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rfc:rfc2309

Network Working Group B. Braden, USC/ISI Request for Comments: 2309 D. Clark, MIT LCS Category: Informational J. Crowcroft, UCL

                                               B. Davie, Cisco Systems
                                             S. Deering, Cisco Systems
                                                        D. Estrin, USC
                                                        S. Floyd, LBNL
                                                     V. Jacobson, LBNL
                                                G. Minshall, Fiberlane
                                                     C. Partridge, BBN
                                    L. Peterson, University of Arizona
                                    K. Ramakrishnan, ATT Labs Research
                                                S. Shenker, Xerox PARC
                                                J. Wroclawski, MIT LCS
                                                        L. Zhang, UCLA
                                                            April 1998
   Recommendations on Queue Management and Congestion Avoidance
                          in the Internet

Status of Memo

    This memo provides information for the Internet community.  It
    does not specify an Internet standard of any kind.  Distribution
    of this memo is unlimited.

Copyright Notice

    Copyright (C) The Internet Society (1998).  All Rights Reserved.

Abstract

    This memo presents two 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 in routers,
    to improve the performance of today's Internet.  It also urges a
    concerted effort of research, measurement, and ultimate deployment
    of router mechanisms to protect the Internet from flows that are
    not sufficiently responsive to congestion notification.

Braden, et. al. Informational [Page 1] RFC 2309 Internet Performance Recommendations April 1998

1. INTRODUCTION

 The Internet protocol architecture is based on a connectionless end-
 to-end packet service using the IP protocol.  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 [Nagle84], and is technically called
 "congestion collapse".
 The original fix for Internet meltdown was provided by Van Jacobson.
 Beginning in 1986, Jacobson developed the congestion avoidance
 mechanisms that are now required in TCP implementations [Jacobson88,
 HostReq89].  These mechanisms operate in the hosts to cause TCP
 connections to "back off" during congestion.  We say that TCP flows
 are "responsive" to congestion signals (i.e., dropped packets) from
 the network.  It is primarily these TCP congestion avoidance
 algorithms that prevent the congestion 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 [RFC2001], 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 routers to
 complement the endpoint congestion avoidance mechanisms.
 It is useful to distinguish between two classes of router algorithms
 related to congestion control: "queue management" versus "scheduling"
 algorithms.  To a rough approximation, queue management algorithms
 manage the length of packet queues by 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 router mechanisms are closely
 related, they address rather different performance issues.
 This memo highlights two router performance issues.  The first issue
 is the need for an advanced form of router queue management that we
 call "active queue management."  Section 2 summarizes the benefits
 that active queue management can bring.  Section 3 describes a
 recommended active queue management mechanism, called Random Early
 Detection or "RED".  We expect that the RED algorithm can be used
 with a wide variety of scheduling algorithms, can be implemented
 relatively efficiently, and will provide significant Internet

Braden, et. al. Informational [Page 2] RFC 2309 Internet Performance Recommendations April 1998

 performance improvement.
 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, 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 5 concludes the memo with a set of recommendations to the
 IETF concerning these topics.
 The discussion in this memo applies to "best-effort" traffic.  The
 Internet integrated services architecture, which provides a mechanism
 for protecting individual flows from congestion, introduces its own
 queue management and scheduling algorithms [Shenker96, Wroclawski96].
 Similarly, the discussion of queue management and congestion control
 requirements for differential services is a separate issue.  However,
 we do not expect the deployment of integrated services and
 differential services to significantly diminish the importance of the
 best-effort traffic issues discussed in this memo.
 Preparation of this memo 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).

2. THE NEED FOR ACTIVE QUEUE MANAGEMENT

 The traditional technique for managing router queue lengths 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.
 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.

Braden, et. al. Informational [Page 3] RFC 2309 Internet Performance Recommendations April 1998

 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 queue management's most important
      goal.
      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 a flow's
      window size, packets often arrive at routers 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.  It should be clear why we would like to have normally-
      small queues in routers: we want to have 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
      maintained in the network; instead, they should reflect the size
      of bursts we need to absorb.
 Besides tail drop, two alternative queue disciplines that can be
 applied when the queue becomes full are "random drop on full" or
 "drop front on full".  Under the random drop on full discipline, a
 router 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
 arrives.  Under the "drop front on full" discipline [Lakshman96], the
 router 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.

