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Network Working Group                                 B. Braden, USC/ISIRequest for Comments: 2309                             D. Clark, MIT LCSCategory: 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 1998Recommendations on Queue Management and Congestion Avoidancein the InternetStatus 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 19981. 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 InternetBraden, et. al.              Informational                      [Page 2]

RFC 2309          Internet Performance Recommendations        April 1998   performance improvement.   The second issue, discussed inSection 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 subjectiveBraden, 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 19983. 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 inAppendix 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 inBraden, 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 19984. 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 ownBraden, 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 couldBraden, 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 additionBraden, 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.  URLhttp://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, URLhttp://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 fromhttp://ftp.ee.lbl.gov/floyd/red.html.   [REDWWW] Floyd, S., The RED Web Page, 1997, URLhttp://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.  URLhttp://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 1998Security 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.comBraden, 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.comBraden, 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.eduBraden, et. al.              Informational                     [Page 16]

RFC 2309          Internet Performance Recommendations        April 1998Full Copyright Statement   Copyright (C) The Internet Society (1998).  All Rights Reserved.   This document and translations of it may be copied and furnished to   others, and derivative works that comment on or otherwise explain it   or assist in its implementation may be prepared, copied, published   and distributed, in whole or in part, without restriction of any   kind, provided that the above copyright notice and this paragraph are   included on all such copies and derivative works.  However, this   document itself may not be modified in any way, such as by removing   the copyright notice or references to the Internet Society or other   Internet organizations, except as needed for the purpose of   developing Internet standards in which case the procedures for   copyrights defined in the Internet Standards process must be   followed, or as required to translate it into languages other than   English.   The limited permissions granted above are perpetual and will not be   revoked by the Internet Society or its successors or assigns.   This document and the information contained herein is provided on an   "AS IS" basis and THE INTERNET SOCIETY AND THE INTERNET ENGINEERING   TASK FORCE DISCLAIMS ALL WARRANTIES, EXPRESS OR IMPLIED, INCLUDING   BUT NOT LIMITED TO ANY WARRANTY THAT THE USE OF THE INFORMATION   HEREIN WILL NOT INFRINGE ANY RIGHTS OR ANY IMPLIED WARRANTIES OF   MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE.Braden, et. al.              Informational                     [Page 17]