see section 6.4 of[I-D.ietf-tsvwg-l4s-arch] about bottleneck (see section 6.4 of[I-D.ietf-tsvwg-l4s-arch] about
deployment, which also defines the term 'site' to mean a home, an deployment, which also defines the term 'site' to mean a home, an
office, a campus or mobile user equipment). office, a campus or mobile user equipment).
Latency is not the only concern of L4S: Latency is not the only concern of L4S:
o The 'Low Loss" part of the name denotes that L4S generally * The 'Low Loss" part of the name denotes that L4S generally
achieves zero congestion loss (which would otherwise cause achieves zero congestion loss (which would otherwise cause
retransmission delays), due to its use of ECN. retransmission delays), due to its use of ECN.
o The "Scalable throughput" part of the name denotes that the per- * The "Scalable throughput" part of the name denotes that the per-
flow throughput of Scalable congestion controls should scale flow throughput of Scalable congestion controls should scale
indefinitely, avoiding the imminent scaling problems with 'TCP- indefinitely, avoiding the imminent scaling problems with 'TCP-
Friendly' congestion control algorithms [RFC3649]. Friendly' congestion control algorithms [RFC3649].
The former is clearly in scope of this AQM document. However, the The former is clearly in scope of this AQM document. However, the
latter is an outcome of the end-system behaviour, and therefore latter is an outcome of the end-system behaviour, and therefore
outside the scope of this AQM document, even though the AQM is an outside the scope of this AQM document, even though the AQM is an
enabler. enabler.
The overall L4S architecture [I-D.ietf-tsvwg-l4s-arch] gives more The overall L4S architecture [I-D.ietf-tsvwg-l4s-arch] gives more
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high throughput is robust to disturbances. For instance, DCTCP high throughput is robust to disturbances. For instance, DCTCP
averages 2 congestion signals per round-trip whatever the flow averages 2 congestion signals per round-trip whatever the flow
rate, as do other recently developed scalable congestion controls, rate, as do other recently developed scalable congestion controls,
e.g. Relentless TCP [Mathis09], TCP Prague e.g. Relentless TCP [Mathis09], TCP Prague
[I-D.briscoe-iccrg-prague-congestion-control], [PragueLinux], [I-D.briscoe-iccrg-prague-congestion-control], [PragueLinux],
BBRv2 [BBRv2] and the L4S variant of SCREAM for real-time BBRv2 [BBRv2] and the L4S variant of SCREAM for real-time
media [SCReAM], [RFC8298]). For the public Internet a Scalable media [SCReAM], [RFC8298]). For the public Internet a Scalable
transport has to comply with the requirements in Section 4 of transport has to comply with the requirements in Section 4 of
[I-D.ietf-tsvwg-ecn-l4s-id] (aka. the 'Prague L4S requirements'). [I-D.ietf-tsvwg-ecn-l4s-id] (aka. the 'Prague L4S requirements').
C: Abbreviation for Classic, e.g. when used as a subscript. C: Abbreviation for Classic, e.g. when used as a subscript.
L: Abbreviation for L4S, e.g. when used as a subscript. L: Abbreviation for L4S, e.g. when used as a subscript.
The terms Classic or L4S can also qualify other nouns, such as The terms Classic or L4S can also qualify other nouns, such as
'codepoint', 'identifier', 'classification', 'packet', 'flow'. 'codepoint', 'identifier', 'classification', 'packet', 'flow'.
For example: an L4S packet means a packet with an L4S identifier For example: an L4S packet means a packet with an L4S identifier
sent from an L4S congestion control. sent from an L4S congestion control.
Both Classic and L4S services can cope with a proportion of Both Classic and L4S services can cope with a proportion of
unresponsive or less-responsive traffic as well, but in the L4S unresponsive or less-responsive traffic as well, but in the L4S
case its rate has to be smooth enough or low enough not to build a case its rate has to be smooth enough or low enough not to build a
queue (e.g. DNS, VoIP, game sync datagrams, etc). The DualQ queue (e.g. DNS, VoIP, game sync datagrams, etc). The DualQ
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achieve low delay. The L4S queue can be filled with a heavy load of achieve low delay. The L4S queue can be filled with a heavy load of
capacity-seeking flows (TCP Prague etc.) and still achieve low delay. capacity-seeking flows (TCP Prague etc.) and still achieve low delay.
The L4S queue does not rely on the presence of other traffic in the 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 Classic queue that can be 'overtaken'. It gives low latency to L4S
traffic whether or not there is Classic traffic, and the latency of traffic whether or not there is Classic traffic, and the latency of
Classic traffic does not suffer when a proportion of the traffic is Classic traffic does not suffer when a proportion of the traffic is
L4S. L4S.
The two queues are only necessary because: The two queues are only necessary because:
o the large variations (sawteeth) of Classic flows need roughly a * the large variations (sawteeth) of Classic flows need roughly a
base RTT of queuing delay to ensure full utilization base RTT of queuing delay to ensure full utilization
o Scalable flows do not need a queue to keep utilization high, but * Scalable flows do not need a queue to keep utilization high, but
they cannot keep latency predictably low if they are mixed with they cannot keep latency predictably low if they are mixed with
Classic traffic, Classic traffic,
The L4S queue has latency priority within sub-round trip timescales, The L4S queue has latency priority within sub-round trip timescales,
but over longer periods the coupling from the Classic to the L4S AQM but over longer periods the coupling from the Classic to the L4S AQM
(explained below) ensures that it does not have bandwidth priority (explained below) ensures that it does not have bandwidth priority
over the Classic queue. over the Classic queue.
2. DualQ Coupled AQM 2. DualQ Coupled AQM
There are two main aspects to the approach: There are two main aspects to the approach:
o The Coupled AQM that addresses throughput equivalence between * The Coupled AQM that addresses throughput equivalence between
Classic (e.g. Reno, Cubic) flows and L4S flows (that satisfy the Classic (e.g. Reno, Cubic) flows and L4S flows (that satisfy the
Prague L4S requirements). Prague L4S requirements).
o The Dual Queue structure that provides latency separation for L4S * The Dual Queue structure that provides latency separation for L4S
flows to isolate them from the typically large Classic queue. flows to isolate them from the typically large Classic queue.
2.1. Coupled AQM 2.1. Coupled AQM
In the 1990s, the `TCP formula' was derived for the relationship In the 1990s, the `TCP formula' was derived for the relationship
between the steady-state congestion window, cwnd, and the drop between the steady-state congestion window, cwnd, and the drop
probability, p of standard Reno congestion control [RFC5681] . To a probability, p of standard Reno congestion control [RFC5681] . To a
first order approximation, the steady-state cwnd of Reno is inversely first order approximation, the steady-state cwnd of Reno is inversely
proportional to the square root of p. proportional to the square root of p.
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`----------'\\ | AQM |---->: ,'|`-.___.-' `----------'\\ | AQM |---->: ,'|`-.___.-'
\\ | |p' | <' | \\ | |p' | <' |
\\ `-------' (p'^2) //`' \\ `-------' (p'^2) //`'
\\ ^ | // \\ ^ | //
\\,. | v p_C // \\,. | v p_C //
< | _________ .------.// < | _________ .------.//
`\| | | | Drop |/ `\| | | | Drop |/
Classic |queue |===>|/mark | Classic |queue |===>|/mark |
__|______| `------' __|______| `------'
Legend: ===> traffic flow; ---> control dependency.
Figure 1: DualQ Coupled AQM Schematic Figure 1: DualQ Coupled AQM Schematic
Legend: ===> traffic flow; ---> control dependency.
After the AQMs have applied their dropping or marking, the scheduler After the AQMs have applied their dropping or marking, the scheduler
forwards their packets to the link. Even though the scheduler gives forwards their packets to the link. Even though the scheduler gives
priority to the L queue, it is not as strong as the coupling from the priority to the L queue, it is not as strong as the coupling from the
C queue. This is because, as the C queue grows, the base AQM applies C queue. This is because, as the C queue grows, the base AQM applies
more congestion signals to L traffic (as well as C). As L flows more congestion signals to L traffic (as well as C). As L flows
reduce their rate in response, they use less than the scheduling reduce their rate in response, they use less than the scheduling
share for L traffic. So, because the scheduler is work preserving, share for L traffic. So, because the scheduler is work preserving,
it schedules any C traffic in the gaps. it schedules any C traffic in the gaps.
Giving priority to the L queue has the benefit of very low L queue Giving priority to the L queue has the benefit of very low L queue
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2.5.1.1. Requirements in Unexpected Cases 2.5.1.1. Requirements in Unexpected Cases
The flexibility to allow operator-specific classifiers (Section 2.3) The flexibility to allow operator-specific classifiers (Section 2.3)
leads to the need to specify what the AQM in each queue ought to do leads to the need to specify what the AQM in each queue ought to do
with packets that do not carry the ECN field expected for that queue. with packets that do not carry the ECN field expected for that queue.
