--- 1/draft-ietf-tsvwg-aqm-dualq-coupled-07.txt 2018-11-04 06:13:33.870265441 -0800 +++ 2/draft-ietf-tsvwg-aqm-dualq-coupled-08.txt 2018-11-04 06:13:33.958267547 -0800 @@ -1,62 +1,69 @@ Transport Area working group (tsvwg) K. De Schepper Internet-Draft Nokia Bell Labs Intended status: Experimental B. Briscoe, Ed. -Expires: April 25, 2019 CableLabs +Expires: May 8, 2019 CableLabs O. Bondarenko Simula Research Lab I. Tsang Nokia - October 22, 2018 + November 04, 2018 DualQ Coupled AQMs for Low Latency, Low Loss and Scalable Throughput (L4S) - draft-ietf-tsvwg-aqm-dualq-coupled-07 + draft-ietf-tsvwg-aqm-dualq-coupled-08 Abstract - 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---DCTCP is so aggressive that existing TCP - algorithms approach starvation. 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. + The Low Latency Low Loss Scalable Throughput (L4S) architecture + allows data flows over the public Internet to predictably achieve + ultra-low queuing latency, generally zero congestion loss and scaling + of per-flow throughput without the problems of traditional TCP. To + achieve this, L4S data flows use a 'scalable' congestion control + similar to Data Centre TCP (DCTCP) and a form of Explicit Congestion + Notification (ECN) with modified behaviour. However, until now, + scalable congestion controls did not co-exist with existing TCP Reno/ + Cubic traffic---scalable controls are so aggressive that 'Classic' + TCP algorithms drive themselves to starvation. Therefore, until now, + L4S controls could only be deployed where a clean-slate environment + could be arranged, such as in private data centres (hence the name + DCTCP). This specification defines `DualQ Coupled Active Queue + Management (AQM)', which enables these scalable congestion controls + 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. It achieves this + indirectly, without having to inspect transport layer flow + identifiers, When tested in a residential broadband setting, DCTCP + also achieves 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. Status of This Memo This Internet-Draft is submitted in full conformance with the provisions of BCP 78 and BCP 79. Internet-Drafts are working documents of the Internet Engineering Task Force (IETF). Note that other groups may also distribute working documents as Internet-Drafts. The list of current Internet- Drafts is at https://datatracker.ietf.org/drafts/current/. Internet-Drafts are draft documents valid for a maximum of six months and may be updated, replaced, or obsoleted by other documents at any time. It is inappropriate to use Internet-Drafts as reference material or to cite them other than as "work in progress." - This Internet-Draft will expire on April 25, 2019. + This Internet-Draft will expire on May 8, 2019. Copyright Notice Copyright (c) 2018 IETF Trust and the persons identified as the document authors. All rights reserved. This document is subject to BCP 78 and the IETF Trust's Legal Provisions Relating to IETF Documents (https://trustee.ietf.org/license-info) in effect on the date of publication of this document. Please review these documents @@ -66,63 +73,63 @@ the Trust Legal Provisions and are provided without warranty as described in the Simplified BSD License. Table of Contents 1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3 1.1. Problem and Scope . . . . . . . . . . . . . . . . . . . . 3 1.2. Terminology . . . . . . . . . . . . . . . . . . . . . . . 5 1.3. Features . . . . . . . . . . . . . . . . . . . . . . . . 6 2. DualQ Coupled AQM . . . . . . . . . . . . . . . . . . . . . . 7 - 2.1. Coupled AQM . . . . . . . . . . . . . . . . . . . . . . . 7 - 2.2. Dual Queue . . . . . . . . . . . . . . . . . . . . . . . 8 - 2.3. Traffic Classification . . . . . . . . . . . . . . . . . 8 - 2.4. Overall DualQ Coupled AQM Structure . . . . . . . . . . . 9 - 2.5. Normative Requirements for a DualQ Coupled AQM . . . . . 11 - 2.5.1. Functional Requirements . . . . . . . . . . . . . . . 11 + 2.1. Coupled AQM . . . . . . . . . . . . . . . . . . . . . . . 8 + 2.2. Dual Queue . . . . . . . . . . . . . . . . . . . . . . . 9 + 2.3. Traffic Classification . . . . . . . . . . . . . . . . . 9 + 2.4. Overall DualQ Coupled AQM Structure . . . . . . . . . . . 10 + 2.5. Normative Requirements for a DualQ Coupled AQM . . . . . 12 + 2.5.1. Functional Requirements . . . . . . . . . . . . . . . 12 2.5.1.1. Requirements in Unexpected Cases . . . . . . . . 13 - 2.5.2. Management Requirements . . . . . . . . . . . . . . . 14 - 3. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 15 - 4. Security Considerations . . . . . . . . . . . . . . . . . . . 15 - 4.1. Overload Handling . . . . . . . . . . . . . . . . . . . . 15 + 2.5.2. Management Requirements . . . . . . . . . . . . . . . 15 + 3. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 16 + 4. Security Considerations . . . . . . . . . . . . . . . . . . . 16 + 4.1. Overload Handling . . . . . . . . . . . . . . . . . . . . 16 4.1.1. Avoiding Classic Starvation: Sacrifice L4S Throughput - or Delay? . . . . . . . . . . . . . . . . . . . . . . 15 + or Delay? . . . . . . . . . . . . . . . . . . . . . . 17 4.1.2. Congestion Signal Saturation: Introduce L4S Drop or - Delay? . . . . . . . . . . . . . . . . . . . . . . . 16 - 4.1.3. Protecting against Unresponsive ECN-Capable Traffic . 17 - 5. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 18 - 6. References . . . . . . . . . . . . . . . . . . . . . . . . . 18 - 6.1. Normative References . . . . . . . . . . . . . . . . . . 18 - 6.2. Informative References . . . . . . . . . . . . . . . . . 18 - Appendix A. Example DualQ Coupled PI2 Algorithm . . . . . . . . 21 - A.1. Pass #1: Core Concepts . . . . . . . . . . . . . . . . . 21 - A.2. Pass #2: Overload Details . . . . . . . . . . . . . . . . 27 - Appendix B. Example DualQ Coupled Curvy RED Algorithm . . . . . 30 - Appendix C. Guidance on Controlling Throughput Equivalence . . . 36 - Appendix D. Open Issues . . . . . . . . . . . . . . . . . . . . 37 - Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 38 + Delay? . . . . . . . . . . . . . . . . . . . . . . . 18 + 4.1.3. Protecting against Unresponsive ECN-Capable Traffic . 19 + 5. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 19 + 6. References . . . . . . . . . . . . . . . . . . . . . . . . . 20 + 6.1. Normative References . . . . . . . . . . . . . . . . . . 20 + 6.2. Informative References . . . . . . . . . . . . . . . . . 20 + Appendix A. Example DualQ Coupled PI2 Algorithm . . . . . . . . 23 + A.1. Pass #1: Core Concepts . . . . . . . . . . . . . . . . . 23 + A.2. Pass #2: Overload Details . . . . . . . . . . . . . . . . 30 + Appendix B. Example DualQ Coupled Curvy RED Algorithm . . . . . 33 + Appendix C. Guidance on Controlling Throughput Equivalence . . . 39 + Appendix D. Open Issues . . . . . . . . . . . . . . . . . . . . 