One document matched: draft-ietf-aqm-recommendation-05.txt
Differences from draft-ietf-aqm-recommendation-04.txt
Network Working Group F. Baker, Ed.
Internet-Draft Cisco Systems
Obsoletes: 2309 (if approved) G. Fairhurst, Ed.
Intended status: Best Current Practice University of Aberdeen
Expires: December 24, 2014 June 24, 2014
IETF Recommendations Regarding Active Queue Management
draft-ietf-aqm-recommendation-05
Abstract
This memo presents recommendations to the Internet community
concerning measures to improve and preserve Internet performance. It
presents a strong recommendation for testing, standardization, and
widespread deployment of active queue management (AQM) in network
devices, to improve the performance of today's Internet. It also
urges a concerted effort of research, measurement, and ultimate
deployment of AQM mechanisms to protect the Internet from flows that
are not sufficiently responsive to congestion notification.
The note largely repeats the recommendations of RFC 2309, updated
after fifteen years of experience and new research.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
Internet-Drafts are working documents of the Internet Engineering
Task Force (IETF). Note that other groups may also distribute
working documents as Internet-Drafts. The list of current Internet-
Drafts is at http://datatracker.ietf.org/drafts/current/.
Internet-Drafts are draft documents valid for a maximum of six months
and may be updated, replaced, or obsoleted by other documents at any
time. It is inappropriate to use Internet-Drafts as reference
material or to cite them other than as "work in progress."
This Internet-Draft will expire on December 18, 2014.
Copyright Notice
Copyright (c) 2014 IETF Trust and the persons identified as the
document authors. All rights reserved.
This document is subject to BCP 78 and the IETF Trust's Legal
Provisions Relating to IETF Documents
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(http://trustee.ietf.org/license-info) in effect on the date of
publication of this document. Please review these documents
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 2
1.1. Requirements Language . . . . . . . . . . . . . . . . . . 4
2. The Need For Active Queue Management . . . . . . . . . . . . 4
2.1. AQM and Multiple Queues . . . . . . . . . . . . . . . . . 8
2.2. AQM and Explicit Congestion Marking (ECN) . . . . . . . . 8
2.3. AQM and Buffer Size . . . . . . . . . . . . . . . . . . . 9
3. Managing Aggressive Flows . . . . . . . . . . . . . . . . . . 9
4. Conclusions and Recommendations . . . . . . . . . . . . . . . 12
4.1. Operational deployments SHOULD use AQM procedures . . . . 13
4.2. Signaling to the transport endpoints . . . . . . . . . . 13
4.2.1. AQM and ECN . . . . . . . . . . . . . . . . . . . . . 14
4.3. AQM algorithms deployed SHOULD NOT require operational
tuning . . . . . . . . . . . . . . . . . . . . . . . . . 15
4.4. AQM algorithms SHOULD respond to measured congestion, not
application profiles. . . . . . . . . . . . . . . . . . . 17
4.5. AQM algorithms SHOULD NOT be dependent on specific
transport protocol behaviours . . . . . . . . . . . . . . 17
4.6. Interactions with congestion control algorithms . . . . . 18
4.7. The need for further research . . . . . . . . . . . . . . 19
5. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 20
6. Security Considerations . . . . . . . . . . . . . . . . . . . 20
7. Privacy Considerations . . . . . . . . . . . . . . . . . . . 20
8. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 20
9. References . . . . . . . . . . . . . . . . . . . . . . . . . 21
9.1. Normative References . . . . . . . . . . . . . . . . . . 21
9.2. Informative References . . . . . . . . . . . . . . . . . 22
Appendix A. Change Log . . . . . . . . . . . . . . . . . . . . . 25
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 26
1. Introduction
The Internet protocol architecture is based on a connectionless end-
to-end packet service using the Internet Protocol, whether IPv4
[RFC0791] or IPv6 [RFC2460]. The advantages of its connectionless
design: flexibility and robustness, have been amply demonstrated.
However, these advantages are not without cost: careful design is
required to provide good service under heavy load. In fact, lack of
attention to the dynamics of packet forwarding can result in severe
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service degradation or "Internet meltdown". This phenomenon was
first observed during the early growth phase of the Internet in the
mid 1980s [RFC0896][RFC0970], and is technically called "congestive
collapse".
The original fix for Internet meltdown was provided by Van Jacobsen.
Beginning in 1986, Jacobsen developed the congestion avoidance
mechanisms [Jacobson88] that are now required for implementations of
the Transport Control Protocol (TCP) [RFC0768] [RFC1122]. These
mechanisms operate in Internet hosts to cause TCP connections to
"back off" during congestion. We say that TCP flows are "responsive"
to congestion signals (i.e., marked or dropped packets) from the
network. It is primarily these TCP congestion avoidance algorithms
that prevent the congestive collapse of today's Internet. Similar
algorithms are specified for other non-TCP transports.
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 congestion avoidance mechanisms
[RFC5681], while necessary and powerful, are not sufficient to
provide good service in all circumstances. Basically, there is a
limit to how much control can be accomplished from the edges of the
network. Some mechanisms are needed in the network devices to
complement the endpoint congestion avoidance mechanisms. These
mechanisms may be implemented in network devices that include
routers, switches, and other network middleboxes.