It is expected that the AQM in each queue will inspect the ECN field It is expected that the AQM in each queue will inspect the ECN field
to determine what sort of congestion notification to signal, then it to determine what sort of congestion notification to signal, then it
will decide whether to apply congestion notification to this will decide whether to apply congestion notification to this
particular packet, as follows: particular packet, as follows:
o If a packet that does not carry an ECT(1) or CE codepoint is * If a packet that does not carry an ECT(1) or CE codepoint is
classified into the L queue: classified into the L queue:
* if the packet is ECT(0), the L AQM SHOULD apply CE-marking - if the packet is ECT(0), the L AQM SHOULD apply CE-marking
using a probability appropriate to Classic congestion control using a probability appropriate to Classic congestion control
and appropriate to the target delay in the L queue and appropriate to the target delay in the L queue
* if the packet is Not-ECT, the appropriate action depends on - if the packet is Not-ECT, the appropriate action depends on
whether some other function is protecting the L queue from whether some other function is protecting the L queue from
misbehaving flows (e.g. per-flow queue misbehaving flows (e.g. per-flow queue
protection [I-D.briscoe-docsis-q-protection] or latency protection [I-D.briscoe-docsis-q-protection] or latency
policing): policing):
+ If separate queue protection is provided, the L AQM SHOULD o If separate queue protection is provided, the L AQM SHOULD
ignore the packet and forward it unchanged, meaning it ignore the packet and forward it unchanged, meaning it
should not calculate whether to apply congestion should not calculate whether to apply congestion
notification and it should neither drop nor CE-mark the notification and it should neither drop nor CE-mark the
packet (for instance, the operator might classify EF traffic packet (for instance, the operator might classify EF traffic
that is unresponsive to drop into the L queue, alongside that is unresponsive to drop into the L queue, alongside
responsive L4S-ECN traffic) responsive L4S-ECN traffic)
+ if separate queue protection is not provided, the L AQM o if separate queue protection is not provided, the L AQM
SHOULD apply drop using a drop probability appropriate to SHOULD apply drop using a drop probability appropriate to
Classic congestion control and appropriate to the target Classic congestion control and appropriate to the target
delay in the L queue delay in the L queue
o If a packet that carries an ECT(1) codepoint is classified into * If a packet that carries an ECT(1) codepoint is classified into
the C queue: the C queue:
* the C AQM SHOULD apply CE-marking using the coupled AQM - the C AQM SHOULD apply CE-marking using the coupled AQM
probability p_CL (= k*p'). probability p_CL (= k*p').
The above requirements are worded as "SHOULDs", because operator- The above requirements are worded as "SHOULDs", because operator-
specific classifiers are for flexibility, by definition. Therefore, specific classifiers are for flexibility, by definition. Therefore,
alternative actions might be appropriate in the operator's specific alternative actions might be appropriate in the operator's specific
circumstances. An example would be where the operator knows that circumstances. An example would be where the operator knows that
certain legacy traffic marked with one codepoint actually has a certain legacy traffic marked with one codepoint actually has a
congestion response associated with another codepoint. congestion response associated with another codepoint.
If the DualQ Coupled AQM has detected overload, it MUST begin using If the DualQ Coupled AQM has detected overload, it MUST begin using
skipping to change at page 19, line 29 skipping to change at page 19, line 45
2.5.2. Management Requirements 2.5.2. Management Requirements
2.5.2.1. Configuration 2.5.2.1. Configuration
By default, a DualQ Coupled AQM SHOULD NOT need any configuration for By default, a DualQ Coupled AQM SHOULD NOT need any configuration for
use at a bottleneck on the public Internet [RFC7567]. The following use at a bottleneck on the public Internet [RFC7567]. The following
parameters MAY be operator-configurable, e.g. to tune for non- parameters MAY be operator-configurable, e.g. to tune for non-
Internet settings: Internet settings:
o Optional packet classifier(s) to use in addition to the ECN field * Optional packet classifier(s) to use in addition to the ECN field
(see Section 2.3); (see Section 2.3);
o Expected typical RTT, which can be used to determine the queuing * Expected typical RTT, which can be used to determine the queuing
delay of the Classic AQM at its operating point, in order to delay of the Classic AQM at its operating point, in order to
prevent typical lone flows from under-utilizing capacity. For prevent typical lone flows from under-utilizing capacity. For
example: example:
* for the PI2 algorithm (Appendix A) the queuing delay target is - for the PI2 algorithm (Appendix A) the queuing delay target is
dependent on the typical RTT; dependent on the typical RTT;
* for the Curvy RED algorithm (Appendix B) the queuing delay at - for the Curvy RED algorithm (Appendix B) the queuing delay at
the desired operating point of the curvy ramp is configured to the desired operating point of the curvy ramp is configured to
encompass a typical RTT; encompass a typical RTT;
* if another Classic AQM was used, it would be likely to need an - if another Classic AQM was used, it would be likely to need an
operating point for the queue based on the typical RTT, and if operating point for the queue based on the typical RTT, and if
so it SHOULD be expressed in units of time. so it SHOULD be expressed in units of time.
An operating point that is manually calculated might be directly An operating point that is manually calculated might be directly
configurable instead, e.g. for links with large numbers of flows configurable instead, e.g. for links with large numbers of flows
where under-utilization by a single flow would be unlikely. where under-utilization by a single flow would be unlikely.
o Expected maximum RTT, which can be used to set the stability * Expected maximum RTT, which can be used to set the stability
parameter(s) of the Classic AQM. For example: parameter(s) of the Classic AQM. For example:
* for the PI2 algorithm (Appendix A), the gain parameters of the - for the PI2 algorithm (Appendix A), the gain parameters of the
PI algorithm depend on the maximum RTT. PI algorithm depend on the maximum RTT.
* for the Curvy RED algorithm (Appendix B) the smoothing - for the Curvy RED algorithm (Appendix B) the smoothing
parameter is chosen to filter out transients in the queue parameter is chosen to filter out transients in the queue
within a maximum RTT. within a maximum RTT.
Stability parameter(s) that are manually calculated assuming a Stability parameter(s) that are manually calculated assuming a
maximum RTT might be directly configurable instead. maximum RTT might be directly configurable instead.
o Coupling factor, k (see Appendix C.2); * Coupling factor, k (see Appendix C.2);
o A limit to the conditional priority of L4S. This is scheduler- * A limit to the conditional priority of L4S. This is scheduler-
dependent, but it SHOULD be expressed as a relation between the dependent, but it SHOULD be expressed as a relation between the
max delay of a C packet and an L packet. For example: max delay of a C packet and an L packet. For example:
* for a WRR scheduler a weight ratio between L and C of w:1 means - for a WRR scheduler a weight ratio between L and C of w:1 means
that the maximum delay to a C packet is w times that of an L that the maximum delay to a C packet is w times that of an L
packet. packet.
* for a time-shifted FIFO (TS-FIFO) scheduler (see Section 4.1.1) - for a time-shifted FIFO (TS-FIFO) scheduler (see Section 4.1.1)
a time-shift of tshift means that the maximum delay to a C a time-shift of tshift means that the maximum delay to a C
packet is tshift greater than that of an L packet. tshift could packet is tshift greater than that of an L packet. tshift could
be expressed as a multiple of the typical RTT rather than as an be expressed as a multiple of the typical RTT rather than as an
absolute delay. absolute delay.
o The maximum Classic ECN marking probability, p_Cmax, before * The maximum Classic ECN marking probability, p_Cmax, before
switching over to drop. switching over to drop.
2.5.2.2. Monitoring 2.5.2.2. Monitoring
An experimental DualQ Coupled AQM SHOULD allow the operator to An experimental DualQ Coupled AQM SHOULD allow the operator to
monitor each of the following operational statistics on demand, per monitor each of the following operational statistics on demand, per
queue and per configurable sample interval, for performance queue and per configurable sample interval, for performance
monitoring and perhaps also for accounting in some cases: monitoring and perhaps also for accounting in some cases:
o Bits forwarded, from which utilization can be calculated; * Bits forwarded, from which utilization can be calculated;
o Total packets in the three categories: arrived, presented to the * Total packets in the three categories: arrived, presented to the
AQM, and forwarded. The difference between the first two will AQM, and forwarded. The difference between the first two will
measure any non-AQM tail discard. The difference between the last measure any non-AQM tail discard. The difference between the last
two will measure proactive AQM discard; two will measure proactive AQM discard;
o ECN packets marked, non-ECN packets dropped, ECN packets dropped, * ECN packets marked, non-ECN packets dropped, ECN packets dropped,
which can be combined with the three total packet counts above to which can be combined with the three total packet counts above to
calculate marking and dropping probabilities; calculate marking and dropping probabilities;
o Queue delay (not including serialization delay of the head packet * Queue delay (not including serialization delay of the head packet
or medium acquisition delay) - see further notes below. or medium acquisition delay) - see further notes below.
Unlike the other statistics, queue delay cannot be captured in a Unlike the other statistics, queue delay cannot be captured in a
simple accumulating counter. Therefore the type of queue delay simple accumulating counter. Therefore the type of queue delay
statistics produced (mean, percentiles, etc.) will depend on statistics produced (mean, percentiles, etc.) will depend on
implementation constraints. To facilitate comparative evaluation implementation constraints. To facilitate comparative evaluation
of different implementations and approaches, an implementation of different implementations and approaches, an implementation
SHOULD allow mean and 99th percentile queue delay to be derived SHOULD allow mean and 99th percentile queue delay to be derived
(per queue per sample interval). A relatively simple way to do (per queue per sample interval). A relatively simple way to do
this would be to store a coarse-grained histogram of queue delay. this would be to store a coarse-grained histogram of queue delay.
skipping to change at page 21, line 31 skipping to change at page 21, line 45
edges that represent contiguous ranges of queue delay. Then, over edges that represent contiguous ranges of queue delay. Then, over
a sample interval, each bin would accumulate a count of the number a sample interval, each bin would accumulate a count of the number
of packets that had fallen within each range. The maximum queue of packets that had fallen within each range. The maximum queue
delay per queue per interval MAY also be recorded. delay per queue per interval MAY also be recorded.
