Internet Engineering Task Force (IETF)                     F. Baker, Ed.
Request for Comments: 7567                                 Cisco Systems
BCP: 197                                               G. Fairhurst, Ed.
Obsoletes: 2309                                   University of Aberdeen
Category: Best Current Practice                                July 2015
ISSN: 2070-1721
Internet Engineering Task Force (IETF)                     F. Baker, Ed.
Request for Comments: 7567                                 Cisco Systems
BCP: 197                                               G. Fairhurst, Ed.
Obsoletes: 2309                                   University of Aberdeen
Category: Best Current Practice                                July 2015
ISSN: 2070-1721

IETF Recommendations Regarding Active Queue Management




This memo presents recommendations to the Internet community concerning measures to improve and preserve Internet performance. It presents a strong recommendation for testing, standardization, and widespread deployment of active queue management (AQM) in network devices to improve the performance of today's Internet. It also urges a concerted effort of research, measurement, and ultimate deployment of AQM mechanisms to protect the Internet from flows that are not sufficiently responsive to congestion notification.


Based on 15 years of experience and new research, this document replaces the recommendations of RFC 2309.

基于15年的经验和新研究,本文件取代RFC 2309的建议。

Status of This Memo


This memo documents an Internet Best Current Practice.


This document is a product of the Internet Engineering Task Force (IETF). It represents the consensus of the IETF community. It has received public review and has been approved for publication by the Internet Engineering Steering Group (IESG). Further information on BCPs is available in Section 2 of RFC 5741.

本文件是互联网工程任务组(IETF)的产品。它代表了IETF社区的共识。它已经接受了公众审查,并已被互联网工程指导小组(IESG)批准出版。有关BCP的更多信息,请参见RFC 5741第2节。

Information about the current status of this document, any errata, and how to provide feedback on it may be obtained at


Copyright Notice


Copyright (c) 2015 IETF Trust and the persons identified as the document authors. All rights reserved.

版权所有(c)2015 IETF信托基金和确定为文件作者的人员。版权所有。

This document is subject to BCP 78 and the IETF Trust's Legal Provisions Relating to IETF Documents ( in effect on the date of publication of this document. Please review these documents carefully, as they describe your rights and restrictions with respect to this document. Code Components extracted from this document must include Simplified BSD License text as described in Section 4.e of the Trust Legal Provisions and are provided without warranty as described in the Simplified BSD License.

本文件受BCP 78和IETF信托有关IETF文件的法律规定的约束(自本文件出版之日起生效。请仔细阅读这些文件,因为它们描述了您对本文件的权利和限制。从本文件中提取的代码组件必须包括信托法律条款第4.e节中所述的简化BSD许可证文本,并提供简化BSD许可证中所述的无担保。

This document may contain material from IETF Documents or IETF Contributions published or made publicly available before November 10, 2008. The person(s) controlling the copyright in some of this material may not have granted the IETF Trust the right to allow modifications of such material outside the IETF Standards Process. Without obtaining an adequate license from the person(s) controlling the copyright in such materials, this document may not be modified outside the IETF Standards Process, and derivative works of it may not be created outside the IETF Standards Process, except to format it for publication as an RFC or to translate it into languages other than English.


Table of Contents


   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   4
     1.1.  Congestion Collapse . . . . . . . . . . . . . . . . . . .   4
     1.2.  Active Queue Management to Manage Latency . . . . . . . .   5
     1.3.  Document Overview . . . . . . . . . . . . . . . . . . . .   6
     1.4.  Changes to the Recommendations of RFC 2309  . . . . . . .   7
     1.5.  Requirements Language . . . . . . . . . . . . . . . . . .   7
   2.  The Need for Active Queue Management  . . . . . . . . . . . .   7
     2.1.  AQM and Multiple Queues . . . . . . . . . . . . . . . . .  11
     2.2.  AQM and Explicit Congestion Marking (ECN) . . . . . . . .  12
     2.3.  AQM and Buffer Size . . . . . . . . . . . . . . . . . . .  12
   3.  Managing Aggressive Flows . . . . . . . . . . . . . . . . . .  13
   4.  Conclusions and Recommendations . . . . . . . . . . . . . . .  16
     4.1.  Operational Deployments SHOULD Use AQM Procedures . . . .  17
     4.2.  Signaling to the Transport Endpoints  . . . . . . . . . .  17
       4.2.1.  AQM and ECN . . . . . . . . . . . . . . . . . . . . .  18
     4.3.  AQM Algorithm Deployment SHOULD NOT Require Operational
           Tuning  . . . . . . . . . . . . . . . . . . . . . . . . .  20
     4.4.  AQM Algorithms SHOULD Respond to Measured Congestion, Not
           Application Profiles  . . . . . . . . . . . . . . . . . .  21
     4.5.  AQM Algorithms SHOULD NOT Be Dependent on Specific
           Transport Protocol Behaviors  . . . . . . . . . . . . . .  22
     4.6.  Interactions with Congestion Control Algorithms . . . . .  22
     4.7.  The Need for Further Research . . . . . . . . . . . . . .  23
   5.  Security Considerations . . . . . . . . . . . . . . . . . . .  25
   6.  Privacy Considerations  . . . . . . . . . . . . . . . . . . .  25
   7.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  25
     7.1.  Normative References  . . . . . . . . . . . . . . . . . .  25
     7.2.  Informative References  . . . . . . . . . . . . . . . . .  26
   Acknowledgements  . . . . . . . . . . . . . . . . . . . . . . . .  31
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  31
   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   4
     1.1.  Congestion Collapse . . . . . . . . . . . . . . . . . . .   4
     1.2.  Active Queue Management to Manage Latency . . . . . . . .   5
     1.3.  Document Overview . . . . . . . . . . . . . . . . . . . .   6
     1.4.  Changes to the Recommendations of RFC 2309  . . . . . . .   7
     1.5.  Requirements Language . . . . . . . . . . . . . . . . . .   7
   2.  The Need for Active Queue Management  . . . . . . . . . . . .   7
     2.1.  AQM and Multiple Queues . . . . . . . . . . . . . . . . .  11
     2.2.  AQM and Explicit Congestion Marking (ECN) . . . . . . . .  12
     2.3.  AQM and Buffer Size . . . . . . . . . . . . . . . . . . .  12
   3.  Managing Aggressive Flows . . . . . . . . . . . . . . . . . .  13
   4.  Conclusions and Recommendations . . . . . . . . . . . . . . .  16
     4.1.  Operational Deployments SHOULD Use AQM Procedures . . . .  17
     4.2.  Signaling to the Transport Endpoints  . . . . . . . . . .  17
       4.2.1.  AQM and ECN . . . . . . . . . . . . . . . . . . . . .  18
     4.3.  AQM Algorithm Deployment SHOULD NOT Require Operational
           Tuning  . . . . . . . . . . . . . . . . . . . . . . . . .  20
     4.4.  AQM Algorithms SHOULD Respond to Measured Congestion, Not
           Application Profiles  . . . . . . . . . . . . . . . . . .  21
     4.5.  AQM Algorithms SHOULD NOT Be Dependent on Specific
           Transport Protocol Behaviors  . . . . . . . . . . . . . .  22
     4.6.  Interactions with Congestion Control Algorithms . . . . .  22
     4.7.  The Need for Further Research . . . . . . . . . . . . . .  23
   5.  Security Considerations . . . . . . . . . . . . . . . . . . .  25
   6.  Privacy Considerations  . . . . . . . . . . . . . . . . . . .  25
   7.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  25
     7.1.  Normative References  . . . . . . . . . . . . . . . . . .  25
     7.2.  Informative References  . . . . . . . . . . . . . . . . .  26
   Acknowledgements  . . . . . . . . . . . . . . . . . . . . . . . .  31
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  31
1. Introduction
1. 介绍

The Internet protocol architecture is based on a connectionless end-to-end packet service using the Internet Protocol, whether IPv4 [RFC791] or IPv6 [RFC2460]. The advantages of its connectionless design -- flexibility and robustness -- have been amply demonstrated. However, these advantages are not without cost: careful design is required to provide good service under heavy load. In fact, lack of attention to the dynamics of packet forwarding can result in severe service degradation or "Internet meltdown". This phenomenon was first observed during the early growth phase of the Internet in the mid 1980s [RFC896] [RFC970]; it is technically called "congestion collapse" and was a key focus of RFC 2309.


Although wide-scale congestion collapse is not common in the Internet, the presence of localized congestion collapse is by no means rare. It is therefore important to continue to avoid congestion collapse.


Since 1998, when RFC 2309 was written, the Internet has become used for a variety of traffic. In the current Internet, low latency is extremely important for many interactive and transaction-based applications. The same type of technology that RFC 2309 advocated for combating congestion collapse is also effective at limiting delays to reduce the interaction delay (latency) experienced by applications [Bri15]. High or unpredictable latency can impact the performance of the control loops used by end-to-end protocols (including congestion control algorithms using TCP). There is now also a focus on reducing network latency using the same technology.