Braden, et. al. Informational [Page 4] RFC 2309 Internet Performance Recommendations April 1998

 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
 serve as a critical mechanism of congestion notification to end
 nodes.  The solution to the full-queues problem is for routers to
 drop packets before a queue becomes full, so that end nodes can
 respond to congestion before buffers overflow.  We call such a
 proactive approach "active queue management".  By dropping packets
 before buffers overflow, active queue management allows routers to
 control when and how many packets to drop.  The next section
 introduces RED, an active queue management mechanism that solves both
 problems listed above (given responsive flows).
 In summary, an active queue management mechanism can provide the
 following advantages for responsive flows.
 1.   Reduce number of packets dropped in routers
      Packet bursts are an unavoidable aspect of packet networks
      [Willinger95].  If all the queue space in a router is already
      committed to "steady state" traffic or if the buffer space is
      inadequate, then the router will have no ability to buffer
      bursts.  By keeping the average queue size small, active queue
      management will provide greater capacity to absorb naturally-
      occurring bursts without dropping packets.
      Furthermore, without active queue management, 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, an unnecessary global synchronization of flows
      cutting back can result in lowered average link utilization, and
      hence lowered network throughput.  Second, TCP recovers with
      more difficulty from a burst of packet drops than from a single
      packet drop.  Third, unnecessary packet drops represent a
      possible waste of bandwidth on the way to the drop point.
      We note that while RED can manage queue lengths and reduce end-
      to-end latency even in the absence of end-to-end congestion
      control, RED will be able to reduce packet dropping only in an
      environment that continues to be dominated by end-to-end
      congestion control.
 2.   Provide lower-delay interactive service
      By keeping the average queue size small, queue management will
      reduce the delays seen by flows.  This is particularly important
      for interactive applications such as short Web transfers, Telnet
      traffic, or interactive audio-video sessions, whose subjective

Braden, et. al. Informational [Page 5] RFC 2309 Internet Performance Recommendations April 1998

      (and objective) performance is better when the end-to-end delay
      is low.
 3.   Avoid lock-out behavior
      Active queue management can prevent lock-out behavior by
      ensuring that there will almost always be a buffer available for
      an incoming packet.  For the same reason, active queue
      management can prevent a router bias against low bandwidth but
      highly bursty flows.
      It is clear that 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 router
      using queue management but only FIFO scheduling, two TCP flows
      may receive very different bandwidths simply because they have
      different round-trip times [Floyd91], and a flow that does not
      use congestion control may receive more bandwidth than a flow
      that does.  Per-flow state to achieve general fairness might be
      maintained by a per-flow scheduling algorithm such as Fair
      Queueing (FQ) [Demers90], or a class-based scheduling algorithm
      such as CBQ [Floyd95], for example.
      On the other hand, active queue management is needed even for
      routers 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 nothing to
      control the overall queue size or the size of individual queues.
      Active queue management is needed to control the overall average
      queue sizes, so that arriving bursts can be accommodated without
      dropping packets.  In addition, active queue management should
      be used to control the queue size for each individual flow or
      class, so that they do not experience unnecessarily high delays.
      Therefore, active queue management 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.  In
      particular, there have been implementations of queue management
      added to FQ, and work is in progress to add RED queue management
      to CBQ.

Braden, et. al. Informational [Page 6] RFC 2309 Internet Performance Recommendations April 1998