2.5.2.3. Anomaly Detection 2.5.2.3. Anomaly Detection
An experimental DualQ Coupled AQM SHOULD asynchronously report the An experimental DualQ Coupled AQM SHOULD asynchronously report the
following data about anomalous conditions: following data about anomalous conditions:
o Start-time and duration of overload state. * Start-time and duration of overload state.
A hysteresis mechanism SHOULD be used to prevent flapping in and A hysteresis mechanism SHOULD be used to prevent flapping in and
out of overload causing an event storm. For instance, exit from out of overload causing an event storm. For instance, exit from
overload state could trigger one report, but also latch a timer. overload state could trigger one report, but also latch a timer.
Then, during that time, if the AQM enters and exits overload state Then, during that time, if the AQM enters and exits overload state
any number of times, the duration in overload state is accumulated any number of times, the duration in overload state is accumulated
but no new report is generated until the first time the AQM is out but no new report is generated until the first time the AQM is out
of overload once the timer has expired. of overload once the timer has expired.
2.5.2.4. Deployment, Coexistence and Scaling 2.5.2.4. Deployment, Coexistence and Scaling
skipping to change at page 22, line 46 skipping to change at page 23, line 18
drop. These choices need to be made either by the developer or by drop. These choices need to be made either by the developer or by
operator policy, rather than by the IETF. operator policy, rather than by the IETF.
4.1.1. Avoiding Classic Starvation: Sacrifice L4S Throughput or Delay? 4.1.1. Avoiding Classic Starvation: Sacrifice L4S Throughput or Delay?
Priority of L4S is required to be conditional to avoid total Priority of L4S is required to be conditional to avoid total
starvation of Classic by heavy L4S traffic. This raises the question starvation of Classic by heavy L4S traffic. This raises the question
of whether to sacrifice L4S throughput or L4S delay (or some other of whether to sacrifice L4S throughput or L4S delay (or some other
policy) to mitigate starvation of Classic: policy) to mitigate starvation of Classic:
Sacrifice L4S throughput: By using weighted round robin as the Sacrifice L4S throughput: By using weighted round robin as the
conditional priority scheduler, the L4S service can sacrifice some conditional priority scheduler, the L4S service can sacrifice some
throughput during overload. This can either be thought of as throughput during overload. This can either be thought of as
guaranteeing a minimum throughput service for Classic traffic, or guaranteeing a minimum throughput service for Classic traffic, or
as guaranteeing a maximum delay for a packet at the head of the as guaranteeing a maximum delay for a packet at the head of the
Classic queue. Classic queue.
The scheduling weight of the Classic queue should be small The scheduling weight of the Classic queue should be small
(e.g. 1/16). Then, in most traffic scenarios the scheduler will (e.g. 1/16). Then, in most traffic scenarios the scheduler will
not interfere and it will not need to - the coupling mechanism and not interfere and it will not need to - the coupling mechanism and
the end-systems will share out the capacity across both queues as the end-systems will share out the capacity across both queues as
skipping to change at page 26, line 27 skipping to change at page 27, line 7
Ing Jyh (Inton) Tsang of Nokia, Belgium built the End-to-End Data Ing Jyh (Inton) Tsang of Nokia, Belgium built the End-to-End Data
Centre to the Home broadband testbed on which DualQ Coupled AQM Centre to the Home broadband testbed on which DualQ Coupled AQM
implementations were tested. implementations were tested.
7. References 7. References
7.1. Normative References 7.1. Normative References
[I-D.ietf-tsvwg-ecn-l4s-id] [I-D.ietf-tsvwg-ecn-l4s-id]
Schepper, K. D. and B. Briscoe, "Explicit Congestion Schepper, K. D. and B. Briscoe, "Explicit Congestion
Notification (ECN) Protocol for Ultra-Low Queuing Delay Notification (ECN) Protocol for Very Low Queuing Delay
(L4S)", draft-ietf-tsvwg-ecn-l4s-id-14 (work in progress), (L4S)", Work in Progress, Internet-Draft, draft-ietf-
March 2021. tsvwg-ecn-l4s-id-19, 26 July 2021,
<https://datatracker.ietf.org/doc/html/draft-ietf-tsvwg-
ecn-l4s-id-19>.
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, Requirement Levels", BCP 14, RFC 2119,
DOI 10.17487/RFC2119, March 1997, DOI 10.17487/RFC2119, March 1997,
<https://www.rfc-editor.org/info/rfc2119>. <https://www.rfc-editor.org/info/rfc2119>.
[RFC3168] Ramakrishnan, K., Floyd, S., and D. Black, "The Addition [RFC3168] Ramakrishnan, K., Floyd, S., and D. Black, "The Addition
of Explicit Congestion Notification (ECN) to IP", of Explicit Congestion Notification (ECN) to IP",
RFC 3168, DOI 10.17487/RFC3168, September 2001, RFC 3168, DOI 10.17487/RFC3168, September 2001,
<https://www.rfc-editor.org/info/rfc3168>. <https://www.rfc-editor.org/info/rfc3168>.
skipping to change at page 28, line 13 skipping to change at page 28, line 34
<https://arxiv.org/abs/1904.07339>. <https://arxiv.org/abs/1904.07339>.
[DCttH15] De Schepper, K., Bondarenko, O., Briscoe, B., and I. [DCttH15] De Schepper, K., Bondarenko, O., Briscoe, B., and I.
Tsang, "`Data Centre to the Home': Ultra-Low Latency for Tsang, "`Data Centre to the Home': Ultra-Low Latency for
All", RITE project Technical Report , 2015, All", RITE project Technical Report , 2015,
<http://riteproject.eu/publications/>. <http://riteproject.eu/publications/>.
[DOCSIS3.1] [DOCSIS3.1]
CableLabs, "MAC and Upper Layer Protocols Interface CableLabs, "MAC and Upper Layer Protocols Interface
(MULPI) Specification, CM-SP-MULPIv3.1", Data-Over-Cable (MULPI) Specification, CM-SP-MULPIv3.1", Data-Over-Cable
Service Interface Specifications DOCSIS(R) 3.1 Version i17 Service Interface Specifications DOCSIS® 3.1 Version i17
or later, January 2019, <https://specification- or later, 21 January 2019, <https://specification-
search.cablelabs.com/CM-SP-MULPIv3.1>. search.cablelabs.com/CM-SP-MULPIv3.1>.
[DualPI2Linux] [DualPI2Linux]
Albisser, O., De Schepper, K., Briscoe, B., Tilmans, O., Albisser, O., De Schepper, K., Briscoe, B., Tilmans, O.,
and H. Steen, "DUALPI2 - Low Latency, Low Loss and and H. Steen, "DUALPI2 - Low Latency, Low Loss and
Scalable (L4S) AQM", Proc. Linux Netdev 0x13 , March 2019, Scalable (L4S) AQM", Proc. Linux Netdev 0x13 , March 2019,
<https://www.netdevconf.org/0x13/session.html?talk- <https://www.netdevconf.org/0x13/session.html?talk-
DUALPI2-AQM>. DUALPI2-AQM>.
[DualQ-Test] [DualQ-Test]
Steen, H., "Destruction Testing: Ultra-Low Delay using Steen, H., "Destruction Testing: Ultra-Low Delay using
Dual Queue Coupled Active Queue Management", Masters Dual Queue Coupled Active Queue Management", Masters
Thesis, Dept of Informatics, Uni Oslo , May 2017. Thesis, Dept of Informatics, Uni Oslo , May 2017,
<https://www.duo.uio.no/bitstream/handle/10852/57424/
thesis-henrste.pdf?sequence=1>.
[I-D.briscoe-docsis-q-protection] [I-D.briscoe-docsis-q-protection]
Briscoe, B. and G. White, "Queue Protection to Preserve Briscoe, B. and G. White, "Queue Protection to Preserve
Low Latency", draft-briscoe-docsis-q-protection-00 (work Low Latency", Work in Progress, Internet-Draft, draft-
in progress), July 2019. briscoe-docsis-q-protection-00, 8 July 2019,
<https://datatracker.ietf.org/doc/html/draft-briscoe-
docsis-q-protection-00>.
[I-D.briscoe-iccrg-prague-congestion-control] [I-D.briscoe-iccrg-prague-congestion-control]
Schepper, K. D., Tilmans, O., and B. Briscoe, "Prague Schepper, K. D., Tilmans, O., and B. Briscoe, "Prague
Congestion Control", draft-briscoe-iccrg-prague- Congestion Control", Work in Progress, Internet-Draft,
congestion-control-00 (work in progress), March 2021. draft-briscoe-iccrg-prague-congestion-control-00, 9 March
2021, <https://datatracker.ietf.org/doc/html/draft-
briscoe-iccrg-prague-congestion-control-00>.
[I-D.briscoe-tsvwg-l4s-diffserv] [I-D.briscoe-tsvwg-l4s-diffserv]
Briscoe, B., "Interactions between Low Latency, Low Loss, Briscoe, B., "Interactions between Low Latency, Low Loss,
Scalable Throughput (L4S) and Differentiated Services", Scalable Throughput (L4S) and Differentiated Services",
draft-briscoe-tsvwg-l4s-diffserv-02 (work in progress), Work in Progress, Internet-Draft, draft-briscoe-tsvwg-l4s-
November 2018. diffserv-02, 4 November 2018,
<https://datatracker.ietf.org/doc/html/draft-briscoe-
tsvwg-l4s-diffserv-02>.