40 + Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 41 1. Introduction 1.1. Problem and Scope Latency is becoming the critical performance factor for many (most?) applications on the public Internet, e.g. interactive Web, Web services, voice, conversational video, interactive video, interactive remote presence, instant messaging, online gaming, remote desktop, cloud-based applications, and video-assisted remote control of machinery and industrial processes. In the 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. + intermittent component of latency. The Diffserv architecture provides Expedited Forwarding [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 and, if all the traffic on a link is marked as EF, Diffserv cannot reduce the delay of any of it. In contrast, the Low Latency Low Loss Scalable throughput (L4S) approach removes the causes of any unnecessary queuing delay. @@ -135,21 +142,21 @@ 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 _all_ 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 [RFC2309] and other algorithms from the 1990s were sensitive to their configuration and - hard to set correctly. So, AQM was not widely deployed. + hard to set correctly. So, AQM was not widely deployed in the 1990s. More recent state-of-the-art AQMs, e.g. fq_CoDel [RFC8290], PIE [RFC8033], Adaptive RED [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 @@ -170,111 +177,132 @@ 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. Latency is not our only concern: 3. It was known when TCP was first developed that it would not scale - to high bandwidth-delay products. + to high bandwidth-delay products [TCP-CA]. Given regular broadband bit-rates over WAN distances are already [RFC3649] beyond the scaling range of `classic' TCP Reno, `less unscalable' Cubic [RFC8312] and Compound [I-D.sridharan-tcpm-ctcp] variants of TCP have been successfully deployed. However, these are now approaching their scaling limits. 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). 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 [RFC8290] 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. + flows from the higher latency in the queues assigned to heavier + flows. 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. - This AQM extension can be combined with any single queue 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. + This AQM extension can be combined with any AQM designed for a single + queue 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. - The overall L4S architecture is described in - [I-D.ietf-tsvwg-l4s-arch]. The supporting papers [PI2] and [DCttH15] - give the full rationale for the AQM's design, both discursively and - in more precise mathematical form. + For the public Internet, nearly all the benefit will typically be + achieved by deploying the Coupled AQM into either end of the access + link between a 'site' and the Internet, which is invariably the + bottleneck. Here, the term 'site' is used loosely to mean a home, an + office, a campus or mobile user equipment. + + The overall L4S architecture [I-D.ietf-tsvwg-l4s-arch] gives more + detail, including on wider deployment aspects such as coexistence in + bottlenecks where a DualQ Coupled AQM has not been deployed. The + supporting papers [PI2] and [DCttH15] give the full rationale for the + AQM's design, both discursively and in more precise mathematical + form. 1.2. Terminology 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 [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. + document are to be interpreted as described in [RFC2119] when, and + only when, they appear in all capitals, as shown here. 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: 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). 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 [Mathis09]). + with scalable properties (e.g. DCTCP [RFC8257], Relentless + TCP [Mathis09], the L4S variant of SCREAM for real-time + media {ToDo: ref}). For the public Internet a scalable control + has to comply with the requirements in [I-D.ietf-tsvwg-ecn-l4s-id] + (aka. the 'TCP Prague requirements'). 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. + responsive traffic as well, as long (e.g. DNS, VoIP, game sync + datagrams, etc), just as a single queue AQM can if this traffic makes + minimal contribution to queuing. The DualQ Coupled AQM behaviour + below is defined to be similar to a single FIFO queue with respect to + unresponsive and overload traffic. 1.3. Features 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 [PI2] - [DCttH15]. + Details of the extensive experiments are available [PI2] [DCttH15]. - 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. + Subjective testing was also conducted by multiple people all + simultaneously using very demanding high bandwidth low latency + applications over a single shared access link [L4Sdemo16]. In one + application, each user could use finger gestures to pan or zoom their + own high definition (HD) sub-window of a larger video scene generated + on the fly in 'the cloud' from a football match. Another user + wearing VR goggles was remotely receiving a feed from a 360-degree + camera in a racing car, again with the sub-window in their field of + vision generated on the fly in 'the cloud' dependent on their head + movements. Even though other users were also downloading large + amounts of L4S and Classic data, playing a gaming benchmark and + watchings videos over the same 40Mb/s downstream broadband link, + latency was so low that the football picture appeared to stick to the + user's finger on the touchpad and the experience fed from the remote + camera did not noticeably lag head movements. All the L4S data (even + including the downloads) achieved the same ultra-low latency. With + an alternative AQM, the video noticeably lagged behind the finger + gestures and head movements. 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 @@ -290,184 +318,191 @@ Then, without any management intervention, applications can exploit it by migrating to scalable controls like DCTCP, which can then evolve _while_ their benefits are being enjoyed by everyone on the Internet. 2. DualQ Coupled AQM There are two main aspects to the approach: o the Coupled AQM that addresses throughput equivalence between - Classic (e.g. Reno, Cubic) flows and L4S (e.g. DCTCP) flows + Classic (e.g. Reno, Cubic) flows and L4S flows (that satisfy the + TCP Prague requirements). o the Dual Queue structure that provides latency separation for L4S flows to isolate them from the typically large Classic queue. 2.1. Coupled AQM 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 as long as the throughput - of a single flow is less than about 500Mb/s. Therefore it can be - assumed that Cubic traffic behaves similarly to Reno (but with a - slightly different constant of proportionality), and the term - 'Classic' will be used for the collection of Reno-friendly traffic - including Cubic in Reno mode. + We focus on Reno as the worst case, because if we do not harm Reno, + we will not harm Cubic. Nonetheless, TCP Cubic implements a Reno- + compatibility mode, which is the only relevant mode for typical RTTs + under 20ms as long as the throughput of a single flow is less than + about 500Mb/s. Therefore it can be assumed that Cubic traffic + behaves similarly to Reno (but with a slightly different constant of + proportionality). The term 'Classic' will be used for the collection + of Reno-friendly traffic including Cubic in Reno mode. The supporting paper [PI2] includes the derivation of 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 the term 'L4S' traffic will be used for all similar behaviour. - In order to make a DCTCP flow run at roughly the same rate as a Reno - TCP flow (all other factors being equal), the drop or marking - probability for Classic traffic, p_C has to be distinct from the - marking probability for L4S traffic, p_L (in contrast to RFC3168 - which requires them to be the same). To remain stable, Classic - traffic needs p_C to change relatively slowly, whereas L4S traffic - needs to be controlled rapidly by a probability p_L that track the - instantaneous queue. It is necessary to make the Classic drop - probability p_C proportional to the square of a variable we shall - call p_CL, which is an input to the instantaneous L4S marking - probability p_L but changes as slowly as p_C. This makes the Reno - flow rate