3. THE QUEUE MANAGEMENT ALGORITHM "RED"

 Random Early Detection, or RED, is an active queue management
 algorithm for routers that will provide the Internet performance
 advantages cited in the previous section [RED93].  In contrast to
 traditional queue management algorithms, which drop packets only when
 the buffer is full, the RED algorithm drops arriving packets
 probabilistically.  The probability of drop increases as the
 estimated average queue size grows.  Note that RED responds to a
 time-averaged queue length, not an instantaneous one.  Thus, if the
 queue has been mostly empty in the "recent past", RED won't tend to
 drop packets (unless the queue overflows, of course!). On the other
 hand, if the queue has recently been relatively full, indicating
 persistent congestion, newly arriving packets are more likely to be
 dropped.
 The RED algorithm itself consists of two main parts: estimation of
 the average queue size and the decision of whether or not to drop an
 incoming packet.
 (a) Estimation of Average Queue Size
      RED estimates the average queue size, either in the forwarding
      path using a simple exponentially weighted moving average (such
      as presented in Appendix A of [Jacobson88]), or in the
      background (i.e., not in the forwarding path) using a similar
      mechanism.
         Note: The queue size can be measured either in units of
         packets or of bytes.  This issue is discussed briefly in
         [RED93] in the "Future Work" section.
         Note: when the average queue size is computed in the
         forwarding path, there is a special case when a packet
         arrives and the queue is empty.  In this case, the
         computation of the average queue size must take into account
         how much time has passed since the queue went empty.  This is
         discussed further in [RED93].
 (b) Packet Drop Decision
      In the second portion of the algorithm, RED decides whether or
      not to drop an incoming packet.  It is RED's particular
      algorithm for dropping that results in performance improvement
      for responsive flows.  Two RED parameters, minth (minimum
      threshold) and maxth (maximum threshold), figure prominently in

Braden, et. al. Informational [Page 7] RFC 2309 Internet Performance Recommendations April 1998

      this decision process.  Minth specifies the average queue size
      *below which* no packets will be dropped, while maxth specifies
      the average queue size *above which* all packets will be
      dropped.  As the average queue size varies from minth to maxth,
      packets will be dropped with a probability that varies linearly
      from 0 to maxp.
         Note: a simplistic method of implementing this would be to
         calculate a new random number at each packet arrival, then
         compare that number with the above probability which varies
         from 0 to maxp.  A more efficient implementation, described
         in [RED93], computes a random number *once* for each dropped
         packet.
         Note: the decision whether or not to drop an incoming packet
         can be made in "packet mode", ignoring packet sizes, or in
         "byte mode", taking into account the size of the incoming
         packet.  The performance implications of the choice between
         packet mode or byte mode is discussed further in [Floyd97].
 RED effectively controls the average queue size while still
 accommodating bursts of packets without loss.  RED's use of
 randomness breaks up synchronized processes that lead to lock-out
 phenomena.
 There have been several implementations of RED in routers, and papers
 have been published reporting on experience with these
 implementations ([Villamizar94], [Gaynor96]).  Additional reports of
 implementation experience would be welcome, and will be posted on the
 RED web page [REDWWW].
 All available empirical evidence shows that the deployment of active
 queue management mechanisms in the Internet would have substantial
 performance benefits.  There are seemingly no disadvantages to using
 the RED algorithm, and numerous advantages.  Consequently, we believe
 that the RED active queue management algorithm should be widely
 deployed.
 We should note that there are some extreme scenarios for which RED
 will not be a cure, although it won't hurt and may still help.  An
 example of such a scenario would be a very large number of flows,
 each so tiny that its fair share would be less than a single packet
 per RTT.

Braden, et. al. Informational [Page 8] RFC 2309 Internet Performance Recommendations April 1998

4. 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 bandwidth is shared
 reasonably equitably among similarly situated flows.  The equitable
 sharing of bandwidth among flows depends on the fact that all flows
 are running basically the same congestion avoidance algorithms,
 conformant with the current TCP specification [HostReq89].
 We introduce the term "TCP-compatible" for a flow that behaves under
 congestion like a flow produced by a conformant TCP.  A TCP-
 compatible flow is responsive to congestion notification, and in
 steady-state it uses no more bandwidth than a conformant TCP running
 under comparable conditions (drop rate, RTT, MTU, etc.)
 It is convenient to divide flows into three classes: (1) TCP-
 compatible 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-compatible.  The last two classes contain more
 aggressive flows that pose significant threats to Internet
 performance, as we will now discuss.
 o    Non-Responsive Flows
      There is a growing set of UDP-based applications whose
      congestion avoidance algorithms are inadequate or nonexistent
      (i.e, the flow does not throttle back upon receipt of congestion
      notification).  Such UDP applications include streaming
      applications like packet voice and video, and also multicast
      bulk data transport [SRM96].  If no action is taken, such
      unresponsive flows could lead to a new congestion collapse.
      In general, all UDP-based streaming applications should
      incorporate effective congestion avoidance mechanisms.  For
      example, recent research has shown the possibility of
      incorporating congestion avoidance mechanisms such as Receiver-
      driven Layered Multicast (RLM) within UDP-based streaming
      applications such as packet video [McCanne96; Bolot94]. Further
      research and development on ways to accomplish congestion
      avoidance for streaming applications will be very important.
      However, it will also be important for the network to be able to
      protect itself against unresponsive flows, and mechanisms to
      accomplish this must be developed and deployed.  Deployment of
      such mechanisms would provide incentive for every streaming
      application to become responsive by incorporating its own