[I-D.cardwell-iccrg-bbr-congestion-control] [I-D.cardwell-iccrg-bbr-congestion-control]
Cardwell, N., Cheng, Y., Yeganeh, S. H., and V. Jacobson, Cardwell, N., Cheng, Y., Yeganeh, S. H., and V. Jacobson,
"BBR Congestion Control", draft-cardwell-iccrg-bbr- "BBR Congestion Control", Work in Progress, Internet-
congestion-control-00 (work in progress), July 2017. Draft, draft-cardwell-iccrg-bbr-congestion-control-00, 3
July 2017, <https://datatracker.ietf.org/doc/html/draft-
cardwell-iccrg-bbr-congestion-control-00>.
[I-D.ietf-tsvwg-l4s-arch] [I-D.ietf-tsvwg-l4s-arch]
Briscoe, B., Schepper, K. D., Bagnulo, M., and G. White, Briscoe, B., Schepper, K. D., Bagnulo, M., and G. White,
"Low Latency, Low Loss, Scalable Throughput (L4S) Internet "Low Latency, Low Loss, Scalable Throughput (L4S) Internet
Service: Architecture", draft-ietf-tsvwg-l4s-arch-08 (work Service: Architecture", Work in Progress, Internet-Draft,
in progress), November 2020. draft-ietf-tsvwg-l4s-arch-10, 1 July 2021,
<https://datatracker.ietf.org/doc/html/draft-ietf-tsvwg-
l4s-arch-10>.
[I-D.ietf-tsvwg-nqb] [I-D.ietf-tsvwg-nqb]
White, G. and T. Fossati, "A Non-Queue-Building Per-Hop White, G. and T. Fossati, "A Non-Queue-Building Per-Hop
Behavior (NQB PHB) for Differentiated Services", draft- Behavior (NQB PHB) for Differentiated Services", Work in
ietf-tsvwg-nqb-05 (work in progress), March 2021. Progress, Internet-Draft, draft-ietf-tsvwg-nqb-07, 28 July
2021, <https://datatracker.ietf.org/doc/html/draft-ietf-
tsvwg-nqb-07>.
[L4Sdemo16] [L4Sdemo16]
Bondarenko, O., De Schepper, K., Tsang, I., and B. Bondarenko, O., De Schepper, K., Tsang, I., and B.
Briscoe, "Ultra-Low Delay for All: Live Experience, Live Briscoe, "Ultra-Low Delay for All: Live Experience, Live
Analysis", Proc. MMSYS'16 pp33:1--33:4, May 2016, Analysis", Proc. MMSYS'16 pp33:1--33:4, May 2016,
<http://dl.acm.org/citation.cfm?doid=2910017.2910633 <http://dl.acm.org/citation.cfm?doid=2910017.2910633
(videos of demos: (videos of demos:
https://riteproject.eu/dctth/#1511dispatchwg )>. https://riteproject.eu/dctth/#1511dispatchwg )>.
[Labovitz10] [Labovitz10]
Labovitz, C., Iekel-Johnson, S., McPherson, D., Oberheide, Labovitz, C., Iekel-Johnson, S., McPherson, D., Oberheide,
J., and F. Jahanian, "Internet Inter-Domain Traffic", Proc J., and F. Jahanian, "Internet Inter-Domain Traffic", Proc
ACM SIGCOMM; ACM CCR 40(4):75--86, August 2010, ACM SIGCOMM; ACM CCR 40(4):75--86, August 2010,
<https://doi.org/10.1145/1851275.1851194>. <https://doi.org/10.1145/1851275.1851194>.
[LLD] White, G., Sundaresan, K., and B. Briscoe, "Low Latency [LLD] White, G., Sundaresan, K., and B. Briscoe, "Low Latency
DOCSIS: Technology Overview", CableLabs White Paper , DOCSIS: Technology Overview", CableLabs White Paper ,
February 2019, <https://cablela.bs/low-latency-docsis- February 2019, <https://cablela.bs/low-latency-docsis-
technology-overview-february-2019>. technology-overview-february-2019>.
[Mathis09] [Mathis09] Mathis, M., "Relentless Congestion Control", PFLDNeT'09 ,
Mathis, M., "Relentless Congestion Control", PFLDNeT'09 ,
May 2009, <http://www.hpcc.jp/pfldnet2009/ May 2009, <http://www.hpcc.jp/pfldnet2009/
Program_files/1569198525.pdf>. Program_files/1569198525.pdf>.
[MEDF] Menth, M., Schmid, M., Heiss, H., and T. Reim, "MEDF - a [MEDF] Menth, M., Schmid, M., Heiss, H., and T. Reim, "MEDF - a
simple scheduling algorithm for two real-time transport simple scheduling algorithm for two real-time transport
service classes with application in the UTRAN", Proc. IEEE service classes with application in the UTRAN", Proc. IEEE
Conference on Computer Communications (INFOCOM'03) Vol.2 Conference on Computer Communications (INFOCOM'03) Vol.2
pp.1116-1122, March 2003. pp.1116-1122, March 2003,
<http://infocom2003.ieee-infocom.org/papers/27_04.PDF>.
[PI2] De Schepper, K., Bondarenko, O., Briscoe, B., and I. [PI2] De Schepper, K., Bondarenko, O., Briscoe, B., and I.
Tsang, "PI2: A Linearized AQM for both Classic and Tsang, "PI2: A Linearized AQM for both Classic and
Scalable TCP", ACM CoNEXT'16 , December 2016, Scalable TCP", ACM CoNEXT'16 , December 2016,
<https://riteproject.files.wordpress.com/2015/10/ <https://riteproject.files.wordpress.com/2015/10/
pi2_conext.pdf>. pi2_conext.pdf>.
[PI2param] [PI2param] Briscoe, B., "PI2 Parameters", Technical Report TR-BB-
Briscoe, B., "PI2 Parameters", Technical Report TR-BB-
2021-001 arXiv:2107.01003 [cs.NI], July 2021, 2021-001 arXiv:2107.01003 [cs.NI], July 2021,
<https://arxiv.org/abs/2107.01003>. <https://arxiv.org/abs/2107.01003>.
[PragueLinux] [PragueLinux]
Briscoe, B., De Schepper, K., Albisser, O., Misund, J., Briscoe, B., De Schepper, K., Albisser, O., Misund, J.,
Tilmans, O., Kuehlewind, M., and A. Ahmed, "Implementing Tilmans, O., K├╝hlewind, M., and A.S. Ahmed, "Implementing
the `TCP Prague' Requirements for Low Latency Low Loss the `TCP Prague' Requirements for Low Latency Low Loss
Scalable Throughput (L4S)", Proc. Linux Netdev 0x13 , Scalable Throughput (L4S)", Proc. Linux Netdev 0x13 ,
March 2019, <https://www.netdevconf.org/0x13/ March 2019, <https://www.netdevconf.org/0x13/
session.html?talk-tcp-prague-l4s>. session.html?talk-tcp-prague-l4s>.
[RFC0970] Nagle, J., "On Packet Switches With Infinite Storage", [RFC0970] Nagle, J., "On Packet Switches With Infinite Storage",
RFC 970, DOI 10.17487/RFC0970, December 1985, RFC 970, DOI 10.17487/RFC0970, December 1985,
<https://www.rfc-editor.org/info/rfc970>. <https://www.rfc-editor.org/info/rfc970>.
[RFC2309] Braden, B., Clark, D., Crowcroft, J., Davie, B., Deering, [RFC2309] Braden, B., Clark, D., Crowcroft, J., Davie, B., Deering,
S., Estrin, D., Floyd, S., Jacobson, V., Minshall, G., S., Estrin, D., Floyd, S., Jacobson, V., Minshall, G.,
Partridge, C., Peterson, L., Ramakrishnan, K., Shenker, Partridge, C., Peterson, L., Ramakrishnan, K., Shenker,
S., Wroclawski, J., and L. Zhang, "Recommendations on S., Wroclawski, J., and L. Zhang, "Recommendations on
Queue Management and Congestion Avoidance in the Queue Management and Congestion Avoidance in the
Internet", RFC 2309, DOI 10.17487/RFC2309, April 1998, Internet", RFC 2309, DOI 10.17487/RFC2309, April 1998,
<https://www.rfc-editor.org/info/rfc2309>. <https://www.rfc-editor.org/info/rfc2309>.
[RFC3246] Davie, B., Charny, A., Bennet, J., Benson, K., Le Boudec, [RFC3246] Davie, B., Charny, A., Bennet, J.C.R., Benson, K., Le
J., Courtney, W., Davari, S., Firoiu, V., and D. Boudec, J.Y., Courtney, W., Davari, S., Firoiu, V., and D.
Stiliadis, "An Expedited Forwarding PHB (Per-Hop Stiliadis, "An Expedited Forwarding PHB (Per-Hop
Behavior)", RFC 3246, DOI 10.17487/RFC3246, March 2002, Behavior)", RFC 3246, DOI 10.17487/RFC3246, March 2002,
<https://www.rfc-editor.org/info/rfc3246>. <https://www.rfc-editor.org/info/rfc3246>.