It is useful to distinguish between two classes of algorithms related
to congestion control: "queue management" versus "scheduling"
algorithms. To a rough approximation, queue management algorithms
manage the length of packet queues by marking or dropping packets
when necessary or appropriate, while scheduling algorithms determine
which packet to send next and are used primarily to manage the
allocation of bandwidth among flows. While these two mechanisms are
closely related, they address different performance issues and
operate on different timescales. Both may be used in combination.
This memo highlights two performance issues:
The first issue is the need for an advanced form of queue management
that we call "Active Queue Management", AQM. Section 2 summarizes
the benefits that active queue management can bring. A number of AQM
procedures are described in the literature, with different
characteristics. This document does not recommend any of them in
particular, but does make recommendations that ideally would affect
the choice of procedure used in a given implementation.
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The second issue, discussed in Section 3 of this memo, is the
potential for future congestive collapse of the Internet due to flows
that are unresponsive, or not sufficiently responsive, to congestion
indications. Unfortunately, while scheduling can mitigate some of
the side-effects of sharing a network queue with an unresponsive
flow, there is currently no consensus solution to controlling the
congestion caused by such aggressive flows. Methods such as
congestion exposure (ConEx) [RFC6789] offer a framework [CONEX] that
can update network devices to alleviate these effcects. Significant
research and engineering will be required before any solution will be
available. It is imperative that work to mitigate the impact of
unresponsive flows is energetically pursued, to ensure the future
stability of the Internet.
Section 4 concludes the memo with a set of recommendations to the
Internet community concerning these topics.
The discussion in this memo applies to "best-effort" traffic, which
is to say, traffic generated by applications that accept the
occasional loss, duplication, or reordering of traffic in flight. It
also applies to other traffic, such as real-time traffic that can
adapt its sending rate to reduce loss and/or delay. It is most
effective when the adaption occurs on time scales of a single Round
Trip Time (RTT) or a small number of RTTs, for elastic traffic
[RFC1633].
[RFC2309] resulted from past discussions of end-to-end performance,
Internet congestion, and Random Early Discard (RED) in the End-to-End
Research Group of the Internet Research Task Force (IRTF). This
update results from experience with this and other algorithms, and
the AQM discussion within the IETF[AQM-WG].
1.1. Requirements Language
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in [RFC2119].
2. The Need For Active Queue Management
Active Queue Management (AQM) is a method that allows network devices
to control the queue length or the mean time that a packet spends in
a queue. Although AQM can be applied across a range of deployment
enviroments, the recommendations in this document are directed to use
in the general Internet. It is expected that the principles and
guidance are also applicable to a wide range of environments, but may
require tuning for specific types of link/network (e.g. to
accommodate the traffic patterns found in data centres, the
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challenges of wireless infrastructure, or the higher delay
encountered on satellite Internet links). The remainder of this
section identifies the need for AQM and the advantages of deploying
the method.
The traditional technique for managing the queue length in a network
device is to set a maximum length (in terms of packets) for each
queue, accept packets for the queue until the maximum length is
reached, then reject (drop) subsequent incoming packets until the
queue decreases because a packet from the queue has been transmitted.
This technique is known as "tail drop", since the packet that arrived
most recently (i.e., the one on the tail of the queue) is dropped
when the queue is full. This method has served the Internet well for
years, but it has two important drawbacks:
1. Full Queues
The tail drop discipline allows queues to maintain a full (or,
almost full) status for long periods of time, since tail drop
signals congestion (via a packet drop) only when the queue has
become full. It is important to reduce the steady-state queue
size, and this is perhaps the most important goal for queue
management.
The naive assumption might be that there is a simple tradeoff
between delay and throughput, and that the recommendation that
queues be maintained in a "non-full" state essentially translates
to a recommendation that low end-to-end delay is more important
than high throughput. However, this does not take into account
the critical role that packet bursts play in Internet
performance. For example, even though TCP constrains the
congestion window of a flow, packets often arrive at network
devices in bursts [Leland94]. If the queue is full or almost
full, an arriving burst will cause multiple packets to be
dropped. This can result in a global synchronization of flows
throttling back, followed by a sustained period of lowered link
utilization, reducing overall throughput.
The point of buffering in the network is to absorb data bursts
and to transmit them during the (hopefully) ensuing bursts of
silence. This is essential to permit transmission of bursts of
data. Normally small queues are preferred in network devices,
with sufficient queue capacity to absorb the bursts. The
counter-intuitive result is that maintaining normally-small
queues can result in higher throughput as well as lower end-to-
end delay. In summary, queue limits should not reflect the
steady state queues we want to be maintained in the network;
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instead, they should reflect the size of bursts that a network
device needs to absorb.
2. Lock-Out
In some situations tail drop allows a single connection or a few
flows to monopolize the queue space starving other connection
preventing them from getting room in the queue.
3. Control loop synchronisation
Congestion control, like other end-to-end mechanisms, introduces
a control loop between hosts. Sessions that share a common network
bottleneck can therefore become synchronised, introducing
periodic disruption (e.g. jitter/loss). "lock-out" is often also
the result of synchronization or other timing effects.
Besides tail drop, two alternative queue management disciplines that
can be applied when a queue becomes full are "random drop on full" or
"head drop on full". When a new packet arrives at a full queue using
the random drop on full discipline, the network device drops a
randomly selected packet from the queue (which can be an expensive
operation, since it naively requires an O(N) walk through the packet
queue). When a new packet arrives at a full queue using the head
drop on full discipline, the network device drops the packet at the
front of the queue [Lakshman96]. Both of these solve the lock-out
problem, but neither solves the full-queues problem described above.