自1998年RFC2309编写以来,互联网已被用于各种通信。在当前的互联网中,低延迟对于许多交互式和基于事务的应用程序来说非常重要。RFC 2309倡导的用于对抗拥塞崩溃的同一类型技术也能有效地限制延迟,以减少应用程序所经历的交互延迟(延迟)[15]。高或不可预测的延迟可能会影响端到端协议(包括使用TCP的拥塞控制算法)使用的控制环路的性能。现在,人们还关注使用相同的技术减少网络延迟。

The mechanisms described in this document may be implemented in network devices on the path between endpoints that include routers, switches, and other network middleboxes. The methods may also be implemented in the networking stacks within endpoint devices that connect to the network.


1.1. Congestion Collapse
1.1. 拥挤崩溃

The original fix for Internet meltdown was provided by Van Jacobsen. Beginning in 1986, Jacobsen developed the congestion avoidance mechanisms [Jacobson88] that are now required for implementations of the Transport Control Protocol (TCP) [RFC793] [RFC1122]. ([RFC7414] provides a roadmap to help identify TCP-related documents.) These mechanisms operate in Internet hosts to cause TCP connections to "back off" during congestion. We say that TCP flows are "responsive" to congestion signals (i.e., packets that are dropped or marked with explicit congestion notification [RFC3168]). It is primarily these

互联网崩溃的最初修复方案是由Van Jacobsen提供的。从1986年开始,Jacobsen开发了拥塞避免机制[Jacobson88],现在实现传输控制协议(TCP)[RFC793][RFC1122]需要这些机制。([RFC7414]提供了帮助识别TCP相关文档的路线图。)这些机制在Internet主机中运行,导致TCP连接在拥塞期间“后退”。我们说TCP流“响应”拥塞信号(即丢弃或标记为显式拥塞通知[RFC3168])。主要是这些

TCP congestion avoidance algorithms that prevent the congestion collapse of today's Internet. Similar algorithms are specified for other non-TCP transports.


However, that is not the end of the story. Considerable research has been done on Internet dynamics since 1988, and the Internet has grown. It has become clear that the congestion avoidance mechanisms [RFC5681], while necessary and powerful, are not sufficient to provide good service in all circumstances. Basically, there is a limit to how much control can be accomplished from the edges of the network. Some mechanisms are needed in network devices to complement the endpoint congestion avoidance mechanisms. These mechanisms may be implemented in network devices.


1.2. Active Queue Management to Manage Latency
1.2. 用于管理延迟的主动队列管理

Internet latency has become a focus of attention to increase the responsiveness of Internet applications and protocols. One major source of delay is the buildup of queues in network devices. Queueing occurs whenever the arrival rate of data at the ingress to a device exceeds the current egress rate. Such queueing is normal in a packet-switched network and is often necessary to absorb bursts in transmission and perform statistical multiplexing of traffic, but excessive queueing can lead to unwanted delay, reducing the performance of some Internet applications.


RFC 2309 introduced the concept of "Active Queue Management" (AQM), a class of technologies that, by signaling to common congestion-controlled transports such as TCP, manages the size of queues that build in network buffers. RFC 2309 also describes a specific AQM algorithm, Random Early Detection (RED), and recommends that this be widely implemented and used by default in routers.


With an appropriate set of parameters, RED is an effective algorithm. However, dynamically predicting this set of parameters was found to be difficult. As a result, RED has not been enabled by default, and its present use in the Internet is limited. Other AQM algorithms have been developed since RFC 2309 was published, some of which are self-tuning within a range of applicability. Hence, while this memo continues to recommend the deployment of AQM, it no longer recommends that RED or any other specific algorithm is used by default. It instead provides recommendations on IETF processes for the selection of appropriate algorithms, and especially that a recommended algorithm is able to automate any required tuning for common deployment scenarios.


Deploying AQM in the network can significantly reduce the latency across an Internet path, and, since the writing of RFC 2309, this has become a key motivation for using AQM in the Internet. In the context of AQM, it is useful to distinguish between two related classes of algorithms: "queue management" versus "scheduling" algorithms. To a rough approximation, queue management algorithms manage the length of packet queues by marking or dropping packets when necessary or appropriate, while scheduling algorithms determine which packet to send next and are used primarily to manage the allocation of bandwidth among flows. While these two mechanisms are closely related, they address different performance issues and operate on different timescales. Both may be used in combination.

在网络中部署AQM可以显著减少互联网路径上的延迟,并且自RFC 2309编写以来,这已成为在互联网中使用AQM的一个关键动机。在AQM的上下文中,区分两类相关的算法很有用:“队列管理”和“调度”算法。大致来说,队列管理算法通过在必要或适当时标记或丢弃数据包来管理数据包队列的长度,而调度算法则确定下一个要发送的数据包,主要用于管理流之间的带宽分配。虽然这两种机制密切相关,但它们解决不同的性能问题,并在不同的时间尺度上运行。两者都可以组合使用。

1.3. Document Overview
1.3. 文件概述

The discussion in this memo applies to "best-effort" traffic, which is to say, traffic generated by applications that accept the occasional loss, duplication, or reordering of traffic in flight. It also applies to other traffic, such as real-time traffic that can adapt its sending rate to reduce loss and/or delay. It is most effective when the adaption occurs on timescales of a single Round-Trip Time (RTT) or a small number of RTTs, for elastic traffic [RFC1633].


Two performance issues are highlighted:


The first issue is the need for an advanced form of queue management that we call "Active Queue Management", AQM. Section 2 summarizes the benefits that active queue management can bring. A number of AQM procedures are described in the literature, with different characteristics. This document does not recommend any of them in particular, but it does make recommendations that ideally would affect the choice of procedure used in a given implementation.


The second issue, discussed in Section 4 of this memo, is the potential for future congestion collapse of the Internet due to flows that are unresponsive, or not sufficiently responsive, to congestion indications. Unfortunately, while scheduling can mitigate some of the side effects of sharing a network queue with an unresponsive flow, there is currently no consensus solution to controlling the congestion caused by such aggressive flows. Methods such as congestion exposure (ConEx) [RFC6789] offer a framework [CONEX] that can update network devices to alleviate these effects. Significant research and engineering will be required before any solution will be available. It is imperative that work to mitigate the impact of unresponsive flows is energetically pursued to ensure acceptable performance and the future stability of the Internet.


Section 4 concludes the memo with a set of recommendations to the Internet community on the use of AQM and recommendations for defining AQM algorithms.


1.4. Changes to the Recommendations of RFC 2309
1.4. RFC 2309建议的变更

This memo replaces the recommendations in [RFC2309], which resulted from past discussions of end-to-end performance, Internet congestion, and RED in the End-to-End Research Group of the Internet Research Task Force (IRTF). It results from experience with RED and other algorithms, and the AQM discussion within the IETF [AQM-WG].


Whereas RFC 2309 described AQM in terms of the length of a queue, this memo uses AQM to refer to any method that allows network devices to control the queue length and/or the mean time that a packet spends in a queue.

鉴于RFC 2309根据队列长度描述了AQM,本备忘录使用AQM来指代允许网络设备控制队列长度和/或数据包在队列中花费的平均时间的任何方法。

This memo also explicitly obsoletes the recommendation that Random Early Detection (RED) be used as the default AQM mechanism for the Internet. This is replaced by a detailed set of recommendations for selecting an appropriate AQM algorithm. As in RFC 2309, this memo illustrates the need for continued research. It also clarifies the research needed with examples appropriate at the time that this memo is published.

该备忘录还明确废除了将随机早期检测(RED)用作互联网默认AQM机制的建议。取而代之的是一套详细的建议,用于选择适当的AQM算法。与RFC 2309一样,本备忘录说明了继续研究的必要性。本备忘录还阐明了本备忘录发布时所需的研究,并列举了适当的例子。

1.5. Requirements Language
1.5. 需求语言

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].


2. The Need for Active Queue Management
2. 主动队列管理的必要性

Active Queue Management (AQM) is a method that allows network devices to control the queue length or the mean time that a packet spends in a queue. Although AQM can be applied across a range of deployment environments, the recommendations in this document are for use in the general Internet. It is expected that the principles and guidance are also applicable to a wide range of environments, but they may require tuning for specific types of links or networks (e.g., to accommodate the traffic patterns found in data centers, the challenges of wireless infrastructure, or the higher delay encountered on satellite Internet links). The remainder of this section identifies the need for AQM and the advantages of deploying AQM methods.


The traditional technique for managing the queue length in a network device is to set a maximum length (in terms of packets) for each queue, accept packets for the queue until the maximum length is reached, then reject (drop) subsequent incoming packets until the queue decreases because a packet from the queue has been transmitted. This technique is known as "tail drop", since the packet that arrived most recently (i.e., the one on the tail of the queue) is dropped when the queue is full. This method has served the Internet well for years, but it has four important drawbacks:


1. Full Queues

1. 满队

The "tail drop" discipline allows queues to maintain a full (or, almost full) status for long periods of time, since tail drop signals congestion (via a packet drop) only when the queue has become full. It is important to reduce the steady-state queue size, and this is perhaps the most important goal for queue management.