[RFC3649] Floyd, S., "HighSpeed TCP for Large Congestion Windows", [RFC3649] Floyd, S., "HighSpeed TCP for Large Congestion Windows",
RFC 3649, DOI 10.17487/RFC3649, December 2003, RFC 3649, DOI 10.17487/RFC3649, December 2003,
<https://www.rfc-editor.org/info/rfc3649>. <https://www.rfc-editor.org/info/rfc3649>.
[RFC5033] Floyd, S. and M. Allman, "Specifying New Congestion [RFC5033] Floyd, S. and M. Allman, "Specifying New Congestion
Control Algorithms", BCP 133, RFC 5033, Control Algorithms", BCP 133, RFC 5033,
skipping to change at page 32, line 5 skipping to change at page 32, line 35
[RFC8312] Rhee, I., Xu, L., Ha, S., Zimmermann, A., Eggert, L., and [RFC8312] Rhee, I., Xu, L., Ha, S., Zimmermann, A., Eggert, L., and
R. Scheffenegger, "CUBIC for Fast Long-Distance Networks", R. Scheffenegger, "CUBIC for Fast Long-Distance Networks",
RFC 8312, DOI 10.17487/RFC8312, February 2018, RFC 8312, DOI 10.17487/RFC8312, February 2018,
<https://www.rfc-editor.org/info/rfc8312>. <https://www.rfc-editor.org/info/rfc8312>.
[SCReAM] Johansson, I., "SCReAM", github repository; , [SCReAM] Johansson, I., "SCReAM", github repository; ,
<https://github.com/EricssonResearch/scream/blob/master/ <https://github.com/EricssonResearch/scream/blob/master/
README.md>. README.md>.
[SigQ-Dyn] [SigQ-Dyn] Briscoe, B., "Rapid Signalling of Queue Dynamics",
Briscoe, B., "Rapid Signalling of Queue Dynamics",
Technical Report TR-BB-2017-001 arXiv:1904.07044 [cs.NI], Technical Report TR-BB-2017-001 arXiv:1904.07044 [cs.NI],
September 2017, <https://arxiv.org/abs/1904.07044>. September 2017, <https://arxiv.org/abs/1904.07044>.
Appendix A. Example DualQ Coupled PI2 Algorithm Appendix A. Example DualQ Coupled PI2 Algorithm
As a first concrete example, the pseudocode below gives the DualPI2 As a first concrete example, the pseudocode below gives the DualPI2
algorithm. DualPI2 follows the structure of the DualQ Coupled AQM algorithm. DualPI2 follows the structure of the DualQ Coupled AQM
framework in Figure 1. A simple ramp function (configured in units framework in Figure 1. A simple ramp function (configured in units
of queuing time) with unsmoothed ECN marking is used for the Native of queuing time) with unsmoothed ECN marking is used for the Native
L4S AQM. The ramp can also be configured as a step function. The L4S AQM. The ramp can also be configured as a step function. The
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[DualPI2Linux]. The specification of the DualQ Coupled AQM for [DualPI2Linux]. The specification of the DualQ Coupled AQM for
DOCSIS cable modems and CMTSs is available in [DOCSIS3.1] and DOCSIS cable modems and CMTSs is available in [DOCSIS3.1] and
explained in [LLD]. explained in [LLD].
A.1. Pass #1: Core Concepts A.1. Pass #1: Core Concepts
The pseudocode manipulates three main structures of variables: the The pseudocode manipulates three main structures of variables: the
packet (pkt), the L4S queue (lq) and the Classic queue (cq). The packet (pkt), the L4S queue (lq) and the Classic queue (cq). The
pseudocode consists of the following six functions: pseudocode consists of the following six functions:
o The initialization function dualpi2_params_init(...) (Figure 2) * The initialization function dualpi2_params_init(...) (Figure 2)
that sets parameter defaults (the API for setting non-default that sets parameter defaults (the API for setting non-default
values is omitted for brevity) values is omitted for brevity)
o The enqueue function dualpi2_enqueue(lq, cq, pkt) (Figure 3) * The enqueue function dualpi2_enqueue(lq, cq, pkt) (Figure 3)
o The dequeue function dualpi2_dequeue(lq, cq, pkt) (Figure 4)
o The recurrence function recur(q, likelihood) for de-randomized ECN * The dequeue function dualpi2_dequeue(lq, cq, pkt) (Figure 4)
* The recurrence function recur(q, likelihood) for de-randomized ECN
marking (shown at the end of Figure 4). marking (shown at the end of Figure 4).
o The L4S AQM function laqm(qdelay) (Figure 5) used to calculate the * The L4S AQM function laqm(qdelay) (Figure 5) used to calculate the
ECN-marking probability for the L4S queue ECN-marking probability for the L4S queue
o The base AQM function that implements the PI algorithm * The base AQM function that implements the PI algorithm
dualpi2_update(lq, cq) (Figure 6) used to regularly update the dualpi2_update(lq, cq) (Figure 6) used to regularly update the
base probability (p'), which is squared for the Classic AQM as base probability (p'), which is squared for the Classic AQM as
well as being coupled across to the L4S queue. well as being coupled across to the L4S queue.
It also uses the following functions that are not shown in full here: It also uses the following functions that are not shown in full here:
o scheduler(), which selects between the head packets of the two * scheduler(), which selects between the head packets of the two
queues; the choice of scheduler technology is discussed later; queues; the choice of scheduler technology is discussed later;
o cq.len() or lq.len() returns the current length (aka. backlog) of * cq.len() or lq.len() returns the current length (aka. backlog) of
the relevant queue in bytes; the relevant queue in bytes;
o cq.time() or lq.time() returns the current queuing delay * cq.time() or lq.time() returns the current queuing delay
(aka. sojourn time or service time) of the relevant queue in units (aka. sojourn time or service time) of the relevant queue in units
of time (see Note a); of time (see Note a);
o mark(pkt) and drop(pkt) for ECN-marking and dropping a packet; * mark(pkt) and drop(pkt) for ECN-marking and dropping a packet;
In experiments so far (building on experiments with PIE) on broadband In 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 access links ranging from 4 Mb/s to 200 Mb/s with base RTTs from 5 ms
to 100 ms, DualPI2 achieves good results with the default parameters to 100 ms, DualPI2 achieves good results with the default parameters
in Figure 2. The parameters are categorised by whether they relate in Figure 2. The parameters are categorised by whether they relate
to the Base PI2 AQM, the L4S AQM or the framework coupling them to the Base PI2 AQM, the L4S AQM or the framework coupling them
together. Constants and variables derived from these parameters are together. Constants and variables derived from these parameters are
also included at the end of each category. Each parameter is also included at the end of each category. Each parameter is
explained as it is encountered in the walk-through of the pseudocode explained as it is encountered in the walk-through of the pseudocode
below, and the rationale for the chosen defaults are given so that below, and the rationale for the chosen defaults are given so that
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2: if ( lq.len() + cq.len() + MTU > limit) 2: if ( lq.len() + cq.len() + MTU > limit)
3: drop(pkt) % drop packet if buffer is full 3: drop(pkt) % drop packet if buffer is full
4: timestamp(pkt) % attach arrival time to packet 4: timestamp(pkt) % attach arrival time to packet
5: % Packet classifier 5: % Packet classifier
6: if ( ecn(pkt) modulo 2 == 1 ) % ECN bits = ECT(1) or CE 6: if ( ecn(pkt) modulo 2 == 1 ) % ECN bits = ECT(1) or CE
7: lq.enqueue(pkt) 7: lq.enqueue(pkt)
8: else % ECN bits = not-ECT or ECT(0) 8: else % ECN bits = not-ECT or ECT(0)
9: cq.enqueue(pkt) 9: cq.enqueue(pkt)
10: } 10: }
Figure 3: Example Enqueue Pseudocode for DualQ Coupled PI2 AQM Figure 3: Example Enqueue Pseudocode for DualQ Coupled PI2 AQM
1: dualpi2_dequeue(lq, cq, pkt) { % Couples L4S & Classic queues 1: dualpi2_dequeue(lq, cq, pkt) { % Couples L4S & Classic queues
2: while ( lq.len() + cq.len() > 0 ) { 2: while ( lq.len() + cq.len() > 0 ) {
3: if ( scheduler() == lq ) { 3: if ( scheduler() == lq ) {
4: lq.dequeue(pkt) % Scheduler chooses lq 4: lq.dequeue(pkt) % Scheduler chooses lq
5: p'_L = laqm(lq.time()) % Native L4S AQM 5: p'_L = laqm(lq.time()) % Native L4S AQM
6: p_L = max(p'_L, p_CL) % Combining function 6: p_L = max(p'_L, p_CL) % Combining function
7: if ( recur(lq, p_L) ) % Linear marking 7: if ( recur(lq, p_L) ) % Linear marking
8: mark(pkt) 8: mark(pkt)
9: } else { 9: } else {
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23: recur(q, likelihood) { % Returns TRUE with a certain likelihood 23: recur(q, likelihood) { % Returns TRUE with a certain likelihood
24: q.count += likelihood 24: q.count += likelihood
25: if (q.count > 1) { 25: if (q.count > 1) {
26: q.count -= 1 26: q.count -= 1
27: return TRUE 27: return TRUE
28: } 28: }
29: return FALSE 29: return FALSE
30: } 30: }
Figure 4: Example Dequeue Pseudocode for DualQ Coupled PI2 AQM Figure 4: Example Dequeue Pseudocode for DualQ Coupled PI2 AQM
When packets arrive, first a common queue limit is checked as shown When packets arrive, first a common queue limit is checked as shown
in line 2 of the enqueuing pseudocode in Figure 3. This assumes a in line 2 of the enqueuing pseudocode in Figure 3. This assumes a
shared buffer for the two queues (Note b discusses the merits of shared buffer for the two queues (Note b discusses the merits of
separate buffers). In order to avoid any bias against larger separate buffers). In order to avoid any bias against larger
packets, 1 MTU of space is always allowed and the limit is packets, 1 MTU of space is always allowed and the limit is
deliberately tested before enqueue. deliberately tested before enqueue.