We know in general how to solve the full-queues problem for
"responsive" flows, i.e., those flows that throttle back in response
to congestion notification. In the current Internet, dropped packets
provide a critical mechanism indicating congestion notification to
hosts. The solution to the full-queues problem is for network
devices to drop packets before a queue becomes full, so that hosts
can respond to congestion before buffers overflow. We call such a
proactive approach AQM. By dropping packets before buffers overflow,
AQM allows network devices to control when and how many packets to
drop.
In summary, an active queue management mechanism can provide the
following advantages for responsive flows.
1. Reduce number of packets dropped in network devices
Packet bursts are an unavoidable aspect of packet networks
[Willinger95]. If all the queue space in a network device is
already committed to "steady state" traffic or if the buffer
space is inadequate, then the network device will have no ability
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to buffer bursts. By keeping the average queue size small, AQM
will provide greater capacity to absorb naturally-occurring
bursts without dropping packets.
Furthermore, without AQM, more packets will be dropped when a
queue does overflow. This is undesirable for several reasons.
First, with a shared queue and the tail drop discipline, this can
result in unnecessary global synchronization of flows, resulting
in lowered average link utilization, and hence lowered network
throughput. Second, unnecessary packet drops represent a waste
of network capacity on the path before the drop point.
While AQM can manage queue lengths and reduce end-to-end latency
even in the absence of end-to-end congestion control, it will be
able to reduce packet drops only in an environment that continues
to be dominated by end-to-end congestion control.
2. Provide a lower-delay interactive service
By keeping a small average queue size, AQM will reduce the delays
experienced by flows. This is particularly important for
interactive applications such as short web transfers, POP/IMAP,
DNS, terminal traffic (telnet, ssh, mosh, RDP, etc), gaming or
interactive audio-video sessions, whose subjective (and
objective) performance is better when the end-to-end delay is
low.
3. Avoid lock-out behavior
AQM can prevent lock-out behavior by ensuring that there will
almost always be a buffer available for an incoming packet. For
the same reason, AQM can prevent a bias against low capacity, but
highly bursty, flows.
Lock-out is undesirable because it constitutes a gross unfairness
among groups of flows. However, we stop short of calling this
benefit "increased fairness", because general fairness among
flows requires per-flow state, which is not provided by queue
management. For example, in a network device using AQM with only
FIFO scheduling, two TCP flows may receive very different share
of the network capacity simply because they have different round-
trip times [Floyd91], and a flow that does not use congestion
control may receive more capacity than a flow that does. AQM can
therefore be combined with a scheduling mechanism that divides
network traffic between multiple queues (section 2.1).
4. Reduce the probability of control loop synchronisation
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The probability of network control loop synchronisation can be
reduced by introducing randomness in the AQM functions used by
network devices that trigger congestion avoidance at the sending
host.
2.1. AQM and Multiple Queues
A network device may use per-flow or per-class queuing with a
scheduling algorithm to either prioritise certain applications or
classes of traffic, or to provide isolation between different traffic
flows within a common class. For example, a router may maintain per-
flow state to achieve general fairness by a per-flow scheduling
algorithm such as various forms of Fair Queueing (FQ) [Dem90],
including Weighted Fair Queuing (WFQ), Stochastic Fairness Queueing
(SFQ) [McK90] Deficit Round Robin (DRR) [Shr96] and/or a Class-Based
Queue scheduling algorithm such as CBQ [Floyd95]. Hierarchical
queues may also be used e.g., as a part of a Hierarchical Token
Bucket (HTB), or Hierarchical Fair Service Curve (HFSC) [Sto97] .
These methods are also used to realise a range of Quality of Service
(QoS) behaviours designed to + meet the need of traffic classes (e.g.
using the integrated or differentiated service models).
AQM is needed even for network devices that use per-flow or per-class
queuing, because scheduling algorithms by themselves do not control
the overall queue size or the size of individual queues. AQM
mechanisms need to control the overall queue sizes, to ensure that
arriving bursts can be accommodated without dropping packets. AQM
should also be used to control the queue size for each individual
flow or class, so that they do not experience unnecessarily high
delay. Using a combination of AQM and scheduling between multiple
queues has been shown to offer good results in experimental and some
types of operational use.
In short, scheduling algorithms and queue management should be seen
as complementary, not as replacements for each other.
2.2. AQM and Explicit Congestion Marking (ECN)
An AQM method may use Explicit Congestion Notification (ECN)
[RFC3168] instead of dropping to mark packets under mild or moderate
congestion. ECN-marking can allow a network device to signal
congestion at a point before a transport experiences congestion loss
or additional queuing delay [ECN-Benefit]. Section 4.2.1 describes
some of the benefits of using ECN with AQM.
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2.3. AQM and Buffer Size
It is important to differentiate the choice of buffer size for a
queue in a switch/router or other network device, and the
threshold(s) and other parameters that determine how and when an AQM
algorithm operates. One the one hand, the optimum buffer size is a
function of operational requirements and should generally be sized to
be sufficient to buffer the largest normal traffic burst that is
expected. This size depends on the number and burstiness of traffic
arriving at the queue and the rate at which traffic leaves the queue.