The naive assumption might be that there is a simple trade-off between delay and throughput, and that the recommendation that queues be maintained in a "non-full" state essentially translates to a recommendation that low end-to-end delay is more important than high throughput. However, this does not take into account the critical role that packet bursts play in Internet performance. For example, even though TCP constrains the congestion window of a flow, packets often arrive at network devices in bursts [Leland94]. If the queue is full or almost full, an arriving burst will cause multiple packets to be dropped from the same flow. Bursts of loss can result in a global synchronization of flows throttling back, followed by a sustained period of lowered link utilization, reducing overall throughput [Flo94] [Zha90].


The goal of buffering in the network is to absorb data bursts and to transmit them during the (hopefully) ensuing bursts of silence. This is essential to permit transmission of bursts of data. Queues that are normally small are preferred in network devices, with sufficient queue capacity to absorb the bursts. The counterintuitive result is that maintaining queues that are normally small can result in higher throughput as well as lower end-to-end delay. In summary, queue limits should not reflect the steady-state queues we want to be maintained in the network; instead, they should reflect the size of bursts that a network device needs to absorb.


2. Lock-Out

2. 封锁

In some situations tail drop allows a single connection or a few flows to monopolize the queue space, thereby starving other connections, preventing them from getting room in the queue [Flo92].


3. Mitigating the Impact of Packet Bursts

3. 减轻数据包突发的影响

A large burst of packets can delay other packets, disrupting the control loop (e.g., the pacing of flows by the TCP ACK clock), and reducing the performance of flows that share a common bottleneck.

大数据包突发可能会延迟其他数据包,从而中断控制循环(例如,TCP ACK时钟对数据流的调整),并降低共享一个共同瓶颈的数据流的性能。

4. Control Loop Synchronization

4. 控制回路同步

Congestion control, like other end-to-end mechanisms, introduces a control loop between hosts. Sessions that share a common network bottleneck can therefore become synchronized, introducing periodic disruption (e.g., jitter/loss). "Lock-out" is often also the result of synchronization or other timing effects


Besides tail drop, two alternative queue management disciplines that can be applied when a queue becomes full are "random drop on full" or "head drop on full". When a new packet arrives at a full queue using the "random drop on full" discipline, the network device drops a randomly selected packet from the queue (this can be an expensive operation, since it naively requires an O(N) walk through the packet queue). When a new packet arrives at a full queue using the "head drop on full" discipline, the network device drops the packet at the front of the queue [Lakshman96]. Both of these solve the lock-out problem, but neither solves the full-queues problem described above.


In general, we know how to solve the full-queues problem for "responsive" flows, i.e., those flows that throttle back in response to congestion notification. In the current Internet, dropped packets provide a critical mechanism indicating congestion notification to hosts. The solution to the full-queues problem is for network devices to drop or ECN-mark packets before a queue becomes full, so that hosts can respond to congestion before buffers overflow. We call such a proactive approach AQM. By dropping or ECN-marking packets before buffers overflow, AQM allows network devices to control when and how many packets to drop.


In summary, an active queue management mechanism can provide the following advantages for responsive flows.


1. Reduce number of packets dropped in network devices

1. 减少网络设备中丢弃的数据包数量

Packet bursts are an unavoidable aspect of packet networks [Willinger95]. If all the queue space in a network device is already committed to "steady-state" traffic or if the buffer space is inadequate, then the network device will have no ability to buffer bursts. By keeping the average queue size small, AQM will provide greater capacity to absorb naturally occurring bursts without dropping packets.


Furthermore, without AQM, more packets will be dropped when a queue does overflow. This is undesirable for several reasons. First, with a shared queue and the "tail drop" discipline, this can result in unnecessary global synchronization of flows, resulting in lowered average link utilization and, hence, lowered network throughput. Second, unnecessary packet drops represent a waste of network capacity on the path before the drop point.


While AQM can manage queue lengths and reduce end-to-end latency even in the absence of end-to-end congestion control, it will be able to reduce packet drops only in an environment that continues to be dominated by end-to-end congestion control.


2. Provide a lower-delay interactive service

2. 提供较低延迟的交互式服务

By keeping a small average queue size, AQM will reduce the delays experienced by flows. This is particularly important for interactive applications such as short web transfers, POP/IMAP, DNS, terminal traffic (Telnet, SSH, Mosh, RDP, etc.), gaming or interactive audio-video sessions, whose subjective (and objective) performance is better when the end-to-end delay is low.


3. Avoid lock-out behavior

3. 避免锁定行为

AQM can prevent lock-out behavior by ensuring that there will almost always be a buffer available for an incoming packet. For the same reason, AQM can prevent a bias against low-capacity, but highly bursty, flows.


Lock-out is undesirable because it constitutes a gross unfairness among groups of flows. However, we stop short of calling this benefit "increased fairness", because general fairness among flows requires per-flow state, which is not provided by queue management. For example, in a network device using AQM with only


FIFO scheduling, two TCP flows may receive very different shares of the network capacity simply because they have different RTTs [Floyd91], and a flow that does not use congestion control may receive more capacity than a flow that does. AQM can therefore be combined with a scheduling mechanism that divides network traffic between multiple queues (Section 2.1).


4. Reduce the probability of control loop synchronization

4. 降低控制回路同步的概率

The probability of network control loop synchronization can be reduced if network devices introduce randomness in the AQM functions that trigger congestion avoidance at the sending host.


2.1. AQM and Multiple Queues
2.1. AQM与多队列

A network device may use per-flow or per-class queueing with a scheduling algorithm to either prioritize certain applications or classes of traffic, limit the rate of transmission, or provide isolation between different traffic flows within a common class. For example, a router may maintain per-flow state to achieve general fairness by a per-flow scheduling algorithm such as various forms of Fair Queueing (FQ) [Dem90] [Sut99], including Weighted Fair Queueing (WFQ), Stochastic Fairness Queueing (SFQ) [McK90], Deficit Round Robin (DRR) [Shr96] [Nic12], and/or a Class-Based Queue scheduling algorithm such as CBQ [Floyd95]. Hierarchical queues may also be used, e.g., as a part of a Hierarchical Token Bucket (HTB) or Hierarchical Fair Service Curve (HFSC) [Sto97]. These methods are also used to realize a range of Quality of Service (QoS) behaviors designed to meet the need of traffic classes (e.g., using the integrated or differentiated service models).


AQM is needed even for network devices that use per-flow or per-class queueing, because scheduling algorithms by themselves do not control the overall queue size or the sizes of individual queues. AQM mechanisms might need to control the overall queue sizes to ensure that arriving bursts can be accommodated without dropping packets. AQM should also be used to control the queue size for each individual flow or class, so that they do not experience unnecessarily high delay. Using a combination of AQM and scheduling between multiple queues has been shown to offer good results in experimental use and some types of operational use.


In short, scheduling algorithms and queue management should be seen as complementary, not as replacements for each other.


2.2. AQM and Explicit Congestion Marking (ECN)
2.2. AQM和显式拥塞标记(ECN)

An AQM method may use Explicit Congestion Notification (ECN) [RFC3168] instead of dropping to mark packets under mild or moderate congestion. ECN-marking can allow a network device to signal congestion at a point before a transport experiences congestion loss or additional queueing delay [ECN-Benefit]. Section 4.2.1 describes some of the benefits of using ECN with AQM.


2.3. AQM and Buffer Size
2.3. AQM和缓冲区大小

It is important to differentiate the choice of buffer size for a queue in a switch/router or other network device, and the threshold(s) and other parameters that determine how and when an AQM algorithm operates. The optimum buffer size is a function of operational requirements and should generally be sized to be sufficient to buffer the largest normal traffic burst that is expected. This size depends on the amount and burstiness of traffic arriving at the queue and the rate at which traffic leaves the queue.


One objective of AQM is to minimize the effect of lock-out, where one flow prevents other flows from effectively gaining capacity. This need can be illustrated by a simple example of drop-tail queueing when a new TCP flow injects packets into a queue that happens to be almost full. A TCP flow's congestion control algorithm [RFC5681] increases the flow rate to maximize its effective window. This builds a queue in the network, inducing latency in the flow and other flows that share this queue. Once a drop-tail queue fills, there will also be loss. A new flow, sending its initial burst, has an enhanced probability of filling the remaining queue and dropping packets. As a result, the new flow can be prevented from effectively sharing the queue for a period of many RTTs. In contrast, AQM can minimize the mean queue depth and therefore reduce the probability that competing sessions can materially prevent each other from performing well.


AQM frees a designer from having to limit the buffer space assigned to a queue to achieve acceptable performance, allowing allocation of sufficient buffering to satisfy the needs of the particular traffic pattern. Different types of traffic and deployment scenarios will lead to different requirements. The choice of AQM algorithm and associated parameters is therefore a function of the way in which congestion is experienced and the required reaction to achieve acceptable performance. The latter is the primary topic of the following sections.


3. Managing Aggressive Flows
3. 管理积极的流动

One of the keys to the success of the Internet has been the congestion avoidance mechanisms of TCP. Because TCP "backs off" during congestion, a large number of TCP connections can share a single, congested link in such a way that link bandwidth is shared reasonably equitably among similarly situated flows. The equitable sharing of bandwidth among flows depends on all flows running compatible congestion avoidance algorithms, i.e., methods conformant with the current TCP specification [RFC5681].


