3. Managing Aggressive Flows 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 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 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 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. 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. 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). 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 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. 2. Deployed AQM algorithms SHOULD support Explicit Congestion Notification (ECN) as well as loss to signal congestion to endpoints. 3. AQM algorithms SHOULD NOT require tuning of initial or configuration parameters in common use cases. 4. AQM algorithms SHOULD respond to measured congestion, not application profiles. 5. AQM algorithms SHOULD NOT interpret specific transport protocol behaviors. 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. 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. 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 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 mechanisms need to allow combination with other mechanisms, such as scheduling, to allow implementation of policies for providing fairness between different flows. 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. 4.2. Signaling to the Transport Endpoints 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 Dropping transport segments (packets) in transit. o Marking transport segments (packets), such as using Explicit Congestion Control [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 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; 2. A non-conformant, broken, or malicious sender could ignore a reported ECN mark, as it could ignore a loss without using 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). 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 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 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 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. 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 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. 4.5. AQM Algorithms SHOULD NOT Be Dependent on Specific Transport Protocol Behaviors 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 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 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 appropriate use of delay-based methods and the implications of AQM o suitable algorithms for marking ECN-capable packets that do not require operational configuration or tuning for common use o experience in the deployment of ECN alongside AQM o tools for enabling AQM (and ECN) deployment and measuring the performance o methods for mitigating the impact of non-conformant and malicious flows o implications on applications of using new network and transport methods Hence, this document reiterates the call of RFC 2309: we need continuing research as applications develop.
5. Security Considerations 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 This document, by itself, presents no new privacy issues. 7. References 7.1. Normative References [RFC2119] Bradner, S., "Key words for use in RFCs to Indicate Requirement Levels", BCP 14, RFC 2119, DOI 10.17487/RFC2119, March 1997, <http://www.rfc-editor.org/info/rfc2119>. [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, <http://www.rfc-editor.org/info/rfc3168>. [RFC4301] Kent, S. and K. Seo, "Security Architecture for the Internet Protocol", RFC 4301, DOI 10.17487/RFC4301, December 2005, <http://www.rfc-editor.org/info/rfc4301>.
[RFC4774] Floyd, S., "Specifying Alternate Semantics for the Explicit Congestion Notification (ECN) Field", BCP 124, RFC 4774, DOI 10.17487/RFC4774, November 2006, <http://www.rfc-editor.org/info/rfc4774>. [RFC5405] Eggert, L. and G. Fairhurst, "Unicast UDP Usage Guidelines for Application Designers", BCP 145, RFC 5405, DOI 10.17487/RFC5405, November 2008, <http://www.rfc-editor.org/info/rfc5405>. [RFC5681] Allman, M., Paxson, V., and E. Blanton, "TCP Congestion Control", RFC 5681, DOI 10.17487/RFC5681, September 2009, <http://www.rfc-editor.org/info/rfc5681>. [RFC6040] Briscoe, B., "Tunnelling of Explicit Congestion Notification", RFC 6040, DOI 10.17487/RFC6040, November 2010, <http://www.rfc-editor.org/info/rfc6040>. [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, <http://www.rfc-editor.org/info/rfc6679>. [RFC7141] Briscoe, B. and J. Manner, "Byte and Packet Congestion Notification", BCP 41, RFC 7141, DOI 10.17487/RFC7141, February 2014, <http://www.rfc-editor.org/info/rfc7141>. 7.2. Informative References [AQM-WG] IETF, "Active Queue Management and Packet Scheduling (aqm) WG", <http://datatracker.ietf.org/wg/aqm/charter/>. [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, <http://www.icir.org/floyd/papers/phase.pdf>. [Flo94] Floyd, S. and V. Jacobsen, "The Synchronization of Periodic Routing Messages", 1994, <http://ee.lbl.gov/papers/sync_94.pdf>. [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. [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. [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.