Different types of traffic and deployment scenarios will lead to
different requirements.
AQM frees a designer from having to the limit buffer space to achieve
acceptable performance, allowing allocation of sufficient buffering
to satisfy the needs of the particular traffic pattern. On the other
hand, the choice of AQM algorithm and associated parameters is a
function of the way in which congestion is experienced and the
required reaction to achieve acceptable performance. This latter
topic is the primary topic of the following sections.
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.
It is convenient to divide flows into three classes: (1) TCP Friendly
flows, (2) unresponsive flows, i.e., flows that do not slow down when
congestion occurs, and (3) flows that are responsive but are not TCP-
friendly. The last two classes contain more aggressive flows that
pose significant threats to Internet performance, which we will now
discuss.
1. TCP-Friendly flows
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A TCP-friendly flow responds to congestion notification within a
small number of path Round Trip Times (RTT), and in steady-state
it uses no more capacity than a conformant TCP running under
comparable conditions (drop rate, RTT, packet size, etc.). This
is described in the remainder of the document.
2. Non-Responsive Flows
The User Datagram Protocol (UDP) [RFC0768] provides a minimal,
best-effort transport to applications and upper-layer protocols
(both simply called "applications" in the remainder of this
document) and does not itself provide mechanisms to prevent
congestion collapse and establish a degree of fairness [RFC5405].
There is a growing set of UDP-based applications whose congestion
avoidance algorithms are inadequate or nonexistent (i.e, a flow
that does not throttle its sending rate when it experiences
congestion). Examples include some UDP streaming applications
for packet voice and video, and some multicast bulk data
transport. If no action is taken, such unresponsive flows could
lead to a new congestive collapse [RFC2309].
In general, UDP-based applications need to incorporate effective
congestion avoidance mechanisms [RFC5405]. Further research and
development of ways to accomplish congestion avoidance for
presently unresponsive applications continue to be important.
Network devices need to be able to protect themselves against
unresponsive flows, and mechanisms to accomplish this must be
developed and deployed. Deployment of such mechanisms would
provide an incentive for all applications to become responsive by
either using a congestion-controlled transport (e.g. TCP, SCTP
[RFC4960] and DCCP [RFC4340].) or by incorporating their own
congestion control in the application [RFC5405].
Lastly, some applications (e.g. current web browsers) open a
large numbers of 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.
3. Non-TCP-friendly Transport Protocols
A second threat is posed by transport protocol implementations
that are responsive to congestion, but, either deliberately or
through faulty implementation, are not TCP-friendly. Such
applications may gain an unfair share of the available network
capacity.
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For example, the popularity of the Internet has caused a
proliferation in the number of TCP implementations. Some of
these may fail to implement the TCP congestion avoidance
mechanisms correctly because of poor implementation. Others may
deliberately be implemented with congestion avoidance algorithms
that are more aggressive in their use of capacity than other TCP
implementations; this would allow a vendor to claim to have a
"faster TCP". The logical consequence of such implementations
would be a spiral of increasingly aggressive TCP implementations,
leading back to the point where there is effectively no
congestion avoidance and the Internet is chronically congested.
Another example could be an RTP/UDP video flow that uses an
adaptive codec, but responds incompletely to indications of
congestion or responds over an excessively long time period.
Such flows are unlikely to be responsive to congestion signals in
a timeframe 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 and peer-to-peer file-sharing) have exploited
this by opening multiple connections to the same endpoint.
The projected increase in the fraction of total Internet traffic for
more aggressive flows in classes 2 and 3 clearly poses a threat to
future Internet stability. There is an urgent need for measurements
of current conditions and for further research into the ways of
managing such flows. This raises many difficult issues in
identifying and isolating unresponsive or non-TCP-friendly flows at
an acceptable overhead cost. Finally, there is as yet little
measurement or simulation evidence available about the rate at which
these threats are likely to be realized, or about the expected
benefit of algorithms for managing such flows.
Another topic requiring consideration is the appropriate
granugranularity 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.
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
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"distinguishing" themselves from one another), and different
granularities may be chosen for different places in the network. It
may be the case that the granularity is less important than the fact
that a network device needs to be able to deal with more unresponsive
flows at *some* granularity. The granularity of flows for congestion
management is, at least in part, a question of policy that needs to
be addressed in the wider IETF community.
4. Conclusions and Recommendations
The IRTF, in publishing [RFC2309], and the IETF in subsequent
discussion, has developed a set of specific recommendations regarding
the implementation and operational use of AQM procedures. The
updated recommendations provided by this document are summarised as:
1. Network devices SHOULD implement some AQM mechanism to manage
queue lengths, reduce end-to-end latency, and avoid lock-out
phenomena within the Internet.
2. Deployed AQM algorithms SHOULD support Explicit Congestion
Notification (ECN) as well as loss to signal congestion to
endpoints.
3. The algorithms that the IETF recommends SHOULD NOT require
operational (especially manual) configuration or tuning.
4. AQM algorithms SHOULD respond to measured congestion, not
application profiles.
5. AQM algorithms SHOULD NOT interpret specific transport protocol
behaviours.
6. Transport protocol congestion control algorithms SHOULD maximize
their use of available capacity (when there is data to send)
without incurring undue loss or undue round trip delay.