roughly equal the DCTCP flow rate, because it squares the - square root of p_C in the Reno rate equation to make it proportional - to the smoothed value of p_L used in the DCTCP rate equation. + For safe co-existence, under stationary conditions, a DCTCP flow has + to run at roughly the same rate as a Reno TCP flow (all other factors + being equal). So the drop or marking probability for Classic + traffic, p_C has to be distinct from the marking probability for L4S + traffic, p_L. [RFC8311] updates the original ECN specification + [RFC3168] to allow these probabilities to be distinct, because RFC + 3168 required them to be the same. + + Also, to remain stable, Classic sources need the network to smooth + p_C so it changes relatively slowly. In contrast, L4S avoids + smoothing in the network, because it delays all signals for a worst- + case RTT. So instead, L4S sources smooth the ECN marking probability + themselves, so they expect the network to generate ECN marks with a + probability p_L that tracks the instantaneous unsmoothed queue. + + The Coupled AQM achieves safe coexistence by making the Classic drop + probability p_C proportional to the square of the coupled L4S + probability p_CL. p_CL is an input to the instantaneous L4S marking + probability p_L but it changes as slowly as p_C. This makes the Reno + flow rate roughly equal the DCTCP flow rate, because the squaring of + p_CL counterbalances the square root of p_C in the Classic 'TCP + formula'. Stating this as a formula, the relation between Classic drop - probability, p_C, and the input variable p_CL to the L4S marking - probability p_L needs to take the form: + probability, p_C, and the coupled L4S probability p_CL needs to take + the form: p_C = ( p_CL / k )^2 (1) - where k is the constant of proportionality. + where k is the constant of proportionality, which we shall call the + coupling factor. 2.2. Dual Queue Classic traffic typically builds a large queue to prevent under- utilization. Therefore a separate queue is provided for L4S traffic, and it is scheduled with priority over Classic. Priority is conditional to prevent starvation of Classic traffic. 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. + other factors such as RTT being equal). 2.3. Traffic Classification Both the Coupled AQM and DualQ mechanisms need an identifier to - distinguish L and C packets. A separate draft - [I-D.ietf-tsvwg-ecn-l4s-id] recommends using the ECT(1) codepoint of - the ECN field as this identifier, having assessed various - alternatives. An additional process document has proved necessary to - make the ECT(1) codepoint available for experimentation [RFC8311]. + distinguish L and C packets. Then the coupling algorithm can achieve + coexistence without having to inspect flow identifiers, because it + can apply the appropriate marking or dropping probability to all + flows of each type. A separate + specification [I-D.ietf-tsvwg-ecn-l4s-id] requires the sender to use + the ECT(1) codepoint of the ECN field as this identifier, having + assessed various alternatives. An additional process document has + proved necessary to make the ECT(1) codepoint available for + experimentation [RFC8311]. For policy reasons, an operator might choose to steer certain packets (e.g. from certain flows or with certain addresses) out of the L queue, even though they identify themselves as L4S by their ECN - codepoints. In such cases, the classifier MUST NOT alter the ECN - field, so that it is preserved end-to-end. The aim is that each - operator can choose how it treats L4S traffic locally, but an - individual operator does not alter the identification of L4S packets, - which would prevent other operators downstream from making their own + codepoints. In such cases, the device MUST NOT alter the ECN field, + so that it is preserved end-to-end. The aim is that each operator + can choose how it treats L4S traffic locally, but an individual + operator does not alter the identification of L4S packets, which + would prevent other operators downstream from making their own choices on how to treat L4S traffic. In addition, other identifiers could be used to classify certain additional packet types into the L queue, that are deemed not to risk harming the L4S service. For instance addresses of specific applications or hosts (see [I-D.ietf-tsvwg-ecn-l4s-id]), specific Diffserv codepoints such as EF (Expedited Forwarding) and Voice-Admit service classes (see [I-D.briscoe-tsvwg-l4s-diffserv]) or certain protocols (e.g. ARP, DNS). - Note that the DualQ Coupled AQM only reads these classifiers, it MUST - NOT re-mark or alter these identifiers (except for marking the ECN - field with the CE codepoint - with increasing frequency to indicate + Note that the mechanism only reads these classifiers, it MUST NOT re- + mark or alter these identifiers (except for marking the ECN field + with the CE codepoint - with increasing frequency to indicate increasing congestion). 2.4. Overall DualQ Coupled AQM Structure Figure 1 shows the overall structure that any DualQ Coupled AQM is likely to have. This schematic is intended to aid understanding of the current designs of DualQ Coupled AQMs. However, it is not intended to preclude other innovative ways of satisfying the normative requirements in Section 2.5 that minimally define a DualQ Coupled AQM. The classifier on the left separates incoming traffic between the two queues (L and C). Each queue has its own AQM that determines the - likelihood of marking or dropping (p_L and p_C). It has been proved - [PI2] that it is preferable to control TCP with a linear PI + likelihood of marking or dropping (p_L and p_C). It has been + proved [PI2] that it is preferable to control load with a linear controller, then square the output before applying it as a drop - probability to TCP. So, the AQM for Classic traffic needs to be - implemented in two stages: i) a base stage that outputs an internal - probability p' (pronounced p-prime); and ii) a squaring stage that - outputs p_C, where + probability to TCP (because TCP decreases its load proportional to + the square-root of the increase in drop). So, the AQM for Classic + traffic needs to be implemented in two stages: i) a base stage that + outputs an internal probability p' (pronounced p-prime); and ii) a + squaring stage that outputs p_C, where p_C = (p')^2. (2) Substituting for p_C in Eqn (1) gives: p' = p_CL / k - So we get our slow-moving input to ECN marking in the L queue as: + So the slow-moving input to ECN marking in the L queue (the coupled + L4S probability) is: p_CL = k*p', (3) where k is the constant coupling factor (see Appendix C). It can be seen that these two transformations of p' implement the - required coupling given in equation (1) earlier. Substituting for p' - from equation (3) into (2): - - p_C = ( p_CL / k )^2. + required coupling given in equation (1) earlier. The actual probability p_L that we apply to the L queue needs to track the immediate L queue delay, as well as track p_CL under stationary conditions. So we use a native AQM in the L queue that - calculates a marking probability p'L as a function of the - instantaneous L queue. And, given the L queue has conditional strict - priority over the C queue, whenever the L queue grows, we should - apply marking probability p'_L, but p_L should not fall below p_CL. - This suggests: + calculates a probability p'_L as a function of the instantaneous L + queue. And, given the L queue has conditional strict priority over + the C queue, whenever the L queue grows, we should apply marking + probability p'_L, but p_L should not fall below p_CL. This suggests: - p_L = max(p'L, p_CL), + p_L = max(p'_L, p_CL), (4) which has also been found to work very well in practice. - This allows p_L to be coupled to p_C by marking L4S traffic - proportionately to the intermediate output from the first stage. - Specifically, the output of the base AQM is coupled across to the L - queue in proportion to the output of the base AQM - _________ | | ,------. L4S queue | |===>| ECN | ,'| _______|_| |marker|\ <' | | `------'\\ //`' v ^ p_L \\ // ,-------. | \\ - // |Native |p'L | \\,. - // | L4S |-->(MAX) < | ___ + // |Native |p'_L | \\,. + // | L4S |--->(MAX) < | ___ ,----------.