DualQ Coupled AQM for Low Latency, Low Loss and Scalable Throughput
draft-briscoe-aqm-dualq-coupled-01

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---throughput starves. So, until now, DCTCP could only be deployed where a clean-slate environment could be arranged, such as in private data centres. This specification defines `DualQ Coupled Active Queue Management (AQM)' to allow scalable congestion controls like DCTCP to safely co-exist with classic Internet traffic. The Coupled AQM ensures that a flow runs at about the same rate whether it uses DCTCP or TCP Reno/Cubic, but without inspecting transport layer flow identifiers. When tested in a residential broadband setting, DCTCP achieved sub-millisecond average queuing delay and zero congestion loss under a wide range of mixes of DCTCP and `Classic' broadband Internet traffic, without compromising the performance of the Classic traffic. The solution also reduces network complexity and eliminates network configuration.

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Table of Contents

• 1. Introduction
• 1.1. Problem and Scope
• 1.2. Terminology
• 1.3. Features
• 2. DualQ Coupled AQM Algorithm
• 2.1. Coupled AQM
• 2.2. Dual Queue
• 2.3. Traffic Classification
• 2.4. Normative Requirements
• 3. IANA Considerations
• 4. Security Considerations
• 4.1. Overload Handling
• 5. Acknowledgements
• 6. References
• 6.1. Normative References
• 6.2. Informative References
• Appendix A. Example DualQ Coupled Algorithm
• Appendix B. Guidance on Controlling Throughput Equivalence
• Appendix C. DCTCP Safety Enhancements
• Authors' Addresses

1. Introduction

1.1. Problem and Scope

Latency is becoming the critical performance factor for many (most?) applications on the public Internet, e.g. Web, voice, conversational video, gaming, finance apps, remote desktop and cloud-based applications. In the developed world, further increases in access network bit-rate offer diminishing returns, whereas latency is still a multi-faceted problem. In the last decade or so, much has been done to reduce propagation time by placing caches or servers closer to users. However, queuing remains a major component of latency.

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. Then Diffserv is of little use. Instead, we need to remove the causes of any unnecessary delay.

The bufferbloat project has shown that excessively-large buffering (`bufferbloat') has been introducing significantly more delay than the underlying propagation time. These delays appear only intermittently—only when a capacity-seeking (e.g. TCP) flow is long enough for the queue to fill the buffer, making every packet in other flows sharing the buffer sit through the queue.

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.

More recent state-of-the-art AQMs, e.g. fq_CoDel [I-D.ietf-aqm-fq-codel], PIE [I-D.ietf-aqm-pie], 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 from the delay variations it inflicts on itself, and it has other problems - it overrides the flow rate decisions of variable rate video applications, it does not recognise the flows within IPSec VPN tunnels and it is relatively expensive to implement.

It seems that further changes to the network alone will now yield diminishing returns. Data Centre TCP (DCTCP [I-D.bensley-tcpm-dctcp]) teaches us that a small but radical change to TCP is needed to cut two major outstanding causes of queuing delay variability:

1.

the `sawtooth' varying rate of TCP itself;

2.

the smoothing delay deliberately introduced into AQMs to permit bursts without triggering losses.

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:[RFC3649] beyond the scaling range of `classic' TCP Reno, `less unscalable' Cubic [I-D.zimmermann-tcpm-cubic] 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).

3.

It was known when TCP was first developed that it would not scale to high bandwidth-delay products.

Given regular broadband bit-rates over WAN distances are already 

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 [I-D.ietf-aqm-fq-codel] that classify packets by flow identifier into numerous separate queues in order to isolate sparse flows from the higher latency in the queues assigned to heavier flow. In contrast, the AQM exploits the behaviour of scalable congestion controls like DCTCP so that every packet in every flow sharing the queue for DCTCP-like traffic can be served with very low latency.

This AQM extension can be combined with any single qeueu AQM that generates a statistical or deterministic mark/drop probability driven by the queue dynamics. In many cases it simplifies the basic control algorithm, and requires little extra processing. Therefore it is believed the Coupled AQM would be applicable and easy to deploy in all types of buffers; buffers in cost-reduced mass-market residential equipment; buffers in end-system stacks; buffers in carrier-scale equipment including remote access servers, routers, firewalls and Ethernet switches; buffers in network interface cards, buffers in virtualized network appliances, hypervisors, and so on.

The supporting paper [DCttH15] gives 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.

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]).

Either service can cope with a proportion of unresponsive or less-responsive traffic as well (e.g. DNS, VoIP, etc).

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 [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.

Unlike Diffserv Expedited Forwarding, the L4S queue does not have to be limited to a small proportion of the link capacity in order to achieve low delay. The L4S queue can be filled with a heavy load of capacity-seeking flows like DCTCP and still achieve low delay. The L4S queue does not rely on the presence of other traffic in the Classic queue that can be 'overtaken'. It gives low latency to L4S traffic whether or not there is Classic traffic, and the latency of Classic traffic does not suffer when a proportion of the traffic is L4S. The two queues are only necessary because DCTCP-like flows cannot keep latency predictably low and keep utilization high if they are mixed with legacy TCP flows,

The experiments used the Linux implementation of DCTCP that is deployed in private data centres, without any modification despite its known deficiencies. Nonetheless, certain modifications will be necessary before DCTCP is safe to use on the Internet, which are recorded for now in Appendix C. However, the focus of this specification is to get the network service in place. Then, without any management intervention, applications can exploit it by migrating to scalable controls like DCTCP, which can then evolve while their benefits are being enjoyed by everyone on the Internet.