7. Research, engineering, and measurement efforts are needed
regarding the design of mechanisms to deal with flows that are
unresponsive to congestion notification or are responsive, but
are more aggressive than present TCP.
These recommendations are expressed using the word "SHOULD". This is
in recognition that there may be use cases that have not been
envisaged in this document in which the recommendation does not
apply. 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
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in network cores that are normally very stable in depth and behavior
experience occasional issues that need moderation. The
recommendations are detailed in the following sections.
4.1. Operational deployments SHOULD use AQM procedures
AQM procedures are designed to minimize the delay and buffer
exhaustion induced in the network by queues that have filled as a
result of host behavior. Marking and loss behaviors provide a signal
that buffers within network devices are becoming unnecessarily full,
and that the sender would do well to moderate its behavior.
The use of scheduling mechanisms, such as priority queuing, classful
queuing, and fair queuing, is often effective in networks to help a
network serve the needs of a range of applications. Network
operators can use these methods to manage traffic passing a choke
point. This is discussed in [RFC2474] and [RFC2475]. 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 polices for
providing fairness between different flows.
o AQM should be used to control the queue size for each individual
flow or class, so that they do not experience unnecessarily high
delay.
4.2. Signaling to the transport endpoints
There are a number of ways a network device may signal to the end
point that the network is becoming congested and trigger a reduction
in rate. The signalling methods include:
o Delaying transport segments (packets) in flight, such as in a
queue.
o Dropping transport segments (packets) in transit.
o Marking transport segments (packets), such as using Explicit
Congestion Control[RFC3168] [RFC4301] [RFC4774] [RFC6040]
[RFC6679].
Increased network latency is used as an implicit signal of
congestion. E.g., in TCP additional delay can affect ACK Clocking
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and has the result of reducing the rate of transmission of new data.
In the Real Time Protocol (RTP), network latency impacts the RTCP-
reported RTT and increased latency can trigger a sender to adjust its
rate. Methods such as Low Extra Delay Background Transport (LEDBAT)
[RFC6817] assume increased latency as a primary signal of congestion.
Appropriate use of delay-based methods and the implications of AQM
presently remains an area for further research.
It is essential that all Internet hosts respond to loss [RFC5681],
[RFC5405][RFC4960][RFC4340]. Packet dropping by network devices that
are under load has two effects: It protects the network, which is the
primary reason that network devices drop packets. The detection of
loss also provides a signal to a reliable transport (e.g. TCP, SCTP)
that there is potential congestion using a pragmatic heuristic; "when
the network discards a message in flight, it may imply the presence
of faulty equipment or media in a path, and it may imply the presence
of congestion. To be conservative, a transport must assume it may be
the latter." Unreliable transports (e.g. using UDP) need to
similarly react to loss [RFC5405]
Network devices SHOULD use an AQM algorithm to determine the packets
that are marked or discarded due to congestion. Procedures for
dropping or marking packets within the network need to avoid
increasing synchronisation events, and hence randomness SHOULD be
introduced in the algorithms that generate these congestion signals
to the endpoints.
Loss also has an effect on the efficiency of a flow and can
significantly impact some classes of application. In reliable
transports the dropped data must be 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
signalling by loss is not entirely positive; it is a necessary evil.
4.2.1. AQM and ECN
Explicit Congestion Notification (ECN) [RFC4301] [RFC4774] [RFC6040]
[RFC6679] is a network-layer function that allows a transport to
receive network congestion information from a network device without
incurring the unintended consequences of loss. ECN includes both
transport mechanisms and functions implemented in network devices,
the latter rely upon using AQM to decider when and whether to ECN-
mark.
Congestion for ECN-capable transports is signalled by a network
device setting the "Congestion Experienced (CE)" codepoint in the IP
header. This codepoint is noted by the remote receiving end point
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and signalled back to the sender using a transport protocol
mechanism, allowing the sender to trigger timely congestion control.
The decision to set the CE codepoint requires an AQM algorithm
configured with a threshold. Non-ECN capable flows (the default) are
dropped under congestion.
Network devices SHOULD use an AQM algorithm that marks ECN-capable
traffic when making decisions about the response to congestion.
Network devices need to implement this method by marking ECN-capable
traffic or by dropping non-ECN-capable traffic.
Safe deployment of ECN requires that network devices drop excessive
traffic, even when marked as originating from an ECN-capable
transport. This is a necessary safety precaution because:
1. A non-conformant, broken or malicious receiver could conceal an
ECN mark, and not report this to the sender;
2. A non-conformant, broken or malicious sender could ignore a
reported ECN mark, as it could ignore a loss without using ECN;
3. A malfunctioning or non-conforming network device may "hide" an
ECN mark (or fail to correctly set the ECN codepoint at an egress
of a network tunnel).
In normal operation, such cases should be very uncommon, however
overload protection is desirable to protect traffic from
misconfigured or malicious use of ECN (e.g. a denial-of-service
attack that generates ECN-capable traffic that is unresponsive to CE-
marking).
An AQM algorithm that supports ECN needs to define the threshold and
algorithm for ECN-marking. This threshold MAY differ from that used
for dropping packets that are not marked as ECN-capable, and SHOULD
be configurable.
Network devices SHOULD use an algorithm to drop excessive traffic
(e.g. at some level above the threshold for CE-marking), even when
the packets are marked as originating from an ECN-capable transport.