// | AQM | ^ p_CL `\|.'Cond-`. | IP-ECN |/ `-------' | / itional \ ==>|Classifier| ,-------. (k*p') [ priority]==> | |\ | Base | | \scheduler/ - `----------'\\ | AQM |--->: ,'|`-.___.-' + `----------'\\ | AQM |---->: ,'|`-.___.-' \\ | |p' | <' | \\ `-------' (p'^2) //`' \\ ^ | // \\,. | v p_C // < | _________ .------.// `\| | | | Drop |/ Classic |queue |===>|/mark | __|______| `------' Legend: ===> traffic flow; ---> control dependency. @@ -512,71 +547,74 @@ capitals) in Section 2.5 are observed. 2.5. Normative Requirements for a DualQ Coupled AQM The following requirements are intended to capture only the essential aspects of a DualQ Coupled AQM. They are intended to be independent of the particular AQMs used for each queue. 2.5.1. Functional Requirements - In the Dual Queue, L4S packets MUST be given priority over Classic, - although priority MUST be bounded in order not to starve Classic - traffic. + A Dual Queue Coupled AQM implementation MUST utilize two queues, each + with an AQM algorithm. The two queues can be part of a larger + queuing hierarchy [I-D.briscoe-tsvwg-l4s-diffserv]. + + The AQM algorithm for the low latency (L) queue MUST apply ECN + marking. + + The scheduler draining the two queues MUST give L4S packets priority + over Classic, although priority MUST be bounded in order not to + starve Classic traffic. - Whatever identifier is used for L4S experiments, [I-D.ietf-tsvwg-ecn-l4s-id] defines the meaning of an ECN marking on L4S traffic, relative to drop of Classic traffic. In order to prevent starvation of Classic traffic by scalable L4S traffic, it says, "The likelihood that an AQM drops a Not-ECT Classic packet (p_C) MUST be roughly proportional to the square of the likelihood - that it would have marked it if it had been an L4S packet (p_L)." In - other words, in any DualQ Coupled AQM, the power to which p_L is - raised in Eqn. (1) MUST be 2. The term 'likelihood' is used to allow - for marking and dropping to be either probabilistic or deterministic. + that it would have marked it if it had been an L4S packet (p_L)." + The term 'likelihood' is used to allow for marking and dropping to be + either probabilistic or deterministic. + + For the current specification, this translates into the following + requirement. A DualQ Coupled AQM MUST apply ECN marking to traffic + in the L queue that is no lower than that derived from the likelihood + of drop (or ECN marking) in the Classic queue using Eqn. (1). 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). [I-D.ietf-tsvwg-ecn-l4s-id] says, "The constant of proportionality (k) does not have to be standardised for interoperability, but a value of 2 is RECOMMENDED." 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) [RFC5681] and other so-called TCP-friendly controls, such as TCP Cubic in its TCP-friendly mode. - {ToDo: The requirements for scalable congestion controls on the - Internet (termed the TCP Prague requirements) - [I-D.ietf-tsvwg-ecn-l4s-id] are not necessarily final. 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.} - The choice of k is a matter of operator policy, and operators MAY choose a different value using Table 1 and the guidelines in Appendix C. If multiple users share capacity at a bottleneck (e.g. in the Internet access link of a campus network), the operator's choice of k will determine capacity sharing between the flows of different users. However, on the public Internet, access network operators typically isolate customers from each other with some form of layer-2 - multiplexing (TDM in DOCSIS, CDMA in 3G) or L3 scheduling (WRR in - DSL), rather than relying on TCP to share capacity between customers - [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. + multiplexing (OFDM(A) in DOCSIS3.1, CDMA in 3G, SC-FDMA in LTE) or L3 + scheduling (WRR in DSL), rather than relying on TCP to share capacity + between customers [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 the relative throughput of small flows. 2.5.1.1. Requirements in Unexpected Cases 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 with packets that do not carry the ECN field expected for that queue. It is recommended that the AQM in each queue inspects the ECN field to determine what sort of congestion notification to signal, then decides whether to apply congestion notification to this particular packet, as follows: @@ -626,55 +664,88 @@ By default, a DualQ Coupled AQM SHOULD NOT need any configuration for use at a bottleneck on the public Internet [RFC7567]. The following parameters MAY be operator-configurable, e.g. to tune for non- Internet settings: o Optional packet classifier(s) to use in addition to the ECN field (see Section 2.3); o Expected typical RTT (a parameter for typical or target queuing - delay in each queue might be configurable instead); + delay in each queue might be configurable instead; if so it MUST + be expressed in units of time); o Expected maximum RTT (a stability parameter that depends on maximum RTT might be configurable instead); o Coupling factor, k; o The limit to the conditional priority of L4S (scheduler-dependent, e.g. the scheduler weight for WRR, or the time-shift for time- shifted FIFO); o The maximum Classic ECN marking probability, p_Cmax, before switching over to drop. An experimental DualQ Coupled AQM SHOULD allow the operator to - monitor the following operational statistics: + monitor each of the following operational statistics on demand, per + queue and per configurable sample interval, for performance + monitoring and perhaps also for accounting in some cases: - o Bits forwarded (total and per queue per sample interval), from - which utilization can be calculated + o Bits forwarded, from which utilization can be calculated; - o Q delay (per queue over sample interval) {ToDo: max per interval, - histogram with configurable edges (from which percentile(s) can be - derived), not incl. medium access delay} + o Total packets arriving, enqueued and dequeued to distinguish tail + discard from proactive AQM discard; - o Total packets arriving, enqueued and dequeued (per queue per - sample interval) + o ECN packets marked, non-ECN packets dropped, ECN packets dropped, + from which marking and dropping probabilities can be calculated; - o ECN packets marked, non-ECN packets dropped, ECN packets dropped - (per queue per sample interval), from which marking and dropping - probabilities can be calculated + o Queue delay (not including serialization delay of the head packet + or medium acquisition delay) - see further notes below. - o Time and duration of each overload event. + Unlike the other statistics, queue delay cannot be captured in a + simple accumulating counter. Therefore the type of queue delay + statistics produced (mean, percentiles, etc.) will depend on + implementation constraints. To facilitate comparative evaluation + of different implementations and approaches, an implementation + SHOULD allow mean and 99th percentile queue delay to be derived + (per queue per sample interval). A relatively simple way to do + this would