If limit is not exceeded, the packet is timestamped in line 4. This If limit is not exceeded, the packet is timestamped in line 4. This
assumes that queue delay is measured using the sojourn time technique assumes that queue delay is measured using the sojourn time technique
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loop sloppier (for a typical RTT it would double the Classic queue's loop sloppier (for a typical RTT it would double the Classic queue's
feedback delay). feedback delay).
All the dequeue code is contained within a large while loop so that All the dequeue code is contained within a large while loop so that
if it decides to drop a packet, it will continue until it selects a if it decides to drop a packet, it will continue until it selects a
packet to schedule. Line 3 of the dequeue pseudocode is where the packet to schedule. Line 3 of the dequeue pseudocode is where the
scheduler chooses between the L4S queue (lq) and the Classic queue scheduler chooses between the L4S queue (lq) and the Classic queue
(cq). Detailed implementation of the scheduler is not shown (see (cq). Detailed implementation of the scheduler is not shown (see
discussion later). discussion later).
o If an L4S packet is scheduled, in lines 7 and 8 the packet is ECN- * If an L4S packet is scheduled, in lines 7 and 8 the packet is ECN-
marked with likelihood p_L. The recur() function at the end of marked with likelihood p_L. The recur() function at the end of
Figure 4 is used, which is preferred over random marking because Figure 4 is used, which is preferred over random marking because
it avoids delay due to randomization when interpreting congestion it avoids delay due to randomization when interpreting congestion
signals, but it still desynchronizes the saw-teeth of the flows. signals, but it still desynchronizes the saw-teeth of the flows.
Line 6 calculates p_L as the maximum of the coupled L4S Line 6 calculates p_L as the maximum of the coupled L4S
probability p_CL and the probability from the native L4S AQM p'_L. probability p_CL and the probability from the native L4S AQM p'_L.
This implements the max() function shown in Figure 1 to couple the This implements the max() function shown in Figure 1 to couple the
outputs of the two AQMs together. Of the two probabilities input outputs of the two AQMs together. Of the two probabilities input
to p_L in line 6: to p_L in line 6:
* p'_L is calculated per packet in line 5 by the laqm() function - p'_L is calculated per packet in line 5 by the laqm() function
(see Figure 5), (see Figure 5),
* Whereas p_CL is maintained by the dualpi2_update() function - Whereas p_CL is maintained by the dualpi2_update() function
which runs every Tupdate (Tupdate is set in line 13 of which runs every Tupdate (Tupdate is set in line 13 of
Figure 2). Figure 2).
o If a Classic packet is scheduled, lines 10 to 17 drop or mark the * If a Classic packet is scheduled, lines 10 to 17 drop or mark the
packet with probability p_C. packet with probability p_C.
The Native L4S AQM algorithm (Figure 5) is a ramp function, similar The Native L4S AQM algorithm (Figure 5) is a ramp function, similar
to the RED algorithm, but simplified as follows: to the RED algorithm, but simplified as follows:
o The extent of the ramp is defined in units of queuing delay, not * The extent of the ramp is defined in units of queuing delay, not
bytes, so that configuration remains invariant as the queue bytes, so that configuration remains invariant as the queue
departure rate varies. departure rate varies.
o It uses instantaneous queueing delay, which avoids the complexity * It uses instantaneous queueing delay, which avoids the complexity
of smoothing, but also avoids embedding a worst-case RTT of of smoothing, but also avoids embedding a worst-case RTT of
smoothing delay in the network (see Section 2.1). smoothing delay in the network (see Section 2.1).
o The ramp rises linearly directly from 0 to 1, not to an * The ramp rises linearly directly from 0 to 1, not to an
intermediate value of p'_L as RED would, because there is no need intermediate value of p'_L as RED would, because there is no need
to keep ECN marking probability low. to keep ECN marking probability low.
o Marking does not have to be randomized. Determinism is used * Marking does not have to be randomized. Determinism is used
instead of randomness; to reduce the delay necessary to smooth out instead of randomness; to reduce the delay necessary to smooth out
the noise of randomness from the signal. the noise of randomness from the signal.
The ramp function requires two configuration parameters, the minimum The ramp function requires two configuration parameters, the minimum
threshold (minTh) and the width of the ramp (range), both in units of threshold (minTh) and the width of the ramp (range), both in units of
queuing time), as shown in lines 18 & 19 of the initialization queuing time), as shown in lines 18 & 19 of the initialization
function in Figure 2. The ramp function can be configured as a step function in Figure 2. The ramp function can be configured as a step
(see Note c). (see Note c).
Although the DCTCP paper [Alizadeh-stability] recommends an ECN Although the DCTCP paper [Alizadeh-stability] recommends an ECN
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Figure 5: Example Pseudocode for the Native L4S AQM Figure 5: Example Pseudocode for the Native L4S AQM
1: dualpi2_update(lq, cq) { % Update p' every Tupdate 1: dualpi2_update(lq, cq) { % Update p' every Tupdate
2: curq = cq.time() % use queuing time of first-in Classic packet 2: curq = cq.time() % use queuing time of first-in Classic packet
3: p' = p' + alpha * (curq - target) + beta * (curq - prevq) 3: p' = p' + alpha * (curq - target) + beta * (curq - prevq)
4: p_CL = k * p' % Coupled L4S prob = base prob * coupling factor 4: p_CL = k * p' % Coupled L4S prob = base prob * coupling factor
5: p_C = p'^2 % Classic prob = (base prob)^2 5: p_C = p'^2 % Classic prob = (base prob)^2
6: prevq = curq 6: prevq = curq
7: } 7: }
(Clamping p' within the range [0,1] omitted for clarity - see text) Figure 6: Example PI-Update Pseudocode for DualQ Coupled PI2 AQM
Figure 6: Example PI-Update Pseudocode for DualQ Coupled PI2 AQM (Clamping p' within the range [0,1] omitted for clarity - see text)
The coupled marking probability, p_CL depends on the base probability The coupled marking probability, p_CL depends on the base probability
(p'), which is kept up to date by the core PI algorithm in Figure 6 (p'), which is kept up to date by the core PI algorithm in Figure 6
executed every Tupdate. executed every Tupdate.
Note that p' solely depends on the queuing time in the Classic queue. Note that p' solely depends on the queuing time in the Classic queue.
In line 2, the current queuing delay (curq) is evaluated from how In line 2, the current queuing delay (curq) is evaluated from how
long the head packet was in the Classic queue (cq). The function long the head packet was in the Classic queue (cq). The function
cq.time() (not shown) subtracts the time stamped at enqueue from the cq.time() (not shown) subtracts the time stamped at enqueue from the
current time (see Note a) and implicitly takes the current queuing current time (see Note a) and implicitly takes the current queuing
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is for the default to be a good compromise for anywhere in the is for the default to be a good compromise for anywhere in the
intended deployment environment---the public Internet. The target intended deployment environment---the public Internet. The target
queuing delay is related to the typical base RTT, RTT_typ, by two queuing delay is related to the typical base RTT, RTT_typ, by two
factors, shown in the comment on line 9 of Figure 2 as target = factors, shown in the comment on line 9 of Figure 2 as target =
RTT_typ * 0.22 * 2. These factors ensure that, in a large proportion RTT_typ * 0.22 * 2. These factors ensure that, in a large proportion
of cases (say 90%), the sawtooth variations in RTT will fit within of cases (say 90%), the sawtooth variations in RTT will fit within
the buffer without underutilizing the link. Frankly, these factors the buffer without underutilizing the link. Frankly, these factors
are educated guesses, but with the emphasis closer to 'educated' than are educated guesses, but with the emphasis closer to 'educated' than
to 'guess' (see [PI2param] for background investigations): to 'guess' (see [PI2param] for background investigations):
o RTT_typ is taken as 34 ms. This is based on an average CDN * RTT_typ is taken as 34 ms. This is based on an average CDN
latency measured in each country weighted by the number of latency measured in each country weighted by the number of
Internet users in that country to produce an overall weighted Internet users in that country to produce an overall weighted
average for the Internet [PI2param]. average for the Internet [PI2param].
o The factor 0.22 is a geometry factor that characterizes the shape * The factor 0.22 is a geometry factor that characterizes the shape
of the sawteeth of prevalent Classic congestion controllers. The of the sawteeth of prevalent Classic congestion controllers. The
geometry factor is the difference between the minimum and the geometry factor is the difference between the minimum and the
average queue delays of the sawteeth, relative to the base RTT. average queue delays of the sawteeth, relative to the base RTT.
For instance, the geometry factor of standard Reno is 0.5. For instance, the geometry factor of standard Reno is 0.5.