4.3. AQM algorithms deployed 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.
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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. The
latter includes information observed from monitoring the size of the
queue, experienced queueing delay, rate of packet discard, etc.
This document therefore specifies that AQM algorithms that are
proposed for deployment in the Internet have the following
properties:
o SHOULD NOT require tuning of initial or configuration parameters.
An algorithm needs to provide a default behaviour 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 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). Guidance needs to
be provided on the cases where auto-tuning is unlikely to achieve
satisfactory performance and to identify the set of parameters
that can be tuned. For example, the expected response of an
algorithm may need to be configured to accommodate the largest
expected Path RTT, since this value can not be known at
initialisation. This guidance is expected to enable the algorithm
to be deployed in networks that have specific characteristics
(paths with variable/larger delay; networks where capacity is
impacted by interactions with lower layer mechanisms, etc).
o MAY provide logging and alarm signals to assist in identifying if
an algorithm using manual or auto-tuning is functioning as
expected. (e.g., 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.
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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 next section).
Other methods exist, e.g. Differentiated Services queueing, Pre-
Congestion Notification (PCN) [RFC5559], that can be used to
differentiate and police classes of application. Network devices may
combine AQM with these traffic classification mechanisms and perform
AQM only on specific queues within a network device.
An AQM algorithm should not deliberately try to prejudice the size of
packet that performs best (i.e. Preferentially drop/mark based only
on packet size). Procedures for selecting packets to mark/drop
SHOULD observe 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 should not be
taken into account [Byte-pkt].
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 or throughput, or other performance
parameter. When a transport or application responds to a dropped or
marked packet, the size of the rate reduction should be proportionate
to the size of the packet that was sent [Byte-pkt].
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 Differentiated Services Code Point (DSCP) [RFC5559],
enabling use of the ECN field (i.e. any of ECT(0), ECT(1) or
CE)[RFC3168] [RFC4774], a multi-field (MF) classifier that combines
the values of a set of protocol fields (e.g. IP address, transport,
ports) or an equivalent codepoint at a lower layer. This
recommendation goes beyond what is defined in RFC 3168, by allowing
that an implementation MAY use more than one instance of an AQM
algorithm to handle both ECN-capable and non-ECN-capable packets.
4.5. AQM algorithms SHOULD NOT be dependent on specific transport
protocol behaviours
In deploying AQM, network devices need to support a range of Internet
traffic and SHOULD NOT make implicit assumptions about the
characteristics desired by the set transports/applications the
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network supports. That is, AQM methods should be opaque to the
choice of transport and application.
AQM algorithms are often evaluated by considering TCP [RFC0793] with
a limited number of applications. Although TCP is the predominant
transport in the Internet today, this no longer represents a
sufficient selection of traffic for verification. There is
significant use of UDP [RFC0768] in voice and video services, and
some applications find utility in SCTP [RFC4960] and DCCP [RFC4340].
Hence, AQM algorithms should also demonstrate operation with
transports other than TCP and need to consider a variety of
applications. Selection of AQM algorithms also needs to consider use
of tunnel encapsulations that may carry traffic aggregates.
AQM algorithms SHOULD NOT target or derive implicit assumptions about
the characteristics desired by specific transports/applications.
Transports and applications need to respond to the congestion signals
provided by AQM (i.e. dropping or ECN-marking) in a timely manner
(within a few RTT at the latest).
4.6. Interactions with congestion control algorithms
Applications and transports need to react to received implicit or
explicit signals that indicate the presence of congestion. This
section identifies issues that can impact the design of transport
protocols when using paths that use AQM.
Transport protocols and applications need timely signals of
congestion. The time taken to detect and respond to congestion is
increased when network devices queue packets in buffers. It can be
difficult to detect tail losses at a higher layer and this may
sometimes require transport timers or probe packets to detect and
respond to such loss. Loss patterns may also impact timely
detection, e.g. the time may be reduced when network devices do not
drop long runs of packets from the same flow.
A common objective of an elastic transport congestion control
protocol is to allow an application to deliver the maximum rate of
data without inducing excessive delays when packets are queued in a
buffers within the network. To achieve this, a transport should try
to operate at rate below the inflexion point of the load/delay curve
(the bend of what is sometimes called a "hockey-stick" curve). 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
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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 less than permitted by the congestion
control window (or rate). Examples include multimedia codecs that
stream at some natural rate (or set of rates) or an application that
is naturally interactive (e.g., some web applications, gaming,
transaction-based protocols). Such applications may have different
objectives. They may not wish to maximize throughput, but may desire
a lower loss rate or bounded delay.
The correct operation of an AQM-enabled network device MUST NOT rely
upon specific transport responses to congestion signals.
4.7. The need for further research
The second recommendation of [RFC2309] called for further research
into the interaction between network queues and host applications,
and the means of signaling between them. This research has occurred,
and we as a community have learned a lot. However, we are not done.
We have learned that the problems of congestion, latency and buffer-
sizing have not gone away, and are becoming more important to many
users. A number of self-tuning AQM algorithms have been found that
offer significant advantages for deployed networks. There is also
renewed interest in deploying AQM and the potential of ECN.