be to store a coarse-grained histogram of queue delay. + This could be done with a small number of bins with configurable + edges that represent contiguous ranges of queue delay. Then, over + a sample interval, each bin would accumulate a count of the number + of packets that had fallen within each range. The maximum queue + delay per queue per interval MAY also be recorded. - The type of statistics produced for variables like Q delay (mean, - percentiles, etc.) will depend on implementation constraints. + An experimental DualQ Coupled AQM SHOULD asynchronously report the + following data about anomalous conditions: + + o Start-time and duration of overload state. + + A hysteresis mechanism SHOULD be used to prevent flapping in and + out of overload causing an event storm. For instance, exit from + overload state could trigger one report, but also latch a timer. + Then, during that time, if the AQM enters and exits overload state + 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 + of overload once the timer has expired. + + [RFC5706] suggests that deployment, coexistence and scaling should + also be covered as management requirements. The raison d'etre of the + DualQ Couple AQM is to enable deployment and coexistence of scalable + congestion controls - as incremental replacements for today's TCP- + friendly controls that do not scale with bandwidth-delay product. + Therefore, these motivating issues are explained in the Introduction + and detailed in the L4S architecture [I-D.ietf-tsvwg-l4s-arch]. + Also, the descriptions of specific DualQ Coupled AQM algorithms in + the appendices cover scaling of their configuration parameters, e.g. + with respect to RTT and sampling frequency. 3. IANA Considerations This specification contains no IANA considerations. 4. Security Considerations 4.1. Overload Handling Where the interests of users or flows might conflict, it could be @@ -688,23 +759,22 @@ useful objective would be for the overload behaviour of the DualQ AQM to be at least no worse than a single queue AQM. However, a trade- off needs to be made between complexity and the risk of either traffic class harming the other. In each of the following three subsections, an overload issue specific to the DualQ is described, followed by proposed solution(s). Under overload the higher priority L4S service will have to sacrifice some aspect of its performance. Alternative solutions are provided below that each relax a different factor: e.g. throughput, delay, - drop. Some of these choices might need to be determined by operator - policy or by the developer, rather than by the IETF. {ToDo: Reach - consensus on which it is to be in each case.} + drop. These choices need to be made either by the developer or by + operator policy, rather than by the IETF. 4.1.1. Avoiding Classic Starvation: Sacrifice L4S Throughput or Delay? Priority of L4S is required to be conditional to avoid total throughput starvation of Classic by heavy L4S traffic. This raises the question of whether to sacrifice L4S throughput or L4S delay (or some other policy) to mitigate starvation of Classic: Sacrifice L4S throughput: By using weighted round robin as the conditional priority scheduler, the L4S service can sacrifice some @@ -748,55 +818,55 @@ packets relative to L4S. The example implementation in Appendix A can implement either policy. 4.1.2. Congestion Signal Saturation: Introduce L4S Drop or Delay? To keep the throughput of both L4S and Classic flows roughly equal over the full load range, a different control strategy needs to be defined above the point where one AQM first saturates to a probability of 100% leaving no room to push back the load any harder. - If k>1, L4S will saturate first, but saturation can be caused by - unresponsive traffic in either queue. + If k>1, L4S will saturate first, even though saturation could be + caused by unresponsive traffic in either queue. The term 'unresponsive' includes cases where a flow becomes temporarily unresponsive, for instance, a real-time flow that takes a while to adapt its rate in response to congestion, or a TCP-like flow that is normally responsive, but above a certain congestion level it will not be able to reduce its congestion window below the minimum of - 2 segments, effectively becoming unresponsive. (Note that L4S - traffic ought to remain responsive below a window of 2 segments (see - [I-D.ietf-tsvwg-ecn-l4s-id]). + 2 segments [RFC5681], effectively becoming unresponsive. (Note that + L4S traffic ought to remain responsive below a window of 2 segments + (see [I-D.ietf-tsvwg-ecn-l4s-id]). Saturation raises the question of whether to relieve congestion by introducing some drop into the L4S queue or by allowing delay to grow in both queues (which could eventually lead to tail drop too): Drop on Saturation: Saturation can be avoided by setting a maximum threshold for L4S ECN marking (assuming k>1) before saturation starts to make the flow rates of the different traffic types diverge. Above that the drop probability of Classic traffic is applied to all packets of all traffic types. Then experiments have shown that queueing delay can be kept at the target in any overload situation, including with unresponsive traffic, and no - further measures are required. + further measures are required [DualQ-Test]. Delay on Saturation: When L4S marking saturates, instead of switching to drop, the drop and marking probabilities could be capped. Beyond that, delay will grow either solely in the queue with unresponsive traffic (if WRR is used), or in both queues (if time-shifted FIFO is used). In either case, the higher delay ought to control temporary high congestion. If the overload is more persistent, eventually the combined DualQ will overflow and tail drop will control congestion. - The example implementation in Appendix A applies only the "drop on + The example implementation in Appendix A solely applies the "drop on saturation" policy. 4.1.3. Protecting against Unresponsive ECN-Capable Traffic Unresponsive traffic has a greater advantage if it is also ECN- capable. The advantage is undetectable at normal low levels of drop/ marking, but it becomes significant with the higher levels of drop/ marking typical during overload. This is an issue whether the ECN- capable traffic is L4S or Classic. @@ -809,22 +879,23 @@ problem with unresponsive ECN as well as addressing the saturation problem. It leaves only a small range of congestion levels where unresponsive traffic gains any advantage from using the ECN capability, and the advantage is hardly detectable [DualQ-Test]. 5. Acknowledgements Thanks to Anil Agarwal, Sowmini Varadhan's and Gabi Bracha for detailed review comments particularly of the appendices and suggestions on how to make our explanation clearer. Thanks also to - Greg White and Tom Henderson for insights on the choice of schedulers - and queue delay measurement techniques. + Greg White for improving the normative requirements and both Greg and + Tom Henderson for insights on the choice of schedulers, queue delay + measurement techniques. The authors' contributions were originally part-funded by the European Community under its Seventh Framework Programme through the Reducing Internet Transport Latency (RITE) project (ICT-317700). Bob Briscoe's contribution was also part-funded by the Research Council of Norway through the TimeIn project. The views expressed here are solely those of the authors. 