In this document, a flow is known as "TCP-friendly" when it has a congestion response that approximates the average response expected of a TCP flow. One example method of a TCP-friendly scheme is the TCP-Friendly Rate Control algorithm [RFC5348]. In this document, the term is used more generally to describe this and other algorithms that meet these goals.


There are a variety of types of network flow. Some convenient classes that describe flows are: (1) TCP-friendly flows, (2) unresponsive flows, i.e., flows that do not slow down when congestion occurs, and (3) flows that are responsive but are less responsive to congestion than TCP. The last two classes contain more aggressive flows that can pose significant threats to Internet performance.


1. TCP-friendly flows

1. TCP友好流

A TCP-friendly flow responds to congestion notification within a small number of path RTTs, and in steady-state it uses no more capacity than a conformant TCP running under comparable conditions (drop rate, RTT, packet size, etc.). This is described in the remainder of the document.


2. Non-responsive flows

2. 非响应流

A non-responsive flow does not adjust its rate in response to congestion notification within a small number of path RTTs; it can also use more capacity than a conformant TCP running under comparable conditions. There is a growing set of applications whose congestion avoidance algorithms are inadequate or nonexistent (i.e., a flow that does not throttle its sending rate when it experiences congestion).


The User Datagram Protocol (UDP) [RFC768] provides a minimal, best-effort transport to applications and upper-layer protocols (both simply called "applications" in the remainder of this document) and does not itself provide mechanisms to prevent congestion collapse or establish a degree of fairness [RFC5405].


Examples that use UDP include some streaming applications for packet voice and video, and some multicast bulk data transport. Other traffic, when aggregated, may also become unresponsive to congestion notification. If no action is taken, such unresponsive flows could lead to a new congestion collapse [RFC2914]. Some applications can even increase their traffic volume in response to congestion (e.g., by adding Forward Error Correction when loss is experienced), with the possibility that they contribute to congestion collapse.


In general, applications need to incorporate effective congestion avoidance mechanisms [RFC5405]. Research continues to be needed to identify and develop ways to accomplish congestion avoidance for presently unresponsive applications. Network devices need to be able to protect themselves against unresponsive flows, and mechanisms to accomplish this must be developed and deployed. Deployment of such mechanisms would provide an incentive for all applications to become responsive by either using a congestion-controlled transport (e.g., TCP, SCTP [RFC4960], and DCCP [RFC4340]) or incorporating their own congestion control in the application [RFC5405] [RFC6679].


3. Transport flows that are less responsive than TCP

3. 比TCP响应性差的传输流

A second threat is posed by transport protocol implementations that are responsive to congestion, but, either deliberately or through faulty implementation, reduce the effective window less than a TCP flow would have done in response to congestion. This covers a spectrum of behaviors between (1) and (2). If applications are not sufficiently responsive to congestion signals, they may gain an unfair share of the available network capacity.


For example, the popularity of the Internet has caused a proliferation in the number of TCP implementations. Some of these may fail to implement the TCP congestion avoidance mechanisms correctly because of poor implementation. Others may deliberately be implemented with congestion avoidance algorithms that are more aggressive in their use of capacity than other TCP implementations; this would allow a vendor to claim to have a "faster TCP". The logical consequence of such implementations would be a spiral of increasingly aggressive TCP implementations, leading back to the point where there is effectively no congestion avoidance and the Internet is chronically congested.


Another example could be an RTP/UDP video flow that uses an adaptive codec, but responds incompletely to indications of congestion or responds over an excessively long time period.


Such flows are unlikely to be responsive to congestion signals in a time frame comparable to a small number of end-to-end transmission delays. However, over a longer timescale, perhaps seconds in duration, they could moderate their speed, or increase their speed if they determine capacity to be available.


Tunneled traffic aggregates carrying multiple (short) TCP flows can be more aggressive than standard bulk TCP. Applications (e.g., web browsers primarily supporting HTTP 1.1 and peer-to-peer file-sharing) have exploited this by opening multiple connections to the same endpoint.

承载多个(短)TCP流的隧道式流量聚合可能比标准的批量TCP更具攻击性。应用程序(例如,主要支持HTTP 1.1和对等文件共享的web浏览器)通过打开到同一端点的多个连接来利用这一点。

Lastly, some applications (e.g., web browsers primarily supporting HTTP 1.1) open a large numbers of successive short TCP flows for a single session. This can lead to each individual flow spending the majority of time in the exponential TCP slow start phase, rather than in TCP congestion avoidance. The resulting traffic aggregate can therefore be much less responsive than a single standard TCP flow.

最后,一些应用程序(例如,主要支持HTTP 1.1的web浏览器)为单个会话打开大量连续的短TCP流。这可能导致每个流的大部分时间都花费在指数TCP慢启动阶段,而不是TCP拥塞避免阶段。因此,产生的流量聚合可能比单个标准TCP流的响应性差得多。

The projected increase in the fraction of total Internet traffic for more aggressive flows in classes 2 and 3 could pose a threat to the performance of the future Internet. There is therefore an urgent need for measurements of current conditions and for further research into the ways of managing such flows. This raises many difficult issues in finding methods with an acceptable overhead cost that can identify and isolate unresponsive flows or flows that are less responsive than TCP. Finally, there is as yet little measurement or simulation evidence available about the rate at which these threats are likely to be realized or about the expected benefit of algorithms for managing such flows.


Another topic requiring consideration is the appropriate granularity of a "flow" when considering a queue management method. There are a few "natural" answers: 1) a transport (e.g., TCP or UDP) flow (source address/port, destination address/port, protocol); 2) Differentiated Services Code Point, DSCP; 3) a source/destination host pair (IP address); 4) a given source host or a given destination host, or various combinations of the above; 5) a subscriber or site receiving the Internet service (enterprise or residential).

另一个需要考虑的主题是在考虑队列管理方法时“流”的适当粒度。有几个“自然”答案:1)传输(例如TCP或UDP)流(源地址/端口、目标地址/端口、协议);2) 区分服务码点;3) 源/目的主机对(IP地址);4) 给定源主机或给定目标主机,或上述主机的各种组合;5) 接收互联网服务的用户或站点(企业或住宅)。

The source/destination host pair gives an appropriate granularity in many circumstances. However, different vendors/providers use different granularities for defining a flow (as a way of "distinguishing" themselves from one another), and different granularities may be chosen for different places in the network. It may be the case that the granularity is less important than the fact that a network device needs to be able to deal with more unresponsive


flows at *some* granularity. The granularity of flows for congestion management is, at least in part, a question of policy that needs to be addressed in the wider IETF community.


4. Conclusions and Recommendations
4. 结论和建议

The IRTF, in producing [RFC2309], and the IETF in subsequent discussion, have developed a set of specific recommendations regarding the implementation and operational use of AQM procedures. The recommendations provided by this document are summarized as:


1. Network devices SHOULD implement some AQM mechanism to manage queue lengths, reduce end-to-end latency, and avoid lock-out phenomena within the Internet.

1. 网络设备应该实现一些AQM机制来管理队列长度,减少端到端延迟,并避免互联网中的锁定现象。

2. Deployed AQM algorithms SHOULD support Explicit Congestion Notification (ECN) as well as loss to signal congestion to endpoints.

2. 部署的AQM算法应支持显式拥塞通知(ECN)以及端点信号丢失拥塞。

3. AQM algorithms SHOULD NOT require tuning of initial or configuration parameters in common use cases.

3. AQM算法不应要求在常见用例中调整初始或配置参数。

4. AQM algorithms SHOULD respond to measured congestion, not application profiles.

4. AQM算法应该响应测量的拥塞,而不是应用程序配置文件。

5. AQM algorithms SHOULD NOT interpret specific transport protocol behaviors.

5. AQM算法不应解释特定的传输协议行为。

6. Congestion control algorithms for transport protocols SHOULD maximize their use of available capacity (when there is data to send) without incurring undue loss or undue round-trip delay.

6. 传输协议的拥塞控制算法应最大限度地利用可用容量(当有数据要发送时),而不会造成不适当的损失或不适当的往返延迟。

7. Research, engineering, and measurement efforts are needed regarding the design of mechanisms to deal with flows that are unresponsive to congestion notification or are responsive, but are more aggressive than present TCP.

7. 需要进行研究、工程和测量工作,以设计机制来处理对拥塞通知无响应或有响应但比现有TCP更具攻击性的流。

These recommendations are expressed using the word "SHOULD". This is in recognition that there may be use cases that have not been envisaged in this document in which the recommendation does not apply. Therefore, care should be taken in concluding that one's use case falls in that category; during the life of the Internet, such use cases have been rarely, if ever, observed and reported. To the contrary, available research [Choi04] says that even high-speed links in network cores that are normally very stable in depth and behavior experience occasional issues that need moderation. The recommendations are detailed in the following sections.


4.1. Operational Deployments SHOULD Use AQM Procedures
4.1. 运营部署应使用AQM程序

AQM procedures are designed to minimize the delay and buffer exhaustion induced in the network by queues that have filled as a result of host behavior. Marking and loss behaviors provide a signal that buffers within network devices are becoming unnecessarily full and that the sender would do well to moderate its behavior.