In 2013, an obvious example of further research is the need to
consider the use of Map/Reduce applications in data centers; do we
need to extend our taxonomy of TCP/SCTP sessions to include not only
"mice" and "elephants", but "lemmings". "Lemmings" are flash crowds
of "mice" that the network inadvertently try to signal to as if they
were elephant flows, resulting in head of line blocking in data
center applications.
Examples of other required research include:
o Research into new AQM and scheduling algorithms.
o Appropriate use of delay-based methods and the implications of
AQM.
o Research into the use of and deployment of ECN alongside AQM.
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o Tools for enabling AQM (and ECN) deployment and measuring the
performance.
o Methods for mitigating the impact of non-conformant and malicious
flows.
o Research to understand the implications of using new network and
transport methods on applications.
Hence, this document therefore reiterates the call of RFC 2309: we
need continuing research as applications develop.
5. IANA Considerations
This memo asks the IANA for no new parameters.
6. Security Considerations
While security is a very important issue, it is largely orthogonal to
the performance issues discussed in this memo.
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
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 should consider ways to
mitigate such attacks.
7. Privacy Considerations
This document, by itself, presents no new privacy issues.
8. Acknowledgements
The original recommendation in [RFC2309] was written by the End-to-
End Research Group, which is to say Bob Braden, Dave Clark, Jon
Crowcroft, Bruce Davie, Steve Deering, Deborah Estrin, Sally Floyd,
Van Jacobson, Greg Minshall, Craig Partridge, Larry Peterson, KK
Ramakrishnan, Scott Shenker, John Wroclawski, and Lixia Zhang. This
is an edited version of that document, with much of its text and
arguments unchanged.
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The need for an updated document was agreed to in the tsvarea meeting
at IETF 86. This document was reviewed on the aqm@ietf.org list.
Comments were received from Colin Perkins, Richard Scheffenegger,
Dave Taht, John Leslie, David Collier-Brown and many others.
Gorry Fairhurst was in part supported by the European Community under
its Seventh Framework Programme through the Reducing Internet
Transport Latency (RITE) project (ICT-317700).
9. References
9.1. Normative References
[Byte-pkt]
and Internet Engineering Task Force, Work in Progress,
"Byte and Packet Congestion Notification (draft-ietf-
tsvwg-byte-pkt-congest)", July 2013.
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
[RFC3168] Ramakrishnan, K., Floyd, S., and D. Black, "The Addition
of Explicit Congestion Notification (ECN) to IP", RFC
3168, September 2001.
[RFC4301] Kent, S. and K. Seo, "Security Architecture for the
Internet Protocol", RFC 4301, December 2005.
[RFC4774] Floyd, S., "Specifying Alternate Semantics for the
Explicit Congestion Notification (ECN) Field", BCP 124,
RFC 4774, November 2006.
[RFC5405] Eggert, L. and G. Fairhurst, "Unicast UDP Usage Guidelines
for Application Designers", BCP 145, RFC 5405, November
2008.
[RFC5681] Allman, M., Paxson, V., and E. Blanton, "TCP Congestion
Control", RFC 5681, September 2009.
[RFC6040] Briscoe, B., "Tunnelling of Explicit Congestion
Notification", RFC 6040, November 2010.
[RFC6679] Westerlund, M., Johansson, I., Perkins, C., O'Hanlon, P.,
and K. Carlberg, "Explicit Congestion Notification (ECN)
for RTP over UDP", RFC 6679, August 2012.
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9.2. Informative References
[AQM-WG] "IETF AQM WG", .
[CONEX] Mathis, M. and B. Briscoe, "The Benefits to Applications
of using Explicit Congestion Notification (ECN)", IETF
(Work-in-Progress) draft-ietf-conex-abstract-mech, March
2014.
[Choi04] Sprint ATL, Burlingame, CA, , , , and , "Analysis of
Point-To-Point Packet Delay In an Operational Network",
March 2004.
[Dem90] Demers, A., Keshav, S., and S. Shenker, "Analysis and
Simulation of a Fair Queueing Algorithm, Internetworking:
Research and Experience", SIGCOMM Symposium proceedings on
Communications architectures and protocols , 1990.
[ECN-Benefit]
Welzl, M. and G. Fairhurst, "The Benefits to Applications
of using Explicit Congestion Notification (ECN)", IETF
(Work-in-Progress) , February 2014.
[Floyd91] Floyd, S., "Connections with Multiple Congested Gateways
in Packet-Switched Networks Part 1: One-way Traffic.",
Computer Communications Review , October 1991.
[Floyd95] Floyd, S. and V. Jacobson, "Link-sharing and Resource
Management Models for Packet Networks", IEEE/ACM
Transactions on Networking , August 1995.
[Jacobson88]
Jacobson, V., "Congestion Avoidance and Control", SIGCOMM
Symposium proceedings on Communications architectures and
protocols , August 1988.
[Jain94] Jain, Raj., Ramakrishnan, KK., and Chiu. Dah-Ming,
"Congestion avoidance scheme for computer networks", US
Patent Office 5377327, December 1994.
[Lakshman96]
Lakshman, TV., Neidhardt, A., and T. Ott, "The Drop From
Front Strategy in TCP Over ATM and Its Interworking with
Other Control Features", IEEE Infocomm , 1996.
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[Leland94]
Leland, W., Taqqu, M., Willinger, W., and D. Wilson, "On
the Self-Similar Nature of Ethernet Traffic (Extended
Version)", IEEE/ACM Transactions on Networking , February
1994.
