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Versions: (draft-baker-tsvwg-aqm-recommendation) 00 01 02 draft-ietf-aqm-recommendation

Network Working Group                                      F. Baker, Ed.
Internet-Draft                                             Cisco Systems
Obsoletes: 2309 (if approved)                          G. Fairhurst, Ed.
Intended status: Best Current Practice            University of Aberdeen
Expires: January 10, 2014                                  July 09, 2013


         IETF Recommendations Regarding Active Queue Management
                   draft-baker-aqm-recommendation-02

Abstract

   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.

   The note largely repeats the recommendations of RFC 2309, updated
   after fifteen years of experience and new research.

Status of This Memo

   This Internet-Draft is submitted in full conformance with the
   provisions of BCP 78 and BCP 79.

   Internet-Drafts are working documents of the Internet Engineering
   Task Force (IETF).  Note that other groups may also distribute
   working documents as Internet-Drafts.  The list of current Internet-
   Drafts is at http://datatracker.ietf.org/drafts/current/.

   Internet-Drafts are draft documents valid for a maximum of six months
   and may be updated, replaced, or obsoleted by other documents at any
   time.  It is inappropriate to use Internet-Drafts as reference
   material or to cite them other than as "work in progress."

   This Internet-Draft will expire on January 10, 2014.

Copyright Notice

   Copyright (c) 2013 IETF Trust and the persons identified as the
   document authors.  All rights reserved.

   This document is subject to BCP 78 and the IETF Trust's Legal
   Provisions Relating to IETF Documents



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   (http://trustee.ietf.org/license-info) 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.

Table of Contents

   1.  Introduction  . . . . . . . . . . . . . . . . . . . . . . . .   2
     1.1.  Requirements Language . . . . . . . . . . . . . . . . . .   4
   2.  The Need For Active Queue Management  . . . . . . . . . . . .   4
   3.  Managing Aggressive Flows . . . . . . . . . . . . . . . . . .   8
   4.  Conclusions and Recommendations . . . . . . . . . . . . . . .  10
     4.1.  Operational deployments SHOULD  use AQM procedures  . . .  11
     4.2.  Signaling to the transport endpoints  . . . . . . . . . .  11
       4.2.1.  AQM and ECN . . . . . . . . . . . . . . . . . . . . .  12
     4.3.  AQM algorithms deployed SHOULD NOT require operational
           tuning  . . . . . . . . . . . . . . . . . . . . . . . . .  13
     4.4.  AQM algorithms SHOULD respond to measured congestion, not
           application profiles. . . . . . . . . . . . . . . . . . .  13
     4.5.  AQM algorithms SHOULD NOT be dependent on specific
           transport protocol behaviours . . . . . . . . . . . . . .  14
     4.6.  Interactions with congestion control algorithms ????  . .  14
     4.7.  The need for further research . . . . . . . . . . . . . .  15
   5.  IANA Considerations . . . . . . . . . . . . . . . . . . . . .  16
   6.  Security Considerations . . . . . . . . . . . . . . . . . . .  16
   7.  Privacy Considerations  . . . . . . . . . . . . . . . . . . .  16
   8.  Acknowledgements  . . . . . . . . . . . . . . . . . . . . . .  16
   9.  References  . . . . . . . . . . . . . . . . . . . . . . . . .  17
     9.1.  Normative References  . . . . . . . . . . . . . . . . . .  17
     9.2.  Informative References  . . . . . . . . . . . . . . . . .  17
   Appendix A.  Change Log . . . . . . . . . . . . . . . . . . . . .  20
   Authors' Addresses  . . . . . . . . . . . . . . . . . . . . . . .  20

1.  Introduction














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   The Internet protocol architecture is based on a connectionless end-
   to-end packet service using the Internet Protocol, whether IPv4
   [RFC0791] 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 of the
   mid 1980s [RFC0896][RFC0970], and is technically called "congestive
   collapse".