The use of scheduling mechanisms, such as priority queueing, classful queueing, and fair queueing, is often effective in networks to help a network serve the needs of a range of applications. Network operators can use these methods to manage traffic passing a choke point. This is discussed in [RFC2474] and [RFC2475]. When scheduling is used, AQM should be applied across the classes or flows as well as within each class or flow:


o AQM mechanisms need to control the overall queue sizes to ensure that arriving bursts can be accommodated without dropping packets.

o AQM机制需要控制总体队列大小,以确保能够在不丢弃数据包的情况下容纳到达的突发。

o AQM mechanisms need to allow combination with other mechanisms, such as scheduling, to allow implementation of policies for providing fairness between different flows.

o AQM机制需要允许与其他机制(如调度)相结合,以允许实现在不同流之间提供公平性的策略。

o AQM should be used to control the queue size for each individual flow or class, so that they do not experience unnecessarily high delay.

o AQM应用于控制每个流或类的队列大小,以便它们不会经历不必要的高延迟。

4.2. Signaling to the Transport Endpoints
4.2. 发送到传输端点的信令

There are a number of ways a network device may signal to the endpoint that the network is becoming congested and trigger a reduction in rate. The signaling methods include:


o Delaying transport segments (packets) in flight, such as in a queue.

o 在飞行中延迟传输段(数据包),如在队列中。

o Dropping transport segments (packets) in transit.

o 正在传输中丢弃传输段(数据包)。

o Marking transport segments (packets), such as using Explicit Congestion Control [RFC3168] [RFC4301] [RFC4774] [RFC6040] [RFC6679].

o 标记传输段(数据包),例如使用显式拥塞控制[RFC3168][RFC4301][RFC4774][RFC6040][RFC6679]。

Increased network latency is used as an implicit signal of congestion. For example, in TCP, additional delay can affect ACK clocking and has the result of reducing the rate of transmission of new data. In the Real-time Transport Protocol (RTP), network latency impacts the RTCP-reported RTT, and increased latency can trigger a sender to adjust its rate. Methods such as Low Extra Delay


Background Transport (LEDBAT) [RFC6817] assume increased latency as a primary signal of congestion. Appropriate use of delay-based methods and the implications of AQM presently remain an area for further research.


It is essential that all Internet hosts respond to loss [RFC5681] [RFC5405] [RFC4960] [RFC4340]. Packet dropping by network devices that are under load has two effects: It protects the network, which is the primary reason that network devices drop packets. The detection of loss also provides a signal to a reliable transport (e.g., TCP, SCTP) that there is incipient congestion, using a pragmatic but ambiguous heuristic. Whereas, when the network discards a message in flight, the loss may imply the presence of faulty equipment or media in a path, or it may imply the presence of congestion. To be conservative, a transport must assume it may be the latter. Applications using unreliable transports (e.g., using UDP) need to similarly react to loss [RFC5405].


Network devices SHOULD use an AQM algorithm to measure local congestion and to determine the packets to mark or drop so that the congestion is managed.


In general, dropping multiple packets from the same sessions in the same RTT is ineffective and can reduce throughput. Also, dropping or marking packets from multiple sessions simultaneously can have the effect of synchronizing them, resulting in increasing peaks and troughs in the subsequent traffic load. Hence, AQM algorithms SHOULD randomize dropping in time, to reduce the probability that congestion indications are only experienced by a small proportion of the active flows.


Loss due to dropping also has an effect on the efficiency of a flow and can significantly impact some classes of application. In reliable transports, the dropped data must be subsequently retransmitted. While other applications/transports may adapt to the absence of lost data, this still implies inefficient use of available capacity, and the dropped traffic can affect other flows. Hence, congestion signaling by loss is not entirely positive; it is a necessary evil.


4.2.1. AQM and ECN
4.2.1. AQM和ECN

Explicit Congestion Notification (ECN) [RFC4301] [RFC4774] [RFC6040] [RFC6679] is a network-layer function that allows a transport to receive network congestion information from a network device without incurring the unintended consequences of loss. ECN includes both


transport mechanisms and functions implemented in network devices; the latter rely upon using AQM to decide when and whether to ECN-mark.


Congestion for ECN-capable transports is signaled by a network device setting the "Congestion Experienced (CE)" codepoint in the IP header. This codepoint is noted by the remote receiving endpoint and signaled back to the sender using a transport protocol mechanism, allowing the sender to trigger timely congestion control. The decision to set the CE codepoint requires an AQM algorithm configured with a threshold. Non-ECN capable flows (the default) are dropped under congestion.


Network devices SHOULD use an AQM algorithm that marks ECN-capable traffic when making decisions about the response to congestion. Network devices need to implement this method by marking ECN-capable traffic or by dropping non-ECN-capable traffic.


Safe deployment of ECN requires that network devices drop excessive traffic, even when marked as originating from an ECN-capable transport. This is a necessary safety precaution because:


1. A non-conformant, broken, or malicious receiver could conceal an ECN mark and not report this to the sender;

1. 不符合、损坏或恶意的接收者可能会隐藏ECN标记,而不会向发送者报告;

2. A non-conformant, broken, or malicious sender could ignore a reported ECN mark, as it could ignore a loss without using ECN;

2. 不符合、损坏或恶意的发送者可以忽略报告的ECN标记,因为它可以忽略丢失而不使用ECN;

3. A malfunctioning or non-conforming network device may "hide" an ECN mark (or fail to correctly set the ECN codepoint at an egress of a network tunnel).

3. 出现故障或不符合要求的网络设备可能“隐藏”ECN标记(或无法正确设置网络隧道出口处的ECN代码点)。

In normal operation, such cases should be very uncommon; however, overload protection is desirable to protect traffic from misconfigured or malicious use of ECN (e.g., a denial-of-service attack that generates ECN-capable traffic that is unresponsive to CE-marking).


When ECN is added to a scheme, the ECN support MAY define a separate set of parameters from those used for controlling packet drop. The AQM algorithm SHOULD still auto-tune these ECN-specific parameters. These parameters SHOULD also be manually configurable.


Network devices SHOULD use an algorithm to drop excessive traffic (e.g., at some level above the threshold for CE-marking), even when the packets are marked as originating from an ECN-capable transport.


4.3. AQM Algorithm Deployment SHOULD NOT Require Operational Tuning
4.3. AQM算法部署不应要求操作调整

A number of AQM algorithms have been proposed. Many require some form of tuning or setting of parameters for initial network conditions. This can make these algorithms difficult to use in operational networks.


AQM algorithms need to consider both "initial conditions" and "operational conditions". The former includes values that exist before any experience is gathered about the use of the algorithm, such as the configured speed of interface, support for full-duplex communication, interface MTU, and other properties of the link. Other properties include information observed from monitoring the size of the queue, the queueing delay experienced, rate of packet discard, etc.


This document therefore specifies that AQM algorithms that are proposed for deployment in the Internet have the following properties:


o AQM algorithm deployment SHOULD NOT require tuning. An algorithm MUST provide a default behavior that auto-tunes to a reasonable performance for typical network operational conditions. This is expected to ease deployment and operation. Initial conditions, such as the interface rate and MTU size or other values derived from these, MAY be required by an AQM algorithm.

o AQM算法部署不需要调整。算法必须提供默认行为,以便在典型网络操作条件下自动调谐到合理的性能。预计这将简化部署和操作。AQM算法可能需要初始条件,例如接口速率和MTU大小或从中导出的其他值。

o AQM algorithm deployment MAY support further manual tuning that could improve performance in a specific deployed network. Algorithms that lack such variables are acceptable, but, if such variables exist, they SHOULD be externalized (made visible to the operator). The specification should identify any cases in which auto-tuning is unlikely to achieve acceptable performance and give guidance on the parametric adjustments necessary. For example, the expected response of an algorithm may need to be configured to accommodate the largest expected Path RTT, since this value cannot be known at initialization. This guidance is expected to enable the algorithm to be deployed in networks that have specific characteristics (paths with variable or larger delay, networks where capacity is impacted by interactions with lower-layer mechanisms, etc).

o AQM算法部署可支持进一步的手动调整,以提高特定部署网络中的性能。缺少此类变量的算法是可以接受的,但如果存在此类变量,则应将其外部化(使操作员可见)。规范应确定自动调谐不可能达到可接受性能的任何情况,并就必要的参数调整提供指导。例如,可能需要将算法的预期响应配置为适应最大的预期路径RTT,因为在初始化时无法知道该值。本指南预计将使算法能够部署在具有特定特征的网络中(具有可变或更大延迟的路径、容量受到与下层机制交互影响的网络等)。

o AQM algorithm deployment MAY provide logging and alarm signals to assist in identifying if an algorithm using manual or auto-tuning is functioning as expected. (For example, this could be based on an internal consistency check between input, output, and mark/drop rates over time.) This is expected to encourage deployment by default and allow operators to identify potential interactions with other network functions.

o AQM算法部署可提供日志记录和报警信号,以帮助识别使用手动或自动调整的算法是否按预期运行。(例如,这可以基于输入、输出和标记/删除率随时间变化的内部一致性检查。)这将鼓励默认部署,并允许运营商识别与其他网络功能的潜在交互。

Hence, self-tuning algorithms are to be preferred. Algorithms recommended for general Internet deployment by the IETF need to be designed so that they do not require operational (especially manual) configuration or tuning.