According to the census of congestion controllers conducted by According to the census of congestion controllers conducted by
Mishra _et al_ in Jul-Oct 2019 [CCcensus19], most Classic TCP Mishra _et al_ in Jul-Oct 2019 [CCcensus19], most Classic TCP
traffic uses Cubic. And, according to the analysis in [PI2param], traffic uses Cubic. And, according to the analysis in [PI2param],
if running over a PI2 AQM, a large proportion of this Cubic if running over a PI2 AQM, a large proportion of this Cubic
traffic would be in its Reno-Friendly mode, which has a geometry traffic would be in its Reno-Friendly mode, which has a geometry
factor of 0.21 (Linux implementation). The rest of the Cubic factor of 0.21 (Linux implementation). The rest of the Cubic
traffic would be in true Cubic mode, which has a geometry factor traffic would be in true Cubic mode, which has a geometry factor
of 0.32. Without modelling the sawtooth profiles from all the of 0.32. Without modelling the sawtooth profiles from all the
other less prevalent congestion controllers, we estimate a 9:1 other less prevalent congestion controllers, we estimate a 9:1
weighted average of these two, resulting in an average geometry weighted average of these two, resulting in an average geometry
factor of 0.22. factor of 0.22.
o The factor 2, is a safety factor that increases the target queue * The factor 2, is a safety factor that increases the target queue
to allow for the distribution of RTT_typ around its mean. to allow for the distribution of RTT_typ around its mean.
Otherwise the target queue would only avoid underutilization for Otherwise the target queue would only avoid underutilization for
those users below the mean. It also provides a safety margin for those users below the mean. It also provides a safety margin for
the proportion of paths in use that span beyond the distance the proportion of paths in use that span beyond the distance
between a user and their local CDN. Currently no data is between a user and their local CDN. Currently no data is
available on the variance of queue delay around the mean in each available on the variance of queue delay around the mean in each
region, so there is plenty of room for this guess to become more region, so there is plenty of room for this guess to become more
educated. educated.
The two 'gain factors' in line 3 of Figure 6, alpha and beta, The two 'gain factors' in line 3 of Figure 6, alpha and beta,
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Tupdate dependent on p'. Instead, in PI2, alpha and beta are Tupdate dependent on p'. Instead, in PI2, alpha and beta are
independent of p' because the squaring applied to Classic traffic independent of p' because the squaring applied to Classic traffic
tunes them inherently. This is explained in [PI2], which also tunes them inherently. This is explained in [PI2], which also
explains why this more principled approach removes the need for most explains why this more principled approach removes the need for most
of the heuristics that had to be added to PIE. of the heuristics that had to be added to PIE.
Nonetheless, an implementer might wish to add selected heuristics to Nonetheless, an implementer might wish to add selected heuristics to
either AQM. For instance the Linux reference DualPI2 implementation either AQM. For instance the Linux reference DualPI2 implementation
includes the following: includes the following:
o Prior to enqueuing an L4S packet, if the L queue contains <2 * Prior to enqueuing an L4S packet, if the L queue contains <2
packets, the packet is flagged to suppress any native L4S AQM packets, the packet is flagged to suppress any native L4S AQM
marking at dequeue (which depends on sojourn time); marking at dequeue (which depends on sojourn time);
o Classic and coupled marking or dropping (i.e. based on p_C and * Classic and coupled marking or dropping (i.e. based on p_C and
p_CL from the PI controller) is only applied to a packet if the p_CL from the PI controller) is only applied to a packet if the
respective queue length in bytes is > 2 MTU (prior to enqueuing respective queue length in bytes is > 2 MTU (prior to enqueuing
the packet or after dequeuing it, depending on whether the AQM is the packet or after dequeuing it, depending on whether the AQM is
configured to be applied at enqueue or dequeue); configured to be applied at enqueue or dequeue);
o In the WRR scheduler, the 'credit' indicating which queue should * In the WRR scheduler, the 'credit' indicating which queue should
transmit is only changed if there are packets in both queues transmit is only changed if there are packets in both queues
(i.e. if there is actual resource contention). This means that a (i.e. if there is actual resource contention). This means that a
properly paced L flow might never be delayed by the WRR. The WRR properly paced L flow might never be delayed by the WRR. The WRR
credit is reset in favour of the L queue when the link is idle. credit is reset in favour of the L queue when the link is idle.
An implementer might also wish to add other heuristics, e.g. burst An implementer might also wish to add other heuristics, e.g. burst
protection [RFC8033] or enhanced burst protection [RFC8034]. protection [RFC8033] or enhanced burst protection [RFC8034].
Notes: Notes:
skipping to change at page 44, line 38 skipping to change at page 45, line 44
14: continue % continue to the top of the while loop 14: continue % continue to the top of the while loop
15: } 15: }
16: mark(pkt) % squared mark 16: mark(pkt) % squared mark
17: } 17: }
18: } 18: }
19: return(pkt) % return the packet and stop 19: return(pkt) % return the packet and stop
20: } 20: }
21: return(NULL) % no packet to dequeue 21: return(NULL) % no packet to dequeue
22: } 22: }
Figure 7: Example Dequeue Pseudocode for DualQ Coupled PI2 AQM Figure 7: Example Dequeue Pseudocode for DualQ Coupled PI2 AQM
(Including Overload Code) (Including Overload Code)
1: dualpi2_update(lq, cq) { % Update p' every Tupdate 1: dualpi2_update(lq, cq) { % Update p' every Tupdate
2a: if ( cq.len() > 0 ) 2a: if ( cq.len() > 0 )
2b: curq = cq.time() %use queuing time of first-in Classic packet 2b: curq = cq.time() %use queuing time of first-in Classic packet
2c: else % Classic queue empty 2c: else % Classic queue empty
2d: curq = lq.time() % use queuing time of first-in L4S packet 2d: curq = lq.time() % use queuing time of first-in L4S packet
3: p' = p' + alpha * (curq - target) + beta * (curq - prevq) 3: p' = p' + alpha * (curq - target) + beta * (curq - prevq)
4: p_CL = p' * k % Coupled L4S prob = base prob * coupling factor 4: p_CL = p' * k % Coupled L4S prob = base prob * coupling factor
5: p_C = p'^2 % Classic prob = (base prob)^2 5: p_C = p'^2 % Classic prob = (base prob)^2
6: prevq = curq 6: prevq = curq
7: } 7: }
Figure 8: Example PI-Update Pseudocode for DualQ Coupled PI2 AQM Figure 8: Example PI-Update Pseudocode for DualQ Coupled PI2 AQM
(Including Overload Code) (Including Overload Code)
The choice of scheduler technology is critical to overload protection The choice of scheduler technology is critical to overload protection
(see Section 4.1). (see Section 4.1).
o A well-understood weighted scheduler such as weighted round robin * A well-understood weighted scheduler such as weighted round robin
(WRR) is recommended. As long as the scheduler weight for Classic (WRR) is recommended. As long as the scheduler weight for Classic
is small (e.g. 1/16), its exact value is unimportant because it is small (e.g. 1/16), its exact value is unimportant because it
does not normally determine capacity shares. The weight is only does not normally determine capacity shares. The weight is only
important to prevent unresponsive L4S traffic starving Classic important to prevent unresponsive L4S traffic starving Classic
traffic. This is because capacity sharing between the queues is traffic. This is because capacity sharing between the queues is
normally determined by the coupled congestion signal, which normally determined by the coupled congestion signal, which
overrides the scheduler, by making L4S sources leave roughly equal overrides the scheduler, by making L4S sources leave roughly equal
per-flow capacity available for Classic flows. per-flow capacity available for Classic flows.
o Alternatively, a time-shifted FIFO (TS-FIFO) could be used. It * Alternatively, a time-shifted FIFO (TS-FIFO) could be used. It
works by selecting the head packet that has waited the longest, works by selecting the head packet that has waited the longest,
biased against the Classic traffic by a time-shift of tshift. To biased against the Classic traffic by a time-shift of tshift. To
implement time-shifted FIFO, the scheduler() function in line 3 of implement time-shifted FIFO, the scheduler() function in line 3 of
the dequeue code would simply be implemented as the scheduler() the dequeue code would simply be implemented as the scheduler()
function at the bottom of Figure 10 in Appendix B. For the public function at the bottom of Figure 10 in Appendix B. For the public
Internet a good value for tshift is 50ms. For private networks Internet a good value for tshift is 50ms. For private networks
with smaller diameter, about 4*target would be reasonable. TS- with smaller diameter, about 4*target would be reasonable. TS-
FIFO is a very simple scheduler, but complexity might need to be FIFO is a very simple scheduler, but complexity might need to be
added to address some deficiencies (which is why it is not added to address some deficiencies (which is why it is not
recommended over WRR): recommended over WRR):
* TS-FIFO does not fully isolate latency in the L4S queue from - TS-FIFO does not fully isolate latency in the L4S queue from
uncontrolled bursts in the Classic queue; uncontrolled bursts in the Classic queue;
* TS-FIFO is only appropriate if time-stamping of packets is - TS-FIFO is only appropriate if time-stamping of packets is
feasible; feasible;
* Even if time-stamping is supported, the sojourn time of the - Even if time-stamping is supported, the sojourn time of the
head packet is always stale. For instance, if a burst arrives head packet is always stale. For instance, if a burst arrives
at an empty queue, the sojourn time will only measure the delay at an empty queue, the sojourn time will only measure the delay
of the burst once the burst is over, even though the queue knew of the burst once the burst is over, even though the queue knew
about it from the start. At the cost of more operations and about it from the start. At the cost of more operations and
more storage, a 'scaled sojourn time' metric of queue delay can more storage, a 'scaled sojourn time' metric of queue delay can
be used, which is the sojourn time of a packet scaled by the be used, which is the sojourn time of a packet scaled by the
ratio of the queue sizes when the packet departed and ratio of the queue sizes when the packet departed and
arrived [SigQ-Dyn]. arrived [SigQ-Dyn].
o A strict priority scheduler would be inappropriate, because it * A strict priority scheduler would be inappropriate, because it
would starve Classic if L4S was overloaded. would starve Classic if L4S was overloaded.