   The original fix for Internet meltdown was provided by Van Jacobsen.
   Beginning in 1986, Jacobsen developed the congestion avoidance
   mechanisms that are now required in TCP implementations [Jacobson88]
   [RFC1122].  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., marked or dropped
   packets) from the network.  It is primarily these TCP congestion
   avoidance algorithms that prevent the congestive collapse of today's
   Internet.

   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 TCP 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 the network
   devices to complement the endpoint congestion avoidance mechanisms.
   These mechanisms may be implemented in network devices that include
   routers, switches, and other network middleboxes.

   It is useful to distinguish between two classes of algorithms related
   to congestion control: "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 AQM mechanisms
   are closely related, they address different performance issues.

   This memo highlights two performance issues:

   The first issue is the need for an advanced form of queue management
   that we call "active queue management."  Section 2 summarizes the
   benefits that active queue management can bring.  A number of Active
   Queue Management (AQM) procedures are described in the literature,



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   with different characteristics.  This document does not recommend any
   of them in particular, but does make recommendations that ideally
   would affect the choice of procedure used in a given implementation.

   The second issue, discussed in Section 3 of this memo, is the
   potential for future congestive collapse of the Internet due to flows
   that are unresponsive, or not sufficiently responsive, to congestion
   indications.  Unfortunately, there is no consensus solution to
   controlling congestion caused by such aggressive flows; significant
   research and engineering will be required before any solution will be
   available.  It is imperative that this work be energetically pursued,
   to ensure the future stability of the Internet.

   Section 4 concludes the memo with a set of recommendations to the
   Internet community concerning these topics.

   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 time scales of a single RTT or
   a small number of RTTs, for elastic traffic [RFC1633].

   [RFC2309] 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).  This update results from
   experience with this and other algorithms, and the Active Queue
   Management discussion within the IETF.

1.1.  Requirements Language

   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

   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 two important drawbacks.




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   1.  Lock-Out

       In some situations tail drop allows a single connection or a few
       flows to monopolize queue space, preventing other connections
       from getting room in the queue.  This "lock-out" phenomenon is
       often the result of synchronization or other timing effects.

   2.  Full Queues

       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 tradeoff
       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.  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.  This can result
       in a global synchronization of flows throttling back, followed by
       a sustained period of lowered link utilization, reducing overall
       throughput.

       The point 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 the transmission of bursty
       data.  Normally we would like to have mall queues in network
       devices: with sufficient queue capacity to absorb the bursts.
       The counter-intuitive result is that maintaining normally-small
       queues can result in higher throughput as well as lower end-to-
       end delay.  In short, 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.

   Besides tail drop, two alternative queue disciplines that can be
   applied when a queue becomes full are "random drop on full" or "drop
   front on full".  Under the random drop on full discipline, a network
   device drops a randomly selected packet from the queue (which can be
   an expensive operation, since it naively requires an O(N) walk
   through the packet queue) when the queue is full and a new packet



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   arrives.  Under the "drop front on full" discipline [Lakshman96], the
   network device drops the packet at the front of the queue when the
   queue is full and a new packet arrives.  Both of these solve the
   lock-out problem, but neither solves the full-queues problem
   described above.

   We know in general 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 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 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

       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
       possible 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






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       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, Telnet
       traffic, 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

       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 share
       of the network capacity simply because they have different round-
       trip times [Floyd91], and a flow that does not use congestion
       control may receive more capacity than a flow that does.  For
       example, a router may maintain per-flow state to achieve general
       fairness by a per-flow scheduling algorithm such as Fair Queueing
       (FQ) [Demers90], or a Class-Based Queue scheduling algorithm such
       as CBQ [Floyd95].

       In contrast, AQM is needed even for network devices that use per-
       flow scheduling algorithms such as FQ or class-based scheduling
       algorithms, such as CBQ.  This is because per-flow scheduling
       algorithms by themselves do not control the overall queue size or
       the size of individual queues.  AQM is needed to control the
       overall average queue sizes, so that arriving bursts can be
       accommodated without dropping packets.  In addition, AQM should
       be used to control the queue size for each individual flow or
       class, so that they do not experience unnecessarily high delay.
       Therefore, AQM should be applied across the classes or flows as
       well as within each class or flow.