4.4. AQM Algorithms SHOULD Respond to Measured Congestion, Not Application Profiles

4.4. AQM算法应该响应测量的拥塞,而不是应用程序配置文件

Not all applications transmit packets of the same size. Although applications may be characterized by particular profiles of packet size, this should not be used as the basis for AQM (see Section 4.5). Other methods exist, e.g., Differentiated Services queueing, Pre-Congestion Notification (PCN) [RFC5559], that can be used to differentiate and police classes of application. Network devices may combine AQM with these traffic classification mechanisms and perform AQM only on specific queues within a network device.


An AQM algorithm should not deliberately try to prejudice the size of packet that performs best (i.e., preferentially drop/mark based only on packet size). Procedures for selecting packets to drop/mark SHOULD observe the actual or projected time that a packet is in a queue (bytes at a rate being an analog to time). When an AQM algorithm decides whether to drop (or mark) a packet, it is RECOMMENDED that the size of the particular packet not be taken into account [RFC7141].


Applications (or transports) generally know the packet size that they are using and can hence make their judgments about whether to use small or large packets based on the data they wish to send and the expected impact on the delay, throughput, or other performance parameter. When a transport or application responds to a dropped or marked packet, the size of the rate reduction should be proportionate to the size of the packet that was sent [RFC7141].


An AQM-enabled system MAY instantiate different instances of an AQM algorithm to be applied within the same traffic class. Traffic classes may be differentiated based on an Access Control List (ACL), the packet DSCP [RFC5559], enabling use of the ECN field (i.e., any of ECT(0), ECT(1) or CE) [RFC3168] [RFC4774], a multi-field (MF) classifier that combines the values of a set of protocol fields


(e.g., IP address, transport, ports), or an equivalent codepoint at a lower layer. This recommendation goes beyond what is defined in RFC 3168 by allowing that an implementation MAY use more than one instance of an AQM algorithm to handle both ECN-capable and non-ECN-capable packets.

(例如,IP地址、传输、端口)或较低层的等效代码点。该建议超出了RFC 3168中的定义,允许实现可以使用AQM算法的多个实例来处理支持ECN和不支持ECN的数据包。

4.5. AQM Algorithms SHOULD NOT Be Dependent on Specific Transport Protocol Behaviors

4.5. AQM算法不应依赖于特定的传输协议行为

In deploying AQM, network devices need to support a range of Internet traffic and SHOULD NOT make implicit assumptions about the characteristics desired by the set of transports/applications the network supports. That is, AQM methods should be opaque to the choice of transport and application.


AQM algorithms are often evaluated by considering TCP [RFC793] with a limited number of applications. Although TCP is the predominant transport in the Internet today, this no longer represents a sufficient selection of traffic for verification. There is significant use of UDP [RFC768] in voice and video services, and some applications find utility in SCTP [RFC4960] and DCCP [RFC4340]. Hence, AQM algorithms should demonstrate operation with transports other than TCP and need to consider a variety of applications. When selecting AQM algorithms, the use of tunnel encapsulations that may carry traffic aggregates needs to be considered.


AQM algorithms SHOULD NOT target or derive implicit assumptions about the characteristics desired by specific transports/applications. Transports and applications need to respond to the congestion signals provided by AQM (i.e., dropping or ECN-marking) in a timely manner (within a few RTTs at the latest).


4.6. Interactions with Congestion Control Algorithms
4.6. 与拥塞控制算法的交互作用

Applications and transports need to react to received implicit or explicit signals that indicate the presence of congestion. This section identifies issues that can impact the design of transport protocols when using paths that use AQM.


Transport protocols and applications need timely signals of congestion. The time taken to detect and respond to congestion is increased when network devices queue packets in buffers. It can be difficult to detect tail losses at a higher layer, and this may sometimes require transport timers or probe packets to detect and respond to such loss. Loss patterns may also impact timely detection, e.g., the time may be reduced when network devices do not drop long runs of packets from the same flow.


A common objective of an elastic transport congestion control protocol is to allow an application to deliver the maximum rate of data without inducing excessive delays when packets are queued in buffers within the network. To achieve this, a transport should try to operate at rate below the inflection point of the load/delay curve (the bend of what is sometimes called a "hockey stick" curve) [Jain94]. When the congestion window allows the load to approach this bend, the end-to-end delay starts to rise -- a result of congestion, as packets probabilistically arrive at non-overlapping times. On the one hand, a transport that operates above this point can experience congestion loss and could also trigger operator activities, such as those discussed in [RFC6057]. On the other hand, a flow may achieve both near-maximum throughput and low latency when it operates close to this knee point, with minimal contribution to router congestion. Choice of an appropriate rate/congestion window can therefore significantly impact the loss and delay experienced by a flow and will impact other flows that share a common network queue.


Some applications may send data at a lower rate or keep less segments outstanding at any given time. Examples include multimedia codecs that stream at some natural rate (or set of rates) or an application that is naturally interactive (e.g., some web applications, interactive server-based gaming, transaction-based protocols). Such applications may have different objectives. They may not wish to maximize throughput, but may desire a lower loss rate or bounded delay.


The correct operation of an AQM-enabled network device MUST NOT rely upon specific transport responses to congestion signals.


4.7. The Need for Further Research
4.7. 进一步研究的必要性

The second recommendation of [RFC2309] called for further research into the interaction between network queues and host applications, and the means of signaling between them. This research has occurred, and we as a community have learned a lot. However, we are not done.


We have learned that the problems of congestion, latency, and buffer-sizing have not gone away and are becoming more important to many users. A number of self-tuning AQM algorithms have been found that offer significant advantages for deployed networks. There is also renewed interest in deploying AQM and the potential of ECN.


Traffic patterns can depend on the network deployment scenario, and Internet research therefore needs to consider the implications of a diverse range of application interactions. This includes ensuring


that combinations of mechanisms, as well as combinations of traffic patterns, do not interact and result in either significantly reduced flow throughput or significantly increased latency.


At the time of writing (in 2015), an obvious example of further research is the need to consider the many-to-one communication patterns found in data centers, known as incast [Ren12], (e.g., produced by Map/Reduce applications). Such analysis needs to study not only each application traffic type but also combinations of types of traffic.


Research also needs to consider the need to extend our taxonomy of transport sessions to include not only "mice" and "elephants", but "lemmings". Here, "lemmings" are flash crowds of "mice" that the network inadvertently tries to signal to as if they were "elephant" flows, resulting in head-of-line blocking in a data center deployment scenario.


Examples of other required research include:


o new AQM and scheduling algorithms

o 新的AQM和调度算法

o appropriate use of delay-based methods and the implications of AQM

o 适当使用基于延迟的方法和AQM的含义

o suitable algorithms for marking ECN-capable packets that do not require operational configuration or tuning for common use

o 用于标记支持ECN的数据包的合适算法,这些数据包不需要操作配置或调优以供通用

o experience in the deployment of ECN alongside AQM

o 与AQM一起部署ECN的经验

o tools for enabling AQM (and ECN) deployment and measuring the performance

o 用于启用AQM(和ECN)部署和测量性能的工具

o methods for mitigating the impact of non-conformant and malicious flows

o 缓解不一致和恶意流影响的方法

o implications on applications of using new network and transport methods

o 使用新网络和传输方法对应用的影响

Hence, this document reiterates the call of RFC 2309: we need continuing research as applications develop.


5. Security Considerations
5. 安全考虑

While security is a very important issue, it is largely orthogonal to the performance issues discussed in this memo.


This recommendation requires algorithms to be independent of specific transport or application behaviors. Therefore, a network device does not require visibility or access to upper-layer protocol information to implement an AQM algorithm. This ability to operate in an application-agnostic fashion is an example of a privacy-enhancing feature.


Many deployed network devices use queueing methods that allow unresponsive traffic to capture network capacity, denying access to other traffic flows. This could potentially be used as a denial-of-service attack. This threat could be reduced in network devices that deploy AQM or some form of scheduling. We note, however, that a denial-of-service attack that results in unresponsive traffic flows may be indistinguishable from other traffic flows (e.g., tunnels carrying aggregates of short flows, high-rate isochronous applications). New methods therefore may remain vulnerable, and this document recommends that ongoing research consider ways to mitigate such attacks.


6. Privacy Considerations
6. 隐私考虑

This document, by itself, presents no new privacy issues.


7. References
7. 工具书类
7.1. Normative References
7.1. 规范性引用文件

[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", BCP 14, RFC 2119, DOI 10.17487/RFC2119, March 1997, <>.

[RFC2119]Bradner,S.,“RFC中用于表示需求水平的关键词”,BCP 14,RFC 2119,DOI 10.17487/RFC2119,1997年3月<>.

[RFC3168] Ramakrishnan, K., Floyd, S., and D. Black, "The Addition of Explicit Congestion Notification (ECN) to IP", RFC 3168, DOI 10.17487/RFC3168, September 2001, <>.

[RFC3168]Ramakrishnan,K.,Floyd,S.,和D.Black,“向IP添加显式拥塞通知(ECN)”,RFC 3168,DOI 10.17487/RFC3168,2001年9月<>.