2. DualQ Coupled AQM Algorithm

There are two main aspects to the algorithm:

• the Coupled AQM that addresses throughput equivalence between Classic (e.g. Reno, Cubic) flows and L4S (e.g. DCTCP) flows
• 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, while the throughput of a single flow is less than about 500Mb/s. Therefore we can assume that Cubic traffic behaves similar to Reno (but with a slightly different constant of proportionality), and we shall use the term 'Classic' for the collection of Reno and Cubic in Reno mode.

In our supporting paper [DCttH15], we derive the equivalent rate equation for DCTCP, for which cwnd is inversely proportional to p (not the square root), where in this case p is the ECN marking probability. DCTCP is not the only congestion control that behaves like this, so we use the term 'L4S' traffic for all similar behaviour.

In order to make a DCTCP flow run at roughly the same rate as a Reno TCP flow (all other factors being equal), we make the drop probability for Classic traffic, p_C distinct from the marking probability for L4S traffic, p_L (in contrast to RFC3168 which requires them to be the same). We make the Classic drop probability p_C proportional to the square of the L4S marking probability p_L. This is because we need to make the Reno flow rate equal the DCTCP flow rate, so we have to square the square root of p_C in the Reno rate equation to make it the same as the straight p_L in the DCTCP rate equation.

There is a really simple way to implement the square of a probability - by testing the queue against two random numbers not one. This is the approach adopted in Appendix A.

    p_C = ( p_L / k )^2                  (1)

Stating this as a formula, the relation between Classic drop probability, p_C, and L4S marking probability, p_L needs to take the form:

where k is the constant of proportionality. Optionally, k can also be expressed as a power of 2 so that implementations can avoid costly division by shifting p_L by log2(k)=k' bits to the right.

2.2. Dual Queue

Classic traffic builds a large queue, so a separate queue is provided for L4S traffic, and it is scheduled with strict priority. Nonetheless, coupled marking ensures that giving priority to L4S traffic still leaves the right amount of spare scheduling time for Classic flows to each get equivalent throughput to DCTCP flows (all other factors such as RTT being equal). The algorithm achieves this without having to inspect flow identifiers.

2.3. Traffic Classification

Both the Coupled AQM and DualQ mechanisms need an identifier to distinguish L4S and C packets, which will need to be standardized. This draft does not currently recommend an approach for identifying for the L4S service, which is initially left open for discussion within the IETF. Another draft [I-D.briscoe-tsvwg-ecn-l4s-id] is submitted for that purpose.

2.4. Normative Requirements

In the Dual Queue, L4S packets MUST be given priority over Classic, although strict priority MAY not be appropriate.

All L4S traffic MUST be ECN-capable, although some Classic traffic MAY also be ECN-capable.

Whatever identifier is used for L4S traffic, it will still be necessary to agree on the meaning of an ECN marking on L4S traffic, relative to a drop of Classic traffic. In order to prevent starvation of Classic traffic by scalable L4S traffic (e.g. DCTCP) the drop probability of Classic traffic MUST be proportional to the square of the marking probability of L4S traffic, In other words, the power to which p_L is raised in Eqn. (1) MUST be 2.

The constant of proportionality, k, in Eqn (1) determines the relative flow rates of Classic and L4S flows when the AQM concerned is the bottleneck (all other factors being equal). k does not have to be standardized because differences do not prevent interoperability. However, k has to take some value, and each operator can make that choice.

A value of k=1 is RECOMMENDED as the default for public Internet access networks, assuming the scalable TCP algorithm operates at an comparable rate to classic tcp. Nonetheless choice of k is a matter of operator policy, and operators MAY choose a different value using Table 1 and the guidelines in Appendix B.

Typically, access network operators isolate customers from each other with some form of layer-2 multiplexing (TDM in DOCSIS, CDMA in 3G) or L3 scheduling (WRR in broadband), rather than relying on TCP to share capacity between customers [RFC0970]. In such cases, the choice of k will solely affect relative flow rates within the customer's access capacity, not between customers. Also, k would not affect rates of small flows, nor long flows at any times when they are all Classic or all L4S.

An example DualQ Coupled AQM algorithm is given in Appendix A. Marking and dropping in each queue is based on an AQM called Curvy RED. Curvy RED requires less operations per packet than RED and can be used if the range of RTTs is limited. Nonetheless, it would be possible to control each queue with an alternative AQM, as long as the above normative requirements (those expressed in capitals) are observed, which are intended to be independent of the specific AQM. Other experiments show that also PIE can be used and is simplified by applying a squared drop probability for classic TCP.