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









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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].

   We call a flow "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.

   It is convenient to divide flows into three classes: (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 not TCP-
   friendly.  The last two classes contain more aggressive flows that
   pose significant threats to Internet performance, which we will now
   discuss.

   1.  TCP-Friendly flows

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

   2.  Non-Responsive Flows

       The User Datagram Protocol (UDP) [RFC0768] 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 and establish a degree of fairness [RFC5405].

       There is a growing set of UDP-based applications whose congestion
       avoidance algorithms are inadequate or nonexistent (i.e, a flow
       that does not throttle its sending rate when it experiences
       congestion).  Examples include some UDP streaming applications
       for packet voice and video, and some multicast bulk data
       transport.  If no action is taken, such unresponsive flows could
       lead to a new congestive collapse [RFC2309].



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       In general, UDP-based applications need to incorporate effective
       congestion avoidance mechanisms [RFC5405].  Further research and
       development of ways to accomplish congestion avoidance for
       presently unresponsive applications continue to be
       important.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, DCCP) or by incorporating their own congestion
       control in the application.  [RFC5405].

   3.  Non-TCP-friendly Transport Protocols

       A second threat is posed by transport protocol implementations
       that are responsive to congestion, but, either deliberately or
       through faulty implementation, are not TCP-friendly.  Such
       applications 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 over 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 of multiple (short) TCP flows can be
       more aggressive than standard bulk TCP.  Applications (e.g. web
       browsers and peer-to-peer file-sharing) have exploited this by
       opening multiple connections to the same endpoint.

   The projected increase in the fraction of total Internet traffic for
   more aggressive flows in classes 2 and 3 clearly poses a threat to



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   future Internet stability.  There is 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
   identifying and isolating unresponsive or non-TCP-friendly flows at
   an acceptable overhead cost.  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, DSCP); 2) a source/
   destination host pair (IP addresses, DSCP); 3) a given source host or
   a given destination host.  We suggest that the source/destination
   host pair gives the most appropriate granularity in many
   circumstances.  However, it is possible that different vendors/
   providers could set different granularities for defining a flow (as a
   way of "distinguishing" themselves from one another), or that
   different granularities could 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 publishing [RFC2309], and the IETF in subsequent
   discussion, has developed a set of specific recommendations regarding
   the implementation and operational use of AQM procedures.  This
   document updates these to include:

   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.  The algorithms that the IETF recommends SHOULD NOT require
       operational (especially manual) configuration or tuning.

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





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

   6.  Transport protocol congestion control algorithms 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.  However, 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 on.  To the
   contrary, available research [Papagiannaki] says that even high speed
   links in network cores that are normally very stable in depth and
   behavior experience occasional issues that need moderation.

4.1.  Operational deployments SHOULD use AQM procedures

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

4.2.  Signaling to the transport endpoints

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

   o  Delaying data segments in flight, such as in a queue.

   o  Dropping traffic in transit.

   o  Marking traffic, such as using Explicit Congestion
      Control[RFC3168] [RFC4301] [RFC4774] [RFC6040] [RFC6679].

   The use of scheduling mechanisms, such as priority queuing, classful
   queuing, and fair queuing, 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].



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   Increased network latency can be used as an implicit signal of
   congestion.  E.g., in TCP additional delay can affect ACK Clocking
   and has the result of reducing the rate of transmission of new data.
   In RTP, this impacts the RTCP-reported RTT and can trigger a sender
   to adjust its rate.  For example, LEDBAT [RFC6817] assumes delay as a
   primary signal of congestion.

   It is essential that all Internet hosts respond to loss [RFC5681],
   [RFC5405][RFC2960][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 potential congestion using a pragmatic heuristic; "when
   the network discards a message in flight, it may imply the presence
   of faulty equipment or media in a path, and it may imply the presence
   of congestion.  To be conservative transport must the latter."
   Unreliable transports (e.g. using UDP) need to similarly react to
   loss [RFC5405]

   Network devices SHOULD use use an AQM algorithm to determine which
   packets are effected by congestion.