[McK90] McKenney, PE. and G. Varghese, "Stochastic Fairness
Queuing",
http://www2.rdrop.com/~paulmck/scalability/paper/
sfq.2002.06.04.pdf , 1990.
[Nic12] Nichols, K., "Controlling Queue Delay", Communications of
the ACM Vol. 55 No. 11, July, 2012, pp.42-50. , July 2002.
[RFC0768] Postel, J., "User Datagram Protocol", STD 6, RFC 768,
August 1980.
[RFC0791] Postel, J., "Internet Protocol", STD 5, RFC 791, September
1981.
[RFC0793] Postel, J., "Transmission Control Protocol", STD 7, RFC
793, September 1981.
[RFC0896] Nagle, J., "Congestion control in IP/TCP internetworks",
RFC 896, January 1984.
[RFC0970] Nagle, J., "On packet switches with infinite storage", RFC
970, December 1985.
[RFC1122] Braden, R., "Requirements for Internet Hosts -
Communication Layers", STD 3, RFC 1122, October 1989.
[RFC1633] Braden, B., Clark, D., and S. Shenker, "Integrated
Services in the Internet Architecture: an Overview", RFC
1633, June 1994.
[RFC2309] Braden, B., Clark, D., Crowcroft, J., Davie, B., Deering,
S., Estrin, D., Floyd, S., Jacobson, V., Minshall, G.,
Partridge, C., Peterson, L., Ramakrishnan, K., Shenker,
S., Wroclawski, J., and L. Zhang, "Recommendations on
Queue Management and Congestion Avoidance in the
Internet", RFC 2309, April 1998.
[RFC2460] Deering, S. and R. Hinden, "Internet Protocol, Version 6
(IPv6) Specification", RFC 2460, December 1998.
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[RFC2474] Nichols, K., Blake, S., Baker, F., and D. Black,
"Definition of the Differentiated Services Field (DS
Field) in the IPv4 and IPv6 Headers", RFC 2474, December
1998.
[RFC2475] Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z.,
and W. Weiss, "An Architecture for Differentiated
Services", RFC 2475, December 1998.
[RFC4340] Kohler, E., Handley, M., and S. Floyd, "Datagram
Congestion Control Protocol (DCCP)", RFC 4340, March 2006.
[RFC4960] Stewart, R., "Stream Control Transmission Protocol", RFC
4960, September 2007.
[RFC5348] Floyd, S., Handley, M., Padhye, J., and J. Widmer, "TCP
Friendly Rate Control (TFRC): Protocol Specification", RFC
5348, September 2008.
[RFC5559] Eardley, P., "Pre-Congestion Notification (PCN)
Architecture", RFC 5559, June 2009.
[RFC6057] Bastian, C., Klieber, T., Livingood, J., Mills, J., and R.
Woundy, "Comcast's Protocol-Agnostic Congestion Management
System", RFC 6057, December 2010.
[RFC6789] Briscoe, B., Woundy, R., and A. Cooper, "Congestion
Exposure (ConEx) Concepts and Use Cases", RFC 6789,
December 2012.
[RFC6817] Shalunov, S., Hazel, G., Iyengar, J., and M. Kuehlewind,
"Low Extra Delay Background Transport (LEDBAT)", RFC 6817,
December 2012.
[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, June,
1999, pp. 1159-1169. , 1999.
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[Willinger95]
Willinger, W., Taqqu, M., Sherman, R., Wilson, D., and V.
Jacobson, "Self-Similarity Through High-Variability:
Statistical Analysis of Ethernet LAN Traffic at the Source
Level", SIGCOMM Symposium proceedings on Communications
architectures and protocols , August 1995.
Appendix A. Change Log
Initial Version: March 2013
Minor update of the algorithms that the IETF recommends SHOULD NOT
require operational (especially manual) configuration or tuningdate:
April 2013
Major surgery. This draft is for discussion at IETF-87 and expected
to be further updated.
July 2013
-00 WG Draft - Updated transport recommendations; revised deployment
configuration section; numerous minor edits.
Oct 2013
-01 WG Draft - Updated transport recommendations; revised deployment
configuration section; numerous minor edits.
Jan 2014 - Feedback from WG.
-02 WG Draft - Minor edits Feb 2014 - Mainly language fixes.
-03 WG Draft - Minor edits Feb 2013 - Comments from David Collier-
Brown and David Taht.
-04 WG Draft - Minor edits May 2014 - Comments during WGLC: Provided
some introductory subsections to help people (with subsections and
better text). - Written more on the role scheduling. - Clarified
that ECN mark threshold needs to be configurable. - Reworked your
"knee" para. Various updates in response to feedback.
-05 WG Draft - Minor edits June 2014 - New text added to address
further comments, and improve introduction - adding context,
reference to Conex, linking between sections, added text on
synchronisation.
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Authors' Addresses
Fred Baker (editor)
Cisco Systems
Santa Barbara, California 93117
USA
Email: fred@cisco.com
Godred Fairhurst (editor)
University of Aberdeen
School of Engineering
Fraser Noble Building
Aberdeen, Scotland AB24 3UE
UK
Email: gorry@erg.abdn.ac.uk
URI: http://www.erg.abdn.ac.uk
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