[RFC4301] Kent, S. and K. Seo, "Security Architecture for the Internet Protocol", RFC 4301, DOI 10.17487/RFC4301, December 2005, <>.

[RFC4301]Kent,S.和K.Seo,“互联网协议的安全架构”,RFC 4301,DOI 10.17487/RFC4301,2005年12月<>.

[RFC4774] Floyd, S., "Specifying Alternate Semantics for the Explicit Congestion Notification (ECN) Field", BCP 124, RFC 4774, DOI 10.17487/RFC4774, November 2006, <>.

[RFC4774]Floyd,S.,“为显式拥塞通知(ECN)字段指定替代语义”,BCP 124,RFC 4774,DOI 10.17487/RFC4774,2006年11月<>.

[RFC5405] Eggert, L. and G. Fairhurst, "Unicast UDP Usage Guidelines for Application Designers", BCP 145, RFC 5405, DOI 10.17487/RFC5405, November 2008, <>.

[RFC5405]Eggert,L.和G.Fairhurst,“应用程序设计者的单播UDP使用指南”,BCP 145,RFC 5405,DOI 10.17487/RFC5405,2008年11月<>.

[RFC5681] Allman, M., Paxson, V., and E. Blanton, "TCP Congestion Control", RFC 5681, DOI 10.17487/RFC5681, September 2009, <>.

[RFC5681]Allman,M.,Paxson,V.和E.Blanton,“TCP拥塞控制”,RFC 5681,DOI 10.17487/RFC56812009年9月<>.

[RFC6040] Briscoe, B., "Tunnelling of Explicit Congestion Notification", RFC 6040, DOI 10.17487/RFC6040, November 2010, <>.

[RFC6040]Briscoe,B.,“明确拥塞通知的隧道挖掘”,RFC 6040,DOI 10.17487/RFC6040,2010年11月<>.

[RFC6679] Westerlund, M., Johansson, I., Perkins, C., O'Hanlon, P., and K. Carlberg, "Explicit Congestion Notification (ECN) for RTP over UDP", RFC 6679, DOI 10.17487/RFC6679, August 2012, <>.

[RFC6679]Westerlund,M.,Johansson,I.,Perkins,C.,O'Hanlon,P.,和K.Carlberg,“UDP上RTP的显式拥塞通知(ECN)”,RFC 6679,DOI 10.17487/RFC66792012年8月<>.

[RFC7141] Briscoe, B. and J. Manner, "Byte and Packet Congestion Notification", BCP 41, RFC 7141, DOI 10.17487/RFC7141, February 2014, <>.

[RFC7141]Briscoe,B.和J.Way,“字节和数据包拥塞通知”,BCP 41,RFC 7141,DOI 10.17487/RFC7141,2014年2月<>.

7.2. Informative References
7.2. 资料性引用

[AQM-WG] IETF, "Active Queue Management and Packet Scheduling (aqm) WG", <>.


[Bri15] Briscoe, B., Brunstrom, A., Petlund, A., Hayes, D., Ros, D., Tsang, I., Gjessing, S., Fairhurst, G., Griwodz, C., and M. Welzl, "Reducing Internet Latency: A Survey of Techniques and their Merit", IEEE Communications Surveys & Tutorials, 2015.


[Choi04] Choi, B., Moon, S., Zhang, Z., Papagiannaki, K., and C. Diot, "Analysis of Point-To-Point Packet Delay In an Operational Network", March 2004.


[CONEX] Mathis, M. and B. Briscoe, "Congestion Exposure (ConEx) Concepts, Abstract Mechanism and Requirements", Work in Progress, draft-ietf-conex-abstract-mech-13, October 2014.


[Dem90] Demers, A., Keshav, S., and S. Shenker, "Analysis and Simulation of a Fair Queueing Algorithm, Internetworking: Research and Experience", SIGCOMM Symposium proceedings on Communications architectures and protocols, 1990.


[ECN-Benefit] Fairhurst, G. and M. Welzl, "The Benefits of using Explicit Congestion Notification (ECN)", Work in Progress, draft-ietf-aqm-ecn-benefits-05, June 2015.


[Flo92] Floyd, S. and V. Jacobsen, "On Traffic Phase Effects in Packet-Switched Gateways", 1992, <>.


[Flo94] Floyd, S. and V. Jacobsen, "The Synchronization of Periodic Routing Messages", 1994, <>.


[Floyd91] Floyd, S., "Connections with Multiple Congested Gateways in Packet-Switched Networks Part 1: One-way Traffic.", Computer Communications Review , October 1991.


[Floyd95] Floyd, S. and V. Jacobson, "Link-sharing and Resource Management Models for Packet Networks", IEEE/ACM Transactions on Networking, August 1995.


[Jacobson88] Jacobson, V., "Congestion Avoidance and Control", SIGCOMM Symposium proceedings on Communications architectures and protocols, August 1988.


[Jain94] Jain, R., Ramakrishnan, KK., and C. Dah-Ming, "Congestion avoidance scheme for computer networks", US Patent Office 5377327, December 1994.

[Jain94]Jain,R.,Ramakrishnan,KK.,和C.Dah Ming,“计算机网络拥塞避免方案”,美国专利局5377327,1994年12月。

[Lakshman96] Lakshman, TV., Neidhardt, A., and T. Ott, "The Drop From Front Strategy in TCP Over ATM and Its Interworking with Other Control Features", IEEE Infocomm, 1996.

[Lakshman 96]Lakshman,TV.,Neidhardt,A.,和T.Ott,“ATM上TCP的前端下降策略及其与其他控制功能的互通”,IEEE Infocomm,1996年。

[Leland94] Leland, W., Taqqu, M., Willinger, W., and D. Wilson, "On the Self-Similar Nature of Ethernet Traffic (Extended Version)", IEEE/ACM Transactions on Networking, February 1994.

[Leland 94]Leland,W.,Taqqu,M.,Willinger,W.,和D.Wilson,“关于以太网流量的自相似性质(扩展版)”,IEEE/ACM网络事务,1994年2月。

[McK90] McKenney, PE. and G. Varghese, "Stochastic Fairness Queuing", 1990, < sfq.2002.06.04.pdf>.


[Nic12] Nichols, K. and V. Jacobson, "Controlling Queue Delay", Communications of the ACM, Vol. 55, Issue 7, pp. 42-50, July 2012.


[Ren12] Ren, Y., Zhao, Y., and P. Liu, "A survey on TCP Incast in data center networks", International Journal of Communication Systems, Volumes 27, Issue 8, pages 116-117, 1990.


[RFC768] Postel, J., "User Datagram Protocol", STD 6, RFC 768, DOI 10.17487/RFC0768, August 1980, <>.

[RFC768]Postel,J.,“用户数据报协议”,STD 6,RFC 768,DOI 10.17487/RFC0768,1980年8月<>.

[RFC791] Postel, J., "Internet Protocol", STD 5, RFC 791, DOI 10.17487/RFC0791, September 1981, <>.

[RFC791]Postel,J.,“互联网协议”,STD 5,RFC 791,DOI 10.17487/RFC07911981年9月<>.

[RFC793] Postel, J., "Transmission Control Protocol", STD 7, RFC 793, DOI 10.17487/RFC0793, September 1981, <>.

[RFC793]Postel,J.,“传输控制协议”,标准7,RFC 793,DOI 10.17487/RFC0793,1981年9月<>.

[RFC896] Nagle, J., "Congestion Control in IP/TCP Internetworks", RFC 896, DOI 10.17487/RFC0896, January 1984, <>.

[RFC896]Nagle,J.,“IP/TCP互联网中的拥塞控制”,RFC 896,DOI 10.17487/RFC0896,1984年1月<>.

[RFC970] Nagle, J., "On Packet Switches With Infinite Storage", RFC 970, DOI 10.17487/RFC0970, December 1985, <>.

[RFC970]Nagle,J.,“具有无限存储的分组交换机”,RFC 970,DOI 10.17487/RFC0970,1985年12月<>.

[RFC1122] Braden, R., Ed., "Requirements for Internet Hosts - Communication Layers", STD 3, RFC 1122, DOI 10.17487/RFC1122, October 1989, <>.

[RFC1122]Braden,R.,Ed.“互联网主机的要求-通信层”,STD 3,RFC 1122,DOI 10.17487/RFC1122,1989年10月<>.

[RFC1633] Braden, R., Clark, D., and S. Shenker, "Integrated Services in the Internet Architecture: an Overview", RFC 1633, DOI 10.17487/RFC1633, June 1994, <>.

[RFC1633]Braden,R.,Clark,D.,和S.Shenker,“互联网体系结构中的综合服务:概述”,RFC 1633,DOI 10.17487/RFC1633,1994年6月<>.

[RFC2309] Braden, B., Clark, D., Crowcroft, J., Davie, B., Deering, S., Estrin, D., Floyd, S., Jacobson, V., Minshall, G., Partridge, C., Peterson, L., Ramakrishnan, K., Shenker, S., Wroclawski, J., and L. Zhang, "Recommendations on Queue Management and Congestion Avoidance in the Internet", RFC 2309, DOI 10.17487/RFC2309, April 1998, <>.