   Loss 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 retransmitted.  While other
   applications/transports may adapt to the absence of the data, this
   still implies inefficient use of available capacity and the dropped
   traffic can affect other flows.  Hence, 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 and functions implemented in network devices, the latter
   rely upon using AQM.

   Congestion for ECN-capable transports is instead signalled by a
   network device setting the "Congestion Experienced (CE)" codepoint in
   the IP header.  This codepoint is noted by the remote receiving end
   point and signalled 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.




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   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 necessary 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 devices may
   similarly "hide" and ECN mark.  In normal operation such cases should
   be very uncommon.

   Network devices SHOULD use an algorithm to drop excessive traffic,
   even when marked as originating from an ECN capable transport.

4.3.  AQM algorithms deployed SHOULD NOT require operational tuning

   A number of algorithms have been proposed.  Many require some form of
   tuning or initial condition.  This can make them difficult to use
   operationally.  Hence, self-tuning algorithms are to be preferred.
   The algorithms that the IETF recommends SHOULD 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 characterised by particular profiles of packet
   size this should not be used as the basis for AQM.  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 mark/drop
   SHOULD observe actual or projected time 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 should not be taken into account [Byte-pkt].

   Applications (or transports) generally know what packet size they are
   using and can hence make their judgements about whether to use small



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   or large packets based on the data they wish to send and the expected
   impact on the delay or 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 [Byte-pkt].

4.5.  AQM algorithms SHOULD NOT be dependent on specific transport
      protocol behaviours

   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 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 [RFC0793] with
   a limited number of applications.  Although TCP is the predominant
   transport in the Internet today.  This is no longer represents a
   sufficient selection of traffic for verification.  There is
   significant use of UDP [RFC0768] in voice and video services, and
   some applications find utility in SCTP [RFC4960] and DCCP [RFC4340].
   Hence, AQM algorithms should also demonstrate operation with
   transports other than TCP and need to consider a variety of
   applications.  AQM algorithms also need to consider use of tunnel
   encapsulations, which may carry traffic aggregates.

   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 RTT 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.

   When speaking of TCP performance, the terms "knee" and "cliff" area
   defined by [Jain94].  They respectively refer to the minimum
   congestion window that maximises throughput and the maximum
   congestion window that avoids loss.  An application that transmits at
   the rate determined by this window has the effect of maximizing the
   rate or throughput.  For the sender, exceeding the cliff is
   ineffective, as it (by definition) induces loss; operating at a point
   close to the cliff has a negative impact on other traffic and
   applications, triggering operator activities, such as those discussed
   in [RFC6057].  Operating below the knee reduces the throughput, since
   the sender fails to use available network capacity.



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   If the objective is to deliver data from its source to its recipient
   in the least possible time, as a result, the behavior of any elastic
   transport congestion control algorithm should seek to use an
   effective window at or above the knee and well below the cliff.
   Choice of an appropriate rate can significantly impact the loss and
   delay experienced not only by a flow but by other flows that share
   the same queue.

   Some applications may send less than permitted by the congestion
   control window (or rate).  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, gaming,
   transaction-based protocols).  Such applications may not wish to
   maximise throughput, but may also desire a lower loss rate or bounded
   delay.

   Transport protocols and applications need timely signals of
   congestion.  The time taken to detect and respond to congestion is
   assisted by network devices not dropping long runs of packets from
   the same flow.  It is difficult to detect tail losses at a higher
   layer and may sometimes require timers or probes to detect and
   respond to such loss.

   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 in
   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 be found that
   offer significant advantages for deployed networks.  There is also
   renewed interest in deploying AQM and the potential of ECN.

   An obvious example of further research in 2013 is the need to
   consider the use of Map/Reduce applications in data centers; do we
   need to extend our taxonomy of TCP/SCTP sessions to include not only
   "mice" and "elephants", but "lemmings"?  "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 data
   center applications.