6. References @@ -881,20 +952,28 @@ Low Loss, Scalable Throughput (L4S) Internet Service: Architecture", draft-ietf-tsvwg-l4s-arch-02 (work in progress), March 2018. [I-D.sridharan-tcpm-ctcp] Sridharan, M., Tan, K., Bansal, D., and D. Thaler, "Compound TCP: A New TCP Congestion Control for High-Speed and Long Distance Networks", draft-sridharan-tcpm-ctcp-02 (work in progress), November 2008. + [L4Sdemo16] + Bondarenko, O., De Schepper, K., Tsang, I., and B. + Briscoe, "Ultra-Low Delay for All: Live Experience, Live + Analysis", Proc. MMSYS'16 pp33:1--33:4, May 2016, + . + [Mathis09] Mathis, M., "Relentless Congestion Control", PFLDNeT'09 , May 2009, . [MEDF] Menth, M., Schmid, M., Heiss, H., and T. Reim, "MEDF - a simple scheduling algorithm for two real-time transport service classes with application in the UTRAN", Proc. IEEE Conference on Computer Communications (INFOCOM'03) Vol.2 pp.1116-1122, March 2003. @@ -931,20 +1010,25 @@ . [RFC3649] Floyd, S., "HighSpeed TCP for Large Congestion Windows", RFC 3649, DOI 10.17487/RFC3649, December 2003, . [RFC5681] Allman, M., Paxson, V., and E. Blanton, "TCP Congestion Control", RFC 5681, DOI 10.17487/RFC5681, September 2009, . + [RFC5706] Harrington, D., "Guidelines for Considering Operations and + Management of New Protocols and Protocol Extensions", + RFC 5706, DOI 10.17487/RFC5706, November 2009, + . + [RFC7567] Baker, F., Ed. and G. Fairhurst, Ed., "IETF Recommendations Regarding Active Queue Management", BCP 197, RFC 7567, DOI 10.17487/RFC7567, July 2015, . [RFC8033] Pan, R., Natarajan, P., Baker, F., and G. White, "Proportional Integral Controller Enhanced (PIE): A Lightweight Control Scheme to Address the Bufferbloat Problem", RFC 8033, DOI 10.17487/RFC8033, February 2017, . @@ -969,20 +1053,24 @@ [RFC8311] Black, D., "Relaxing Restrictions on Explicit Congestion Notification (ECN) Experimentation", RFC 8311, DOI 10.17487/RFC8311, January 2018, . [RFC8312] Rhee, I., Xu, L., Ha, S., Zimmermann, A., Eggert, L., and R. Scheffenegger, "CUBIC for Fast Long-Distance Networks", RFC 8312, DOI 10.17487/RFC8312, February 2018, . + [TCP-CA] Jacobson, V. and M. Karels, "Congestion Avoidance and + Control", Laurence Berkeley Labs Technical Report , + November 1988, . + Appendix A. Example DualQ Coupled PI2 Algorithm As a first concrete example, the pseudocode below gives the DualPI2 algorithm. DualPI2 follows the structure of the DualQ Coupled AQM framework in Figure 1. A simple step threshold (in units of queuing time) is used for the Native L4S AQM, but a ramp is also described as an alternative. And the PI2 algorithm [PI2] is used for the Classic AQM. PI2 is an improved variant of the PIE AQM [RFC8033]. We will introduce the pseudocode in two passes. The first pass @@ -991,31 +1079,34 @@ between the two passes by using letter suffixes where the longer code needs extra lines. A full open source implementation for Linux is available at: https://github.com/olgabo/dualpi2. A.1. Pass #1: Core Concepts The pseudocode manipulates three main structures of variables: the packet (pkt), the L4S queue (lq) and the Classic queue (cq). The - pseudocode consists of the following four functions: + pseudocode consists of the following five functions: o initialization code (Figure 2) that sets parameter defaults (the API for setting non-default values is omitted for brevity) o enqueue code (Figure 3) o dequeue code (Figure 4) + o a ramp function (Figure 5) used to calculate the ECN-marking + probability for the L4S queue + o code to regularly update the base probability (p) used in the - dequeue code (Figure 5). + dequeue code (Figure 6). It also uses the following functions that are not shown in full here: o scheduler(), which selects between the head packets of the two queues; the choice of scheduler technology is discussed later; o cq.len() or lq.len() returns the current length (aka. backlog) of the relevant queue in bytes; o cq.time() or lq.time() returns the current queuing delay (aka. @@ -1049,62 +1140,71 @@ 7: p_Cmax = 1/4 % Max Classic drop/mark prob 8: % Constants derived from PI2 AQM parameters 9: alpha_U = alpha *Tupdate % PI integral gain per update interval 10: beta_U = beta * Tupdate % PI prop'nal gain per update interval 11: 12: % DualQ Coupled framework parameters 13: k = 2 % Coupling factor 14: % scheduler weight or equival't parameter (scheduler-dependent) 15: limit = MAX_LINK_RATE * 250 ms % Dual buffer size 16: - 17: % L4S AQM parameters - 18: T_time = 1 ms % L4S marking threshold in time - 19: T_len = 2 * MTU % Min L4S marking threshold in bytes - 20: % Constants derived from L4S AQM parameters - 21: p_Lmax = min(k*sqrt(p_Cmax), 1) % Max L4S marking prob - 22: } + 17: % L4S ramp AQM parameters + 18: minTh = 475 us % L4S min marking threshold in time units + 19: range = 525 us % Range of L4S ramp in time units + 20: Th_len = 2 * MTU % Min L4S marking threshold in bytes + 21: % Constants derived from L4S AQM parameters + 22: p_Lmax = min(k*sqrt(p_Cmax), 1) % Max L4S marking prob + 23: floor = Th_len * 8 / MIN_LINK_RATE % MIN_LINK_RATE is in Mb/s + 24: if (minTh < floor) { + 25: % Adjust ramp to exceed serialization time of 2 MTU + 26: range = max(range - (floor-minTh), 1) % 1us avoids /0 error + 27: minTh = floor + 28: } + 29: maxTh = minTh+range % L4S min marking threshold in time units + 30: } Figure 2: Example Header Pseudocode for DualQ Coupled PI2 AQM + For brevity the pseudocode shows some parameters in units of + microseconds (us), but a real implementation would probably use + nanoseconds. + The overall goal of the code is to maintain the base probability (p), which is an internal variable from which the marking and dropping probabilities for L4S and Classic traffic (p_L and p_C) are derived. The variable named p in the pseudocode and in this walk-through is the same as p' (p-prime) in Section 2.4. The probabilities p_L and p_C are derived in lines 3, 4 and 5 of the dualpi2_update() function - (Figure 5) then used in the dualpi2_dequeue() function (Figure 4). + (Figure 6) then used in the dualpi2_dequeue() function (Figure 4). The code walk-through below builds up to explaining that part of the code eventually, but it starts from packet arrival. 1: dualpi2_enqueue(lq, cq, pkt) { % Test limit and classify lq or cq 2: if ( lq.len() + cq.len() > limit ) 3: drop(pkt) % drop packet if buffer is full 4: else { % Packet classifier 5: if ( ecn(pkt) modulo 2 == 1 ) % ECN bits = ECT(1) or CE 6: lq.enqueue(pkt) 7: else % ECN bits = not-ECT or ECT(0) 8: cq.enqueue(pkt) 9: } 10: } Figure 3: Example Enqueue Pseudocode for DualQ Coupled PI2 AQM 1: dualpi2_dequeue(lq, cq, pkt) { % Couples L4S & Classic queues 2: while ( lq.len() + cq.len() > 0 ) 3: if ( scheduler() == lq ) { 4: lq.dequeue(pkt) % Scheduler chooses lq - - {ToDo: Generalize 5-7 for any L AQM (see email to Tom 9-Aug-18)} - - 5: if ( ((lq.time() > T_time) % step marking ... - 6: AND (lq.len() > T_len)) - 7: OR (p_CL > rand()) ) % ...or linear marking + 5: p'_L = laqm(lq.time()) % Native L4S AQM + 6: p_L = max(p'_L, p_CL) % Combining function + 7: if ( p_L > rand() ) % Linear marking 8: mark(pkt) 9: } else { 10: cq.dequeue(pkt) % Scheduler chooses cq 11: if ( p_C > rand() ) { % probability p_C = p^2 12: if ( ecn(pkt) == 0 ) { % if ECN field = not-ECT 13: drop(pkt) % squared drop 14: continue % continue to the top of the while loop 15: } 16: mark(pkt) % squared mark 17: } @@ -1153,74 +1253,101 @@ add a whole queue of delay to the control signals, making the control loop very sloppy. 