Braden, et. al. Informational [Page 9] RFC 2309 Internet Performance Recommendations April 1998

      congestion control.
 o    Non-TCP-Compatible Transport Protocols
      The second threat is posed by transport protocol implementations
      that are responsive to congestion notification but, either
      deliberately or through faulty implementations, are not TCP-
      compatible.  Such applications can grab an unfair share of the
      network bandwidth.
      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 bandwidth 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.
      Note that there is a well-known way to achieve more aggressive
      TCP performance without even changing TCP: open multiple
      connections to the same place, as has been done in some Web
      browsers.
 The projected increase in more aggressive flows of both these
 classes, as a fraction of total Internet traffic, clearly poses a
 threat to the future Internet.  There is an urgent need for
 measurements of current conditions and for further research into the
 various ways of managing such flows.  There are many difficult issues
 in identifying and isolating unresponsive or non-TCP-compatible flows
 at an acceptable router overhead cost.  Finally, there is little
 measurement or simulation evidence available about the rate at which
 these threats are likely to be realized, or about the expected
 benefit of router algorithms for managing such flows.
 There is an issue about the appropriate granularity of a "flow".
 There are a few "natural" answers: 1) a TCP or UDP connection (source
 address/port, destination address/port); 2) a source/destination host
 pair; 3) a given source host or a given destination host.  We would
 guess 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

Braden, et. al. Informational [Page 10] RFC 2309 Internet Performance Recommendations April 1998

 be chosen for different places in the network.  It may be the case
 that the granularity is less important than the fact that we are
 dealing with more unresponsive flows at *some* granularity.  The
 granularity of flows for congestion management is, at least in part,
 a policy question that needs to be addressed in the wider IETF
 community.

5. CONCLUSIONS AND RECOMMENDATIONS

 This discussion leads us to make the following recommendations to the
 IETF and to the Internet community as a whole.
 o    RECOMMENDATION 1:
      Internet routers should implement some active queue management
      mechanism to manage queue lengths, reduce end-to-end latency,
      reduce packet dropping, and avoid lock-out phenomena within the
      Internet.
      The default mechanism for managing queue lengths to meet these
      goals in FIFO queues is Random Early Detection (RED) [RED93].
      Unless a developer has reasons to provide another equivalent
      mechanism, we recommend that RED be used.
 o    RECOMMENDATION 2:
      It is urgent to begin or continue research, engineering, and
      measurement efforts contributing to the design of mechanisms to
      deal with flows that are unresponsive to congestion notification
      or are responsive but more aggressive than TCP.
 Although there has already been some limited deployment of RED in the
 Internet, we may expect that widespread implementation and deployment
 of RED in accordance with Recommendation 1 will expose a number of
 engineering issues.  For example, such issues may include:
 implementation questions for Gigabit routers, the use of RED in layer
 2 switches, and the possible use of additional considerations, such
 as priority, in deciding which packets to drop.
 We again emphasize that the widespread implementation and deployment
 of RED would not, in and of itself, achieve the goals of
 Recommendation 2.
 Widespread implementation and deployment of RED will also enable the
 introduction of other new functionality into the Internet.  One
 example of an enabled functionality would be the addition of explicit
 congestion notification [Ramakrishnan97] to the Internet
 architecture, as a mechanism for congestion notification in addition

Braden, et. al. Informational [Page 11] RFC 2309 Internet Performance Recommendations April 1998

 to packet drops.  A second example of new functionality would be
 implementation of queues with packets of different drop priorities;
 packets would be transmitted in the order in which they arrived, but
 during times of congestion packets of the lower drop priority would
 be preferentially dropped.

