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RFC 7567


IETF Recommendations Regarding Active Queue Management

Part 2 of 2, p. 13 to 31
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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].

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

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

   1.  TCP-friendly flows

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

   2.  Non-responsive flows

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

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

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

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

   3.  Transport flows that are less responsive than TCP

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

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

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

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

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

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

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

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

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

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

4.  Conclusions and Recommendations

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

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

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

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

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

   5.  AQM algorithms SHOULD NOT interpret specific transport protocol

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

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

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

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4.1.  Operational Deployments SHOULD Use AQM Procedures

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

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

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

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

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

4.2.  Signaling to the Transport Endpoints

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

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

   o  Dropping transport segments (packets) in transit.

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

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

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

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

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

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

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

4.2.1.  AQM and ECN

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

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

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

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

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

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

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

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

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

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

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

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4.3.  AQM Algorithm Deployment SHOULD NOT Require Operational Tuning

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

4.6.  Interactions with Congestion Control Algorithms

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

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

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

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

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

4.7.  The Need for Further Research

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

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

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

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

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

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

   Examples of other required research include:

   o  new AQM and scheduling algorithms

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

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

   o  experience in the deployment of ECN alongside AQM

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

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

   o  implications on applications of using new network and transport

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

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5.  Security Considerations

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

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

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

6.  Privacy Considerations

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

7.  References

7.1.  Normative References

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

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

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

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

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

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

   [RFC6040]  Briscoe, B., "Tunnelling of Explicit Congestion
              Notification", RFC 6040, DOI 10.17487/RFC6040, 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, DOI 10.17487/RFC6679, August
              2012, <>.

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

7.2.  Informative References

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

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

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

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

Top      Up      ToC       Page 27 
   [Dem90]    Demers, A., Keshav, S., and S. Shenker, "Analysis and
              Simulation of a Fair Queueing Algorithm, Internetworking:
              Research and Experience", SIGCOMM Symposium proceedings on
              Communications architectures and protocols, 1990.

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

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

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

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

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

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

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

              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

Top      Up      ToC       Page 28 
   [McK90]    McKenney, PE. and G. Varghese, "Stochastic Fairness
              Queuing", 1990,

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

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

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

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

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

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

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

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

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

Top      Up      ToC       Page 29 
   [RFC2309]  Braden, B., Clark, D., Crowcroft, J., Davie, B., Deering,
              S., Estrin, D., Floyd, S., Jacobson, V., Minshall, G.,
              Partridge, C., Peterson, L., Ramakrishnan, K., Shenker,
              S., Wroclawski, J., and L. Zhang, "Recommendations on
              Queue Management and Congestion Avoidance in the
              Internet", RFC 2309, DOI 10.17487/RFC2309, April 1998,

   [RFC2460]  Deering, S. and R. Hinden, "Internet Protocol, Version 6
              (IPv6) Specification", RFC 2460, DOI 10.17487/RFC2460,
              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,
              DOI 10.17487/RFC2474, December 1998,

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

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

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

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

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

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

Top      Up      ToC       Page 30 
   [RFC6057]  Bastian, C., Klieber, T., Livingood, J., Mills, J., and R.
              Woundy, "Comcast's Protocol-Agnostic Congestion Management
              System", RFC 6057, DOI 10.17487/RFC6057, December 2010,

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

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

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

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

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

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

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

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

Top      Up      ToC       Page 31 

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

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

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

Authors' Addresses

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


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