[McK90] McKenney, PE. and G. Varghese, "Stochastic Fairness Queuing", 1990, <http://www2.rdrop.com/~paulmck/scalability/paper/ 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, <http://www.rfc-editor.org/info/rfc768>. [RFC791] Postel, J., "Internet Protocol", STD 5, RFC 791, DOI 10.17487/RFC0791, September 1981, <http://www.rfc-editor.org/info/rfc791>. [RFC793] Postel, J., "Transmission Control Protocol", STD 7, RFC 793, DOI 10.17487/RFC0793, September 1981, <http://www.rfc-editor.org/info/rfc793>. [RFC896] Nagle, J., "Congestion Control in IP/TCP Internetworks", RFC 896, DOI 10.17487/RFC0896, January 1984, <http://www.rfc-editor.org/info/rfc896>. [RFC970] Nagle, J., "On Packet Switches With Infinite Storage", RFC 970, DOI 10.17487/RFC0970, December 1985, <http://www.rfc-editor.org/info/rfc970>. [RFC1122] Braden, R., Ed., "Requirements for Internet Hosts - Communication Layers", STD 3, RFC 1122, DOI 10.17487/RFC1122, October 1989, <http://www.rfc-editor.org/info/rfc1122>. [RFC1633] Braden, R., Clark, D., and S. Shenker, "Integrated Services in the Internet Architecture: an Overview", RFC 1633, DOI 10.17487/RFC1633, June 1994, <http://www.rfc-editor.org/info/rfc1633>.
[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, <http://www.rfc-editor.org/info/rfc2309>. [RFC2460] Deering, S. and R. Hinden, "Internet Protocol, Version 6 (IPv6) Specification", RFC 2460, DOI 10.17487/RFC2460, December 1998, <http://www.rfc-editor.org/info/rfc2460>. [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, <http://www.rfc-editor.org/info/rfc2474>. [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, <http://www.rfc-editor.org/info/rfc2475>. [RFC2914] Floyd, S., "Congestion Control Principles", BCP 41, RFC 2914, DOI 10.17487/RFC2914, September 2000, <http://www.rfc-editor.org/info/rfc2914>. [RFC4340] Kohler, E., Handley, M., and S. Floyd, "Datagram Congestion Control Protocol (DCCP)", RFC 4340, DOI 10.17487/RFC4340, March 2006, <http://www.rfc-editor.org/info/rfc4340>. [RFC4960] Stewart, R., Ed., "Stream Control Transmission Protocol", RFC 4960, DOI 10.17487/RFC4960, September 2007, <http://www.rfc-editor.org/info/rfc4960>. [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, <http://www.rfc-editor.org/info/rfc5348>. [RFC5559] Eardley, P., Ed., "Pre-Congestion Notification (PCN) Architecture", RFC 5559, DOI 10.17487/RFC5559, June 2009, <http://www.rfc-editor.org/info/rfc5559>.
[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, <http://www.rfc-editor.org/info/rfc6057>. [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, <http://www.rfc-editor.org/info/rfc6789>. [RFC6817] Shalunov, S., Hazel, G., Iyengar, J., and M. Kuehlewind, "Low Extra Delay Background Transport (LEDBAT)", RFC 6817, DOI 10.17487/RFC6817, December 2012, <http://www.rfc-editor.org/info/rfc6817>. [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, <http://www.rfc-editor.org/info/rfc7414>. [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. [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, <http://groups.csail.mit.edu/ana/Publications/Zhang-DDC- Oscillating-Behavior-of-Network-Traffic-1990.pdf>.
Acknowledgements 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. The need for an updated document was agreed to in the TSV area meeting at IETF 86. This document was reviewed on the email@example.com list. Comments were received from Colin Perkins, Richard Scheffenegger, Dave Taht, John Leslie, David Collier-Brown, and many others. 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). Authors' Addresses Fred Baker (editor) Cisco Systems Santa Barbara, California 93117 United States Email: firstname.lastname@example.org Godred Fairhurst (editor) University of Aberdeen School of Engineering Fraser Noble Building Aberdeen, Scotland AB24 3UE United Kingdom Email: email@example.com URI: http://www.erg.abdn.ac.uk