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 packet to schedule. Line 3 of the dequeue pseudocode is where the scheduler chooses between the L4S queue (lq) and the Classic queue (cq). Detailed implementation of the scheduler is not shown (see discussion later). - o If an L4S packet is scheduled, lines 5 to 8 mark the packet if - either the L4S threshold (T_time) is exceeded, or if a random - marking decision is drawn according to p_CL (maintained by the - dualpi2_update() function discussed below). This logical 'OR' on - a per-packet basis implements the max() function shown in Figure 1 - to couple the outputs of the two AQMs together. The L4S threshold - is usually in units of time (default T_time = 1 ms). However, on - slow links the packet serialization time can approach the - threshold T_time, so line 6 sets a floor of T_len (=2 MTU) to the - threshold, otherwise marking is always too frequent on slow links. + o If an L4S packet is scheduled, lines 7 and 8 ECN-mark the packet + if a random marking decision is drawn according to p_L. 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. This implements + the max() function shown in Figure 1 to couple the outputs of the + two AQMs together. Of the two probabilities input to p_L in line + 6: + + * p'_L is calculated per packet in line 5 by the laqm() function + (see Figure 5), + + * whereas p_CL is maintained by the dualpi2_update() function + which runs every Tupdate (default 16ms) (see Figure 2). o If a Classic packet is scheduled, lines 10 to 17 drop or mark the packet based on the squared probability p_C. - There is some concern that using a step function for the Native L4S - AQM requires end-systems to smooth the signal for a lot longer - - until its fidelity is sufficient. The latency benefits of a ramp are - being investigated as a simple alternative to the step. This ramp - would be similar to the RED algorithm, with the following - differences: + The Native L4S AQM algorithm (Figure 5) is a ramp function, similar + to the RED algorithm, but simpler due to the following differences: o The min and max of the ramp are defined in units of queuing delay, not bytes, so that configuration remains invariant as the queue departure rate varies. - o It uses instantaneous queueing delay without smoothing (smoothing - is done in the end-systems). - - o Determinism is being experimented with instead of randomness; to - reduce the delay necessary to smooth out the noise of randomness - from the signal. For each packet, the algorithm would accumulate - p'_L in a counter and mark the packet that took the counter over - 1, then subtract 1 from the counter and continue. + o It uses instantaneous queueing delay to remove smoothing delay + (L4S senders smooth incoming ECN feedback when necessary). o The ramp rises linearly directly from 0 to 1, not to a an intermediate value of p'_L as RED would, because there is no need to keep ECN marking probability low. - This ramp algorithm would require two configuration parameters (min - and max threshold in units of queuing time), in contrast to the - single parameter of a step. + o Marking does not have to be randomized. Determinism is being + experimented with instead of randomness; to reduce the delay + necessary to smooth out the noise of randomness from the signal. + In this case, for each packet, the algorithm would accumulate p_L + in a counter and mark the packet that took the counter over 1, + then subtract 1 from the counter and continue. + + This ramp function requires two configuration parameters, the minimum + threshold (minTh) and the width of the ramp (range), both in units of + queuing time), as shown in the parameter initialization code in + Figure 2. A minimum marking threshold parameter (Th_len) in + transmission units (default 2 MTU) is also necessary to ensure that + the ramp does not trigger excessive marking on slow links. The code + in lines 23-28 of Figure 2 converts 2 MTU into time units and adjusts + the ramp thresholds to be no shallower than this floor. + + An operator can effectively turn the ramp into a step function, as + used by DCTCP, by setting the range to its minimum value (e.g. 1 ns). + Then the condition for the ramp calculation will hardly ever arise. + There is some concern that using the step function of DCTCP for the + Native L4S AQM requires end-systems to smooth the signal for an + unnecessarily large number of round trips to ensure sufficient + fidelity. A ramp seems to be no worse than a step in initial + experiments with existing DCTCP. Therefore, it is recommended that a + ramp is configured in place of a step, which will allow congestion + control algorithms to investigate faster smoothing algorithms. + + 1: laqm(qdelay) { % Returns native L4S AQM probability + 2: if (qdelay >= maxTh) + 3: return 1 + 4: else if (qdelay > minTh) + 5: return (qdelay - minTh)/range % Divide would use a bit-shift + 6: else + 7: return 0 + 8: } + + Figure 5: Example Pseudocode for the Native L4S AQM 1: dualpi2_update(lq, cq, target) { % Update p every Tupdate 2: curq = cq.time() % use queuing time of first-in Classic packet 3: p = p + alpha_U * (curq - target) + beta_U * (curq - prevq) 4: p_CL = p * k % Coupled L4S prob = base prob * coupling factor 5: p_C = p^2 % Classic prob = (base prob)^2 6: prevq = curq 7: } - Figure 5: Example PI-Update Pseudocode for DualQ Coupled PI2 AQM + Figure 6: Example PI-Update Pseudocode for DualQ Coupled PI2 AQM - The base probability (p) is kept up to date by the core PI algorithm - in Figure 5, which is executed every Tupdate. + p_CL depends on the base probability (p), which is kept up to date by + the core PI algorithm in Figure 6 executed every Tupdate. 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 long the head packet was in the Classic queue (cq). The function cq.time() (not shown) subtracts the time stamped at enqueue from the current time and implicitly takes the current queuing delay as 0 if the queue is empty. The algorithm centres on line 3, which is a classical Proportional- Integral (PI) controller that alters p dependent on: a) the error @@ -1244,21 +1370,21 @@ without over-compensating and therefore causing oscillations in the queue. alpha and beta determine how much p ought to change if it was updated every second. It is best to update p as frequently as possible, but the update interval (Tupdate) will probably be constrained by hardware performance. For link rates from 4 - 200 Mb/s, we found Tupdate=16ms (as recommended in [RFC8033]) is sufficient. However small the chosen value of Tupdate, p should change by the same amount per second, but in finer more frequent steps. So the gain factors - used for updating p in Figure 5 need to be scaled by (Tupdate/1s), + used for updating p in Figure 6 need to be scaled by (Tupdate/1s), which is done in lines 9 and 10 of Figure 2). The suffix '_U' represents 'per update time' (Tupdate). In corner cases, p can overflow the range [0,1] so the resulting value of p has to be bounded (omitted from the pseudocode). Then, as already explained, the coupled and Classic probabilities are derived from the new p in lines 4 and 5 as p_CL = k*p and p_C = p^2. Because the coupled L4S marking probability (p_CL) is factored up by k, the dynamic gain parameters alpha and beta are also inherently @@ -1272,81 +1398,80 @@ are independent of p because the squaring applied to Classic traffic tunes them inherently. This is explained in [PI2], which also explains why this more principled approach removes the need for most of the heuristics that had to be added to PIE. {ToDo: Scaling beta with Tupdate and scaling both alpha & beta with RTT} A.2. Pass #2: Overload Details - Figure 6 repeats the dequeue function of Figure 4, but with overload - details added. Similarly Figure 7 repeats the core PI algorithm of - Figure 5 with overload details added. The initialization and enqueue - functions are unchanged. + Figure 7 repeats the dequeue function of Figure 4, but with overload + details added. Similarly Figure 8 repeats