6. References

 [Bolot94] Bolot, J.-C., Turletti, T., and Wakeman, I., Scalable
 Feedback Control for Multicast Video Distribution in the Internet,
 ACM SIGCOMM '94, Sept. 1994.
 [Demers90] Demers, A., Keshav, S., and Shenker, S., Analysis and
 Simulation of a Fair Queueing Algorithm, Internetworking: Research
 and Experience, Vol. 1, 1990, pp. 3-26.
 [Floyd91] Floyd, S., Connections with Multiple Congested Gateways in
 Packet-Switched Networks Part 1: One-way Traffic.  Computer
 Communications Review, Vol.21, No.5, October 1991, pp.  30-47.  URL
 http://ftp.ee.lbl.gov/floyd/.
 [Floyd95] Floyd, S., and Jacobson, V., Link-sharing and Resource
 Management Models for Packet Networks. IEEE/ACM Transactions on
 Networking, Vol. 3 No. 4, pp. 365-386, August 1995.
 [Floyd97] Floyd, S., RED: Discussions of Byte and Packet Modes, March
 1997 email, http://www-nrg.ee.lbl.gov/floyd/REDaveraging.txt.
 [Gaynor96] Gaynor, M., Proactive Packet Dropping Methods for TCP
 Gateways, October 1996, URL http://www.eecs.harvard.edu/~gaynor/
 final.ps.
 [HostReq89] Braden, R., Ed., "Requirements for Internet Hosts --
 Communication Layers", STD 3, RFC 1122, October 1989.
 [Jacobson88] V. Jacobson, Congestion Avoidance and Control, ACM
 SIGCOMM '88, August 1988.
 [Lakshman96] T. V. Lakshman, Arnie Neidhardt, Teunis Ott, The Drop
 From Front Strategy in TCP Over ATM and Its Interworking with Other
 Control Features, Infocom 96, MA28.1.
 [Leland94] W. Leland, M. Taqqu, W. Willinger, and D. Wilson, On the
 Self-Similar Nature of Ethernet Traffic (Extended Version), IEEE/ACM
 Transactions on Networking, 2(1), pp. 1-15, February 1994.

Braden, et. al. Informational [Page 12] RFC 2309 Internet Performance Recommendations April 1998

 [McCanne96] McCanne, S., Jacobson, V., and M. Vetterli, Receiver-
 driven Layered Multicast, ACM SIGCOMM
 [Nagle84] Nagle, J., "Congestion Control in IP/TCP", RFC 896, January
 1984.
 [Ramakrishnan97] Ramakrishnan, K. K., and S. Floyd, "A Proposal to
 add Explicit Congestion Notification (ECN) to IPv6 and to TCP", Work
 in Progress.
 [RED93] Floyd, S., and Jacobson, V., Random Early Detection gateways
 for Congestion Avoidance, IEEE/ACM Transactions on Networking, V.1
 N.4, August 1993, pp. 397-413.  Also available from
 http://ftp.ee.lbl.gov/floyd/red.html.
 [REDWWW] Floyd, S., The RED Web Page, 1997, URL
 http://ftp.ee.lbl.gov/floyd/red.html.
 [RFC 2001] Stevens, W., "TCP Slow Start, Congestion Avoidance, Fast
 Retransmit, and Fast Recovery Algorithms", RFC 2001, January 1997.
 [Shenker96] Shenker, S., Partridge, C., and R. Guerin, "Specification
 of Guaranteed Quality of Service", Work in Progress.
 [SRM96] Floyd. S., Jacobson, V., McCanne, S., Liu, C., and L. Zhang,
 A Reliable Multicast Framework for Light-weight Sessions and
 Application Level Framing.  ACM SIGCOMM '96, pp 342-355.
 [Villamizar94] Villamizar, C., and Song, C., High Performance TCP in
 ANSNET. Computer Communications Review, V. 24 N. 5, October 1994, pp.
 45-60.  URL http://ftp.ans.net/pub/papers/tcp-performance.ps.
 [Willinger95] W. Willinger, M. S. Taqqu, R. Sherman, D. V.  Wilson,
 Self-Similarity Through High-Variability:  Statistical Analysis of
 Ethernet LAN Traffic at the Source Level, ACM SIGCOMM '95, pp.  100-
 113, August 1995.
 [Wroclawski96] Wroclawski, J., "Specification of the Controlled-Load
 Network Element Service", Work in Progress.