[RFC2309]Braden,B.,Clark,D.,Crowcroft,J.,Davie,B.,Deering,S.,Estrin,D.,Floyd,S.,Jacobson,V.,Minshall,G.,Partridge,C.,Peterson,L.,Ramakrishnan,K.,Shenker,S.,Wroclawski,J.,and L.Zhang,“关于互联网中队列管理和拥塞避免的建议”,RFC 2309,DOI 10.17487/RFC2309,1998年4月, <>.

[RFC2460] Deering, S. and R. Hinden, "Internet Protocol, Version 6 (IPv6) Specification", RFC 2460, DOI 10.17487/RFC2460, December 1998, <>.

[RFC2460]Deering,S.和R.Hinden,“互联网协议,第6版(IPv6)规范”,RFC 2460,DOI 10.17487/RFC2460,1998年12月<>.

[RFC2474] Nichols, K., Blake, S., Baker, F., and D. Black, "Definition of the Differentiated Services Field (DS Field) in the IPv4 and IPv6 Headers", RFC 2474, DOI 10.17487/RFC2474, December 1998, <>.

[RFC2474]Nichols,K.,Blake,S.,Baker,F.,和D.Black,“IPv4和IPv6报头中区分服务字段(DS字段)的定义”,RFC 2474,DOI 10.17487/RFC2474,1998年12月<>.

[RFC2475] Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z., and W. Weiss, "An Architecture for Differentiated Services", RFC 2475, DOI 10.17487/RFC2475, December 1998, <>.

[RFC2475]Blake,S.,Black,D.,Carlson,M.,Davies,E.,Wang,Z.,和W.Weiss,“差异化服务架构”,RFC 2475,DOI 10.17487/RFC2475,1998年12月<>.

[RFC2914] Floyd, S., "Congestion Control Principles", BCP 41, RFC 2914, DOI 10.17487/RFC2914, September 2000, <>.

[RFC2914]Floyd,S.,“拥塞控制原则”,BCP 41,RFC 2914,DOI 10.17487/RFC2914,2000年9月<>.

[RFC4340] Kohler, E., Handley, M., and S. Floyd, "Datagram Congestion Control Protocol (DCCP)", RFC 4340, DOI 10.17487/RFC4340, March 2006, <>.

[RFC4340]Kohler,E.,Handley,M.和S.Floyd,“数据报拥塞控制协议(DCCP)”,RFC 4340,DOI 10.17487/RFC4340,2006年3月<>.

[RFC4960] Stewart, R., Ed., "Stream Control Transmission Protocol", RFC 4960, DOI 10.17487/RFC4960, September 2007, <>.

[RFC4960]Stewart,R.,Ed.“流控制传输协议”,RFC 4960,DOI 10.17487/RFC4960,2007年9月<>.

[RFC5348] Floyd, S., Handley, M., Padhye, J., and J. Widmer, "TCP Friendly Rate Control (TFRC): Protocol Specification", RFC 5348, DOI 10.17487/RFC5348, September 2008, <>.

[RFC5348]Floyd,S.,Handley,M.,Padhye,J.,和J.Widmer,“TCP友好速率控制(TFRC):协议规范”,RFC 5348,DOI 10.17487/RFC5348,2008年9月<>.

[RFC5559] Eardley, P., Ed., "Pre-Congestion Notification (PCN) Architecture", RFC 5559, DOI 10.17487/RFC5559, June 2009, <>.

[RFC5559]Eardley,P.,Ed.,“拥塞前通知(PCN)体系结构”,RFC 5559,DOI 10.17487/RFC5559,2009年6月<>.

[RFC6057] Bastian, C., Klieber, T., Livingood, J., Mills, J., and R. Woundy, "Comcast's Protocol-Agnostic Congestion Management System", RFC 6057, DOI 10.17487/RFC6057, December 2010, <>.

[RFC6057]Bastian,C.,Klieber,T.,Livingood,J.,Mills,J.,和R.Woundy,“康卡斯特的协议不可知拥塞管理系统”,RFC 6057,DOI 10.17487/RFC6057,2010年12月<>.

[RFC6789] Briscoe, B., Ed., Woundy, R., Ed., and A. Cooper, Ed., "Congestion Exposure (ConEx) Concepts and Use Cases", RFC 6789, DOI 10.17487/RFC6789, December 2012, <>.

[RFC6789]Briscoe,B.,Ed.,Woundy,R.,Ed.,和A.Cooper,Ed.,“拥塞暴露(ConEx)概念和用例”,RFC 6789,DOI 10.17487/RFC6789,2012年12月<>.

[RFC6817] Shalunov, S., Hazel, G., Iyengar, J., and M. Kuehlewind, "Low Extra Delay Background Transport (LEDBAT)", RFC 6817, DOI 10.17487/RFC6817, December 2012, <>.

[RFC6817]Shalunov,S.,Hazel,G.,Iyengar,J.,和M.Kuehlewind,“低额外延迟背景传输(LEDBAT)”,RFC 6817,DOI 10.17487/RFC6817,2012年12月<>.

[RFC7414] Duke, M., Braden, R., Eddy, W., Blanton, E., and A. Zimmermann, "A Roadmap for Transmission Control Protocol (TCP) Specification Documents", RFC 7414, DOI 10.17487/RFC7414, February 2015, <>.

[RFC7414]杜克,M.,布拉登,R.,艾迪,W.,布兰顿,E.,和A.齐默尔曼,“传输控制协议(TCP)规范文件路线图”,RFC 7414,DOI 10.17487/RFC7414,2015年2月<>.

[Shr96] Shreedhar, M. and G. Varghese, "Efficient Fair Queueing Using Deficit Round Robin", IEEE/ACM Transactions on Networking, Vol. 4, No. 3, July 1996.


[Sto97] Stoica, I. and H. Zhang, "A Hierarchical Fair Service Curve algorithm for Link sharing, real-time and priority services", ACM SIGCOMM, 1997.

[Sto97]Stoica,I.和H.Zhang,“链路共享、实时和优先级服务的分层公平服务曲线算法”,ACM SIGCOMM,1997。

[Sut99] Suter, B., "Buffer Management Schemes for Supporting TCP in Gigabit Routers with Per-flow Queueing", IEEE Journal on Selected Areas in Communications, Vol. 17, Issue 6, pp. 1159-1169, June 1999.


[Willinger95] Willinger, W., Taqqu, M., Sherman, R., Wilson, D., and V. Jacobson, "Self-Similarity Through High-Variability: Statistical Analysis of Ethernet LAN Traffic at the Source Level", SIGCOMM Symposium proceedings on Communications architectures and protocols, August 1995.


[Zha90] Zhang, L. and D. Clark, "Oscillating Behavior of Network Traffic: A Case Study Simulation", 1990, <>.




The original draft of this document describing best current practice was based on [RFC2309], an Informational RFC. It was written by the End-to-End Research Group, which is to say Bob Braden, Dave Clark, Jon Crowcroft, Bruce Davie, Steve Deering, Deborah Estrin, Sally Floyd, Van Jacobson, Greg Minshall, Craig Partridge, Larry Peterson, KK Ramakrishnan, Scott Shenker, John Wroclawski, and Lixia Zhang. Although there are important differences, many of the key arguments in the present document remain unchanged from those in RFC 2309.

本文件的原始草案描述了当前最佳实践,其依据是[RFC2309],一份信息性RFC。它是由端到端研究小组撰写的,即鲍勃·布拉登、戴夫·克拉克、乔恩·克罗克罗夫特、布鲁斯·戴维斯、史蒂夫·迪林、黛博拉·埃斯特林、莎莉·弗洛伊德、范·雅各布森、格雷格·明索尔、克雷格·帕特里奇、拉里·彼得森、KK·罗摩克里希南、斯科特·申克、约翰·沃克罗夫斯基和张丽霞。尽管存在重要差异,但本文件中的许多关键论点与RFC 2309中的论点保持不变。

The need for an updated document was agreed to in the TSV area meeting at IETF 86. This document was reviewed on the list. Comments were received from Colin Perkins, Richard Scheffenegger, Dave Taht, John Leslie, David Collier-Brown, and many others.

IETF 86的TSV区域会议同意需要更新文件。本文件已在现场审查aqm@ietf.org列表科林·珀金斯、理查德·谢弗内格、戴夫·塔特、约翰·莱斯利、大卫·科利尔·布朗和许多其他人发表了评论。

Gorry Fairhurst was in part supported by the European Community under its Seventh Framework Programme through the Reducing Internet Transport Latency (RITE) project (ICT-317700).

Gorry Fairhurst通过减少互联网传输延迟(RITE)项目(ICT-317700),部分得到了欧洲共同体第七框架计划的支持。

Authors' Addresses


Fred Baker (editor) Cisco Systems Santa Barbara, California 93117 United States



Godred Fairhurst (editor) University of Aberdeen School of Engineering Fraser Noble Building Aberdeen, Scotland AB24 3UE United Kingdom

Godred Fairhurst(编辑)阿伯丁大学工程学院弗雷泽贵族建筑苏格兰阿伯丁英国AB24 3UE