the core PI algorithm of + Figure 6 with overload details added. The initialization, enqueue + and L4S AQM functions are unchanged. In line 7 of the initialization function (Figure 2), the default maximum Classic drop probability p_Cmax = 1/4 or 25%. This is the point at which it is deemed that the Classic queue has become persistently overloaded, so it switches to using solely drop, even for ECN-capable packets. This protects the queue against any unresponsive traffic that falsely claims that it is responsive to ECN marking, as required by [RFC3168] and [RFC7567]. - Line 21 of the initialization function translates this into a maximum + Line 22 of the initialization function translates this into a maximum L4S marking probability (p_Lmax) by rearranging Equation (1). With a coupling factor of k=2 (the default) or greater, this translates to a maximum L4S marking probability of 1 (or 100%). This is intended to ensure that the L4S queue starts to introduce dropping once marking saturates and can rise no further. The 'TCP Prague' requirements [I-D.ietf-tsvwg-ecn-l4s-id] state that, when an L4S congestion control detects a drop, it falls back to a response that coexists with 'Classic' TCP. So it is correct that the L4S queue drops packets proportional to p^2, as if they are Classic packets. Both these switch-overs are triggered by the tests for overload - introduced in lines 4b and 12b of the dequeue function (Figure 6). + introduced in lines 4b and 12b of the dequeue function (Figure 7). Lines 8c to 8g drop L4S packets with probability p^2. Lines 8h to 8i mark the remaining packets with probability p_CL. If p_Lmax = 1, which is the suggested default configuration, all remaining packets will be marked because, to have reached the else block at line 8b, p_CL >= 1. - Lines 2c to 2d in the core PI algorithm (Figure 7) deal with overload + Lines 2c to 2d in the core PI algorithm (Figure 8) deal with overload of the L4S queue when there is no Classic traffic. This is necessary, because the core PI algorithm maintains the appropriate drop probability to regulate overload, but it depends on the length of the Classic queue. If there is no Classic queue the naive - algorithm in Figure 5 drops nothing, even if the L4S queue is + algorithm in Figure 6 drops nothing, even if the L4S queue is overloaded - so tail drop would have to take over (lines 3 and 4 of Figure 3). If the test at line 2a finds that the Classic queue is empty, line 2d measures the current queue delay using the L4S queue instead. While the L4S queue is not overloaded, its delay will always be tiny compared to the target Classic queue delay. So p_L will be driven to zero, and the L4S queue will naturally be governed solely by threshold marking (lines 5 and 6 of the dequeue algorithm in - Figure 6). But, if unresponsive L4S source(s) cause overload, the + Figure 7). But, if unresponsive L4S source(s) cause overload, the DualQ transitions smoothly to L4S marking based on the PI algorithm. - And as overload increases, it naturally transitions from marking to dropping by the switch-over mechanism already described. 1: dualpi2_dequeue(lq, cq) { % Couples L4S & Classic queues, lq & cq 2: while ( lq.len() + cq.len() > 0 ) 3: if ( scheduler() == lq ) { 4a: lq.dequeue(pkt) 4b: if ( p_CL < p_Lmax ) { % Check for overload saturation - 5: if ( ((lq.time() > T_time) % step marking ... - 6: AND (lq.len > T_len)) - 7: OR (p_CL > rand()) ) % ...or linear marking + 5: p'_L = laqm(lq.time()) % Native L4S AQM + 6: p_L = max(p'_L, p_CL) % Combining function + 7: if ( p_L > rand() ) % Linear marking 8a: mark(pkt) 8b: } else { % overload saturation 8c: if ( p_C > rand() ) { % probability p_C = p^2 8e: drop(pkt) % revert to Classic drop due to overload 8f: continue % continue to the top of the while loop 8g: } 8h: if ( p_CL > rand() ) % probability p_CL = k * p 8i: mark(pkt) % linear marking of remaining packets 8j: } 9: } else { @@ -1358,35 +1483,35 @@ 14: continue % continue to the top of the while loop 15: } 16: mark(pkt) % squared mark 17: } 18: } 19: return(pkt) % return the packet and stop 20: } 21: return(NULL) % no packet to dequeue 22: } - Figure 6: Example Dequeue Pseudocode for DualQ Coupled PI2 AQM + Figure 7: Example Dequeue Pseudocode for DualQ Coupled PI2 AQM (Including Integer Arithmetic and Overload Code) 1: dualpi2_update(lq, cq, target) { % Update p every Tupdate 2a: if ( cq.len() > 0 ) 2b: curq = cq.time() %use queuing time of first-in Classic packet 2c: else % Classic queue empty 2d: curq = lq.time() % use queuing time of first-in L4S packet 3: p = p + alpha_U * (curq - target) + beta_U * (curq - prevq) 4: p_CL = p * k % Coupled L4S prob = base prob * coupling factor 5: p_C = p^2 % Classic prob = (base prob)^2 6: prevq = curq 7: } - Figure 7: Example PI-Update Pseudocode for DualQ Coupled PI2 AQM + Figure 8: Example PI-Update Pseudocode for DualQ Coupled PI2 AQM (Including Overload Code) The choice of scheduler technology is critical to overload protection (see Section 4.1). o A well-understood weighted scheduler such as weighted round robin (WRR) is recommended. The scheduler weight for Classic should be low, e.g. 1/16. o Alternatively, a time-shifted FIFO could be used. This is a very @@ -1435,21 +1560,21 @@ 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: } - Figure 8: Example Dequeue Pseudocode for DualQ Coupled Curvy RED AQM + Figure 9: Example Dequeue Pseudocode for DualQ Coupled Curvy RED AQM Packet classification code is not shown, as it is no different from Figure 3. Potential classification schemes are discussed in Section 2.3. The Curvy RED algorithm has not been maintained to the same degree as the DualPI2 algorithm. Some ideas used in DualPI2 would need to be translated into Curvy RED, such as i) the conditional priority scheduler instead of strict priority ii) the time-based L4S threshold; iii) turning off ECN as overload protection; iv) Classic ECN support. These are not shown in the Curvy RED pseudocode, but would need to be implemented for @@ -1493,21 +1618,21 @@ 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 (Figure 9). + integer variant of the pseudocode (Figure 10). 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 5) 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 @@ -1626,21 +1751,21 @@ 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: } - Figure 9: Optimised Example Dequeue Pseudocode for Coupled DualQ AQM + Figure 10: Optimised Example Dequeue Pseudocode for Coupled DualQ AQM using Integer Arithmetic Notes: 1. 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 [CoDel]. In our Linux implementation, it was easiest to measure queuing time at dequeue. Queuing time can be estimated when a packet is enqueued @@ -1669,21 +1794,21 @@ adaptive smoothing methods could be valid and it might be appropriate to decrease the EWMA faster than it increases. 6. 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 Section 4.1). - 7. In the integer variant of the pseudocode (Figure 9) real numbers + 7. In the integer variant of the pseudocode (Figure 10) 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. @@ -1738,22 +1863,20 @@ For a typical mix of RTTs from local data centres and across the general Internet, a value of k'=1 (equivalent to k=2) is recommended as a good workable compromise. Appendix D. Open Issues Most of the following open issues are also tagged '{ToDo}' at the appropriate point in the document: - Operational guidance to monitor L4S experiment - PI2 appendix: scaling of alpha & beta, esp. dependence of beta_U on Tupdate Curvy RED appendix: complete the unfinished parts Authors' Addresses Koen De Schepper Nokia Bell Labs Antwerp