{ToDo: Add management and monitoring requirements}

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 necessary to police traffic to isolate any harm to performance. This is a policy issue that needs to be separable from a basic AQM, but the scheme does need to handle overload. A trade-off needs to be made between complexity and the risk of either class harming the other. It is an operator policy to define what must happen if the service time of the classic queue becomes too great. In the following subsections three optional non-exclusive overload protections are defined. Their objective is for the overload behaviour of the DualQ AQM to be similar to a single queue AQM. Other overload protections can be envisaged:

Minimum throughput service:

By replacing the priority scheduler with a weighted round robin scheduler, a minimum throughput service can be guaranteed for Classic traffic. Typically the scheduling weight of the Classic queue will be small (e.g. 5%) to avoid interference with the coupling but big enough to avoid complete starvation of Classic traffic.

Drop on overload:

On severe overload, e.g. due to non responsive traffic, queues will typically overflow and packet drop will be unavoidable when the queues reach their limits. The drop-limit of each queue should be configured by specifying the maximum supported load and determining the expected maximum size of each queue when that load is separately applied to each queue. The Classic queue limit will typically be larger than the L4S queue limit. Overflow of one traffic type will automatically result in drop in its respective queue. Both traffic types will get a high congestion signal, due to the coupled marking, which will result in similar starvation of responsive traffic in both queues. Thus, the behaviour will be like a single queue AQM. To further improve the arrival fairness of a single queue an extra overall AQM limit can be applied, which is a limit to the sum of both queues. To be effective, it should be configured to be less than the sum of the limits of both queues, but greater than the maximum individual queue limit. It ensures that the drop probability of unresponsive traffic will be independent of its traffic type.

Delay on overload:

To control milder overload of responsive traffic, particularly when close to the maximum congestion signal, delay can be used as an alternative congestion control mechanism. The Dual Queue Coupled AQM can be made to behave like a single FIFO queue with differentiated service times by replacing the priority scheduler with a very simple "biased longest sojourn time first scheduler". The bias is defined as a maximum sojourn time difference (T_m) between the Classic and L4S packets. The scheduler adds T_m to the sojourn time of the next L4S packet, before comparing it with the sojourn time of the next Classic packet, then it selects the packet with the greater adjusted sojourn time. This time shifted FIFO queue behaves just like a single FIFO queue under moderate and high overload.

5. Acknowledgements

Thanks to Anil Agarwal for detailed review comments and suggestions on how to make our explanation clearer.

The authors' contributions are part-funded by the European Community under its Seventh Framework Programme through the Reducing Internet Transport Latency (RITE) project (ICT-317700). The views expressed here are solely those of the authors.

6. References

6.1. Normative References

6.2. Informative References

Appendix A. Example DualQ Coupled Algorithm

As a concrete example, the pseudocode below gives the DualQ Coupled AQM algorithm we used in testing. Although we designed the AQM to be efficient in integer arithmetic, to aid understanding it is first given using real-number arithmetic. Then, one possible optimization for integer arithmetic is given, also in pseudocode. To aid comparison, the line numbers are kept in step between the two by using letter suffixes where the longer code needs extra lines.

1:  dualq_dequeue(lq, cq) {  % Couples L4S & Classic queues, lq & cq
2:     if ( lq.dequeue(pkt) ) {
3a:       p_L = cq.sec() / 2^S_L
3b:       if ( lq.byt() > T )
3c:           mark(pkt)
3d:        elif ( p_L > maxrand(U) )
4:           mark(pkt)
5:        return(pkt)              % return the packet and stop here
6:     }
7:     while ( cq.dequeue(pkt) ) {
8a:       alpha = 2^(-f_C)
8b:       Q_C = alpha * pkt.sec() + (1-alpha)* Q_C % Classic Q EWMA
9a:       sqrt_p_C = Q_C / 2^S_C
9b:       if ( sqrt_p_C > maxrand(2*U) )
10:          drop(pkt)                     % Squared drop, redo loop
11:       else
12:          return(pkt)           % return the packet and stop here
13:    }
14:    return(NULL)                           % no packet to dequeue
15: }

16: maxrand(u) {                % return the max of u random numbers
17:     maxr=0
18:     while (u-- > 0)
19:         maxr = max(maxr, rand())               % 0 <= rand() < 1
20:     return(maxr)
21: }

1:  dualq_dequeue(lq, cq) {  % Couples L4S & Classic queues, lq & cq
2:     if ( lq.dequeue(pkt) ) {
3:        if ((lq.byt() > T) || ((cq.ns() >> (S_L-2)) > maxrand(U)))
4:           mark(pkt)
5:        return(pkt)              % return the packet and stop here
6:     }
7:     while ( cq.dequeue(pkt) ) {
8:         Q_C += (pkt.ns() - Q_C) >> f_C           % Classic Q EWMA
9:        if ( (Q_C >> (S_C-2) ) > maxrand(2*U) )
10:          drop(pkt)                     % Squared drop, redo loop
11:       else
12:          return(pkt)           % return the packet and stop here
13:    }
14:    return(NULL)                           % no packet to dequeue
15: }

    2^k = 1.64 (RTT_reno / RTT_dc)                  (2)
    2^k = 1.19 (RTT_cubic / RTT_dc )                (3)