   Examples of other required research include:



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   o  Research into new AQM and scheduling algorithms.

   o  Research into the use of and 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.

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

5.  IANA Considerations

   This memo asks the IANA for no new parameters.

6.  Security Considerations

   While security is a very important issue, it is largely orthogonal to
   the performance issues discussed in this memo.  We note, however,
   that denial-of-service attacks may create unresponsive traffic flows
   that may be indistinguishable from other flows (e.g. tunnels carrying
   aggregates of short flows, high-rate isochronous applications).  This
   threat exists also in network devices that do not deploy AQM, but
   when AQM is deployed could be used to degrade the benefit of the new
   method.  The recommendations support ongoing research applicable to
   such attacks.

7.  Privacy Considerations

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

8.  Acknowledgements

   The original recommendation in [RFC2309] 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.  This
   is an edited version of that document, with much of its text and
   arguments unchanged.

   The need for an updated document was agreed to in the tsvarea meeting
   at IETF 86.  This document was reviewed on the aqm@ietf.org list.
   Comments came from Colin Perkins, Richard Scheffenegger, and Dave
   Taht.




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   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).

9.  References

9.1.  Normative References

   [Byte-pkt]
              Internet Engineering Task Force, Work in Progress, "Byte
              and Packet Congestion Notification (draft-ietf-tsvwg-byte-
              pkt-congest)", July 2013.

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

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

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

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

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

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

   [RFC6040]  Briscoe, B., "Tunnelling of Explicit Congestion
              Notification", RFC 6040, November 2010.

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

9.2.  Informative References

   [Demers90]
              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.



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   [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, Raj., Ramakrishnan, KK., and Chiu. 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.

   [Papagiannaki]
              Sprint ATL, KAIST, University of Minnesota, Sprint ATL,
              Intel Research, "Analysis of Point-To-Point Packet Delay
              In an Operational Network", IEEE Infocom 2004, March 2004,
              <http://www.ieee-infocom.org/2004/Papers/37_4.PDF>.

   [RFC0768]  Postel, J., "User Datagram Protocol", STD 6, RFC 768,
              August 1980.

   [RFC0791]  Postel, J., "Internet Protocol", STD 5, RFC 791, September
              1981.

   [RFC0793]  Postel, J., "Transmission Control Protocol", STD 7, RFC
              793, September 1981.

   [RFC0896]  Nagle, J., "Congestion control in IP/TCP internetworks",
              RFC 896, January 1984.

   [RFC0970]  Nagle, J., "On packet switches with infinite storage", RFC
              970, December 1985.



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   [RFC1122]  Braden, R., "Requirements for Internet Hosts -
              Communication Layers", STD 3, RFC 1122, October 1989.

   [RFC1633]  Braden, B., Clark, D., and S. Shenker, "Integrated
              Services in the Internet Architecture: an Overview", RFC
              1633, June 1994.

   [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, April 1998.

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

   [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, December
              1998.

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

   [RFC2960]  Stewart, R., Xie, Q., Morneault, K., Sharp, C.,
              Schwarzbauer, H., Taylor, T., Rytina, I., Kalla, M.,
              Zhang, L., and V. Paxson, "Stream Control Transmission
              Protocol", RFC 2960, October 2000.

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

   [RFC4960]  Stewart, R., "Stream Control Transmission Protocol", RFC
              4960, September 2007.

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

   [RFC5559]  Eardley, P., "Pre-Congestion Notification (PCN)
              Architecture", RFC 5559, June 2009.

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





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

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

   [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.

Appendix A.  Change Log

   Initial Version:  March 2013

   Minor uphe algorithms that the IETF recommends SHOULD NOT require
   operational (especially manual) configuration or tuningdate:
      April 2013

   -02; Major surgery.  This draft is for discussion at IETF-87 and
   expected to be further updated.
      July 2013

Authors' Addresses

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

   Email: fred@cisco.com


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

   Email: gorry@erg.abdn.ac.uk
   URI:   http://www.erg.abdn.ac.uk





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