Braden, et. al. Informational [Page 13] RFC 2309 Internet Performance Recommendations April 1998

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 are indistinguishable from flows from normal high-bandwidth
 isochronous applications, and the mechanism suggested in
 Recommendation 2 will be equally applicable to such attacks.

Authors' Addresses

 Bob Braden
 USC Information Sciences Institute
 4676 Admiralty Way
 Marina del Rey, CA 90292
 Phone: 310-822-1511
 EMail: Braden@ISI.EDU
 David D. Clark
 MIT Laboratory for Computer Science
 545 Technology Sq.
 Cambridge, MA  02139
 Phone: 617-253-6003
 EMail: DDC@lcs.mit.edu
 Jon Crowcroft
 University College London
 Department of Computer Science
 Gower Street
 London, WC1E 6BT
 ENGLAND
 Phone: +44 171 380 7296
 EMail: Jon.Crowcroft@cs.ucl.ac.uk
 Bruce Davie
 Cisco Systems, Inc.
 250 Apollo Drive
 Chelmsford, MA 01824
 Phone:
 EMail: bdavie@cisco.com

Braden, et. al. Informational [Page 14] RFC 2309 Internet Performance Recommendations April 1998

 Steve Deering
 Cisco Systems, Inc.
 170 West Tasman Drive
 San Jose, CA 95134-1706
 Phone: 408-527-8213
 EMail: deering@cisco.com
 Deborah Estrin
 USC Information Sciences Institute
 4676 Admiralty Way
 Marina del Rey, CA 90292
 Phone: 310-822-1511
 EMail: Estrin@usc.edu
 Sally Floyd
 Lawrence Berkeley National Laboratory,
 MS 50B-2239,
 One Cyclotron Road,
 Berkeley CA 94720
 Phone:  510-486-7518
 EMail: Floyd@ee.lbl.gov
 Van Jacobson
 Lawrence Berkeley National Laboratory,
 MS 46A,
 One Cyclotron Road,
 Berkeley CA 94720
 Phone: 510-486-7519
 EMail: Van@ee.lbl.gov
 Greg Minshall
 Fiberlane Communications
 1399 Charleston Road
 Mountain View, CA  94043
 Phone:  +1 650 237 3164
 EMail:  Minshall@fiberlane.com

Braden, et. al. Informational [Page 15] RFC 2309 Internet Performance Recommendations April 1998

 Craig Partridge
 BBN Technologies
 10 Moulton St.
 Cambridge MA 02138
 Phone: 510-558-8675
 EMail: craig@bbn.com
 Larry Peterson
 Department of Computer Science
 University of Arizona
 Tucson, AZ 85721
 Phone: 520-621-4231
 EMail: LLP@cs.arizona.edu
 K. K. Ramakrishnan
 AT&T Labs. Research
 Rm. A155
 180 Park Avenue
 Florham Park, N.J. 07932
 Phone: 973-360-8766
 EMail: KKRama@research.att.com
 Scott Shenker
 Xerox PARC
 3333 Coyote Hill Road
 Palo Alto, CA 94304
 Phone: 415-812-4840
 EMail: Shenker@parc.xerox.com
 John Wroclawski
 MIT Laboratory for Computer Science
 545 Technology Sq.
 Cambridge, MA  02139
 Phone: 617-253-7885
 EMail: JTW@lcs.mit.edu
 Lixia Zhang
 UCLA
 4531G Boelter Hall
 Los Angeles, CA 90024
 Phone: 310-825-2695
 EMail: Lixia@cs.ucla.edu

Braden, et. al. Informational [Page 16] RFC 2309 Internet Performance Recommendations April 1998

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Braden, et. al. Informational [Page 17]

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