Appendix B. Example DualQ Coupled Curvy RED Algorithm Appendix B. Example DualQ Coupled Curvy RED Algorithm
As another example of a DualQ Coupled AQM algorithm, the pseudocode As another example of a DualQ Coupled AQM algorithm, the pseudocode
below gives the Curvy RED based algorithm. Although the AQM was below gives the Curvy RED based algorithm. Although the AQM was
designed to be efficient in integer arithmetic, to aid understanding designed to be efficient in integer arithmetic, to aid understanding
it is first given using floating point arithmetic (Figure 10). Then, it is first given using floating point arithmetic (Figure 10). Then,
one possible optimization for integer arithmetic is given, also in one possible optimization for integer arithmetic is given, also in
pseudocode (Figure 11). To aid comparison, the line numbers are kept pseudocode (Figure 11). To aid comparison, the line numbers are kept
in step between the two by using letter suffixes where the longer in step between the two by using letter suffixes where the longer
code needs extra lines. code needs extra lines.
B.1. Curvy RED in Pseudocode B.1. Curvy RED in Pseudocode
The pseudocode manipulates three main structures of variables: the The pseudocode manipulates three main structures of variables: the
packet (pkt), the L4S queue (lq) and the Classic queue (cq) and packet (pkt), the L4S queue (lq) and the Classic queue (cq) and
consists of the following five functions: consists of the following five functions:
o The initialization function cred_params_init(...) (Figure 2) that * The initialization function cred_params_init(...) (Figure 2) that
sets parameter defaults (the API for setting non-default values is sets parameter defaults (the API for setting non-default values is
omitted for brevity); omitted for brevity);
o The dequeue function cred_dequeue(lq, cq, pkt) (Figure 4); * The dequeue function cred_dequeue(lq, cq, pkt) (Figure 4);
o The scheduling function scheduler(), which selects between the * The scheduling function scheduler(), which selects between the
head packets of the two queues. head packets of the two queues.
It also uses the following functions that are either shown elsewhere, It also uses the following functions that are either shown elsewhere,
or not shown in full here: or not shown in full here:
o The enqueue function, which is identical to that used for DualPI2, * The enqueue function, which is identical to that used for DualPI2,
dualpi2_enqueue(lq, cq, pkt) in Figure 3; dualpi2_enqueue(lq, cq, pkt) in Figure 3;
o mark(pkt) and drop(pkt) for ECN-marking and dropping a packet; * mark(pkt) and drop(pkt) for ECN-marking and dropping a packet;
* cq.len() or lq.len() returns the current length (aka. backlog) of
o cq.len() or lq.len() returns the current length (aka. backlog) of
the relevant queue in bytes; the relevant queue in bytes;
o cq.time() or lq.time() returns the current queuing delay * cq.time() or lq.time() returns the current queuing delay
(aka. sojourn time or service time) of the relevant queue in units (aka. sojourn time or service time) of the relevant queue in units
of time (see Note a in Appendix A.1). of time (see Note a in Appendix A.1).
Because Curvy RED was evaluated before DualPI2, certain improvements Because Curvy RED was evaluated before DualPI2, certain improvements
introduced for DualPI2 were not evaluated for Curvy RED. In the introduced for DualPI2 were not evaluated for Curvy RED. In the
pseudocode below, the straightforward improvements have been added on pseudocode below, the straightforward improvements have been added on
the assumption they will provide similar benefits, but that has not the assumption they will provide similar benefits, but that has not
been proven experimentally. They are: i) a conditional priority been proven experimentally. They are: i) a conditional priority
scheduler instead of strict priority ii) a time-based threshold for scheduler instead of strict priority ii) a time-based threshold for
the native L4S AQM; iii) ECN support for the Classic AQM. A recent the native L4S AQM; iii) ECN support for the Classic AQM. A recent
skipping to change at page 53, line 37 skipping to change at page 54, line 45
13: continue % continue to the top of the while loop 13: continue % continue to the top of the while loop
14: } 14: }
15: mark(pkt) 15: mark(pkt)
16: } 16: }
17: } 17: }
18: return(pkt) % return the packet and stop here 18: return(pkt) % return the packet and stop here
19: } 19: }
20: return(NULL) % no packet to dequeue 20: return(NULL) % no packet to dequeue
21: } 21: }
Figure 11: Optimised Example Dequeue Pseudocode for Coupled DualQ AQM Figure 11: Optimised Example Dequeue Pseudocode for Coupled DualQ
using Integer Arithmetic AQM using Integer Arithmetic
The two ranges, range_L and range_C are expressed as powers of 2 so The two ranges, range_L and range_C are expressed as powers of 2 so
that division can be implemented as a right bit-shift (>>) in lines 5 that division can be implemented as a right bit-shift (>>) in lines 5
and 10 of the integer variant of the pseudocode (Figure 11). and 10 of the integer variant of the pseudocode (Figure 11).
For the integer variant of the pseudocode, an integer version of the For the integer variant of the pseudocode, an integer version of the
rand() function used at line 25 of the maxrand(function) in Figure 10 rand() function used at line 25 of the maxrand(function) in Figure 10
would be arranged to return an integer in the range 0 <= maxrand() < would be arranged to return an integer in the range 0 <= maxrand() <
2^32 (not shown). This would scale up all the floating point 2^32 (not shown). This would scale up all the floating point
probabilities in the range [0,1] by 2^32. probabilities in the range [0,1] by 2^32.
skipping to change at page 55, line 7 skipping to change at page 56, line 14
At the time of writing, the range of approaches to RTT-dependence in At the time of writing, the range of approaches to RTT-dependence in
L4S congestion controls has not settled. Therefore, the guidance on L4S congestion controls has not settled. Therefore, the guidance on
the choice of the coupling factor in Appendix C.2 is given against the choice of the coupling factor in Appendix C.2 is given against
DCTCP [RFC8257], which has well-understood RTT-dependence. The DCTCP [RFC8257], which has well-understood RTT-dependence. The
guidance is given for various RTT ratios, so that it can be adapted guidance is given for various RTT ratios, so that it can be adapted
to future circumstances. to future circumstances.
C.2. Guidance on Controlling Throughput Equivalence C.2. Guidance on Controlling Throughput Equivalence
+---------------+------+-------+ +===============+======+=======+
| RTT_C / RTT_L | Reno | Cubic | | RTT_C / RTT_L | Reno | Cubic |
+---------------+------+-------+ +===============+======+=======+
| 1 | k'=1 | k'=0 | | 1 | k'=1 | k'=0 |
+---------------+------+-------+
| 2 | k'=2 | k'=1 | | 2 | k'=2 | k'=1 |
+---------------+------+-------+
| 3 | k'=2 | k'=2 | | 3 | k'=2 | k'=2 |
+---------------+------+-------+
| 4 | k'=3 | k'=2 | | 4 | k'=3 | k'=2 |
+---------------+------+-------+
| 5 | k'=3 | k'=3 | | 5 | k'=3 | k'=3 |
+---------------+------+-------+ +---------------+------+-------+
Table 1: Value of k' for which DCTCP throughput is roughly the same Table 1: Value of k' for
as Reno or Cubic, for some example RTT ratios which DCTCP throughput is
roughly the same as Reno or
Cubic, for some example RTT
ratios
In the above appendices that give example DualQ Coupled algorithms, In the above appendices that give example DualQ Coupled algorithms,
to aid efficient implementation, a coupling factor that is an integer to aid efficient implementation, a coupling factor that is an integer
power of 2 is always used. k' is always used to denote the power. k' power of 2 is always used. k' is always used to denote the power. k'
is related to the coupling factor k in Equation (1) (Section 2.1) by is related to the coupling factor k in Equation (1) (Section 2.1) by
k=2^k'. k=2^k'.
To determine the appropriate coupling factor policy, the operator To determine the appropriate coupling factor policy, the operator
first has to judge whether it wants DCTCP flows to have roughly equal first has to judge whether it wants DCTCP flows to have roughly equal
throughput with Reno or with Cubic (because, even in its Reno- throughput with Reno or with Cubic (because, even in its Reno-
skipping to change at page 56, line 26 skipping to change at page 57, line 40
Koen De Schepper Koen De Schepper
Nokia Bell Labs Nokia Bell Labs
Antwerp Antwerp
Belgium Belgium
Email: koen.de_schepper@nokia.com Email: koen.de_schepper@nokia.com
URI: https://www.bell-labs.com/usr/koen.de_schepper URI: https://www.bell-labs.com/usr/koen.de_schepper
Bob Briscoe (editor) Bob Briscoe (editor)
Independent Independent
UK United Kingdom
Email: ietf@bobbriscoe.net Email: ietf@bobbriscoe.net
URI: http://bobbriscoe.net/ URI: http://bobbriscoe.net/
Greg White Greg White
CableLabs CableLabs
Louisville, CO Louisville, CO,
US United States of America
Email: G.White@CableLabs.com Email: G.White@CableLabs.com
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