Report from the IAB/IRTF Workshop on Congestion Control for Interactive Real-Time Communication
RFC 7295
This RFC was published on the Internet Architecture Board (IAB) stream.
This RFC is not endorsed by the IETF and has no formal standing in the
IETF standards process.
| Document | Type |
RFC
- Informational
(July 2014)
Was
draft-iab-cc-workshop-report
(individual)
|
|
|---|---|---|---|
| Authors | Hannes Tschofenig , Lars Eggert , Zaheduzzaman Sarker | ||
| Last updated | 2018-12-20 | ||
| RFC stream | Internet Architecture Board (IAB) | ||
| Formats |
RFC 7295
Internet Architecture Board (IAB) H. Tschofenig
Request for Comments: 7295 L. Eggert
Category: Informational Z. Sarker
ISSN: 2070-1721 July 2014
Report from the IAB/IRTF Workshop on Congestion Control
for Interactive Real-Time Communication
Abstract
This document provides a summary of the IAB/IRTF Workshop on
'Congestion Control for Interactive Real-Time Communication', which
took place in Vancouver, Canada, on July 28, 2012. The main goal of
the workshop was to foster a discussion on congestion control
mechanisms for interactive real-time communication. This report
summarizes the discussions and lists recommendations to the Internet
Engineering Task Force (IETF) community.
The views and positions in this report are those of the workshop
participants and do not necessarily reflect the views and positions
of the authors, the Internet Architecture Board (IAB), or the
Internet Research Task Force (IRTF).
Status of This Memo
This document is not an Internet Standards Track specification; it is
published for informational purposes.
This document is a product of the Internet Architecture Board (IAB)
and represents information that the IAB has deemed valuable to
provide for permanent record. It represents the consensus of the
Internet Architecture Board (IAB). Documents approved for
publication by the IAB are not a candidate for any level of Internet
Standard; see Section 2 of RFC 5741.
Information about the current status of this document, any errata,
and how to provide feedback on it may be obtained at
http://www.rfc-editor.org/info/rfc7295.
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RFC 7295 Congestion Control Workshop Report July 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
(http://trustee.ietf.org/license-info) in effect on the date of
publication of this document. Please review these documents
carefully, as they describe your rights and restrictions with respect
to this document.
Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Workshop Structure . . . . . . . . . . . . . . . . . . . . . 5
2.1. History and Current Challenges . . . . . . . . . . . . . 5
2.2. Simulations and Measurements . . . . . . . . . . . . . . 8
2.3. Design Aspects of Problems and Solutions . . . . . . . . 9
3. Recommendations . . . . . . . . . . . . . . . . . . . . . . . 13
3.1. Changes to Network Infrastructure . . . . . . . . . . . . 14
3.2. Avoiding Self-Inflicted Queuing . . . . . . . . . . . . . 15
4. Security Considerations . . . . . . . . . . . . . . . . . . . 17
5. Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . 17
6. Informative References . . . . . . . . . . . . . . . . . . . 17
Appendix A. Program Committee . . . . . . . . . . . . . . . . . 22
Appendix B. Workshop Material . . . . . . . . . . . . . . . . . 22
Appendix C. Accepted Position Papers . . . . . . . . . . . . . . 22
Appendix D. Workshop Participants . . . . . . . . . . . . . . . 24
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1. Introduction
The Internet Architecture Board (IAB) holds occasional workshops
designed to consider long-term issues and strategies for the
Internet, and to suggest future directions for the Internet
architecture. This long-term planning function of the IAB is
complementary to the ongoing engineering efforts performed by working
groups of the Internet Engineering Task Force (IETF), under the
leadership of the Internet Engineering Steering Group (IESG) and area
directorates.
Any application that sends significant amounts of data over the
Internet is expected to implement reasonable congestion control
behavior. The goals for congestion control are well understood and
documented in RFC 2914 [2] and RFC 5405 [1]:
1. Preventing congestion collapse.
2. Allowing multiple flows to share the network fairly.
The Internet has been used for interactive real-time communication
for decades, most of which is being transmitted using the Real-Time
Transport Protocol (RTP) over UDP, often over provisioned capacity
and/or using only rudimentary congestion control mechanisms. In
2004, the IAB raised concerns regarding possibilities of a congestion
collapse due to a rapid growth in real-time voice traffic that does
not practice end-to-end congestion control [17]. That congestion
collapse did not happen, but concerns raised about both congestion
collapse and fairness are still valid and have gained more relevance
when applied to more bandwidth-hungry video applications. The
development and upcoming widespread deployment of web-based real-time
media communication -- where RTP is used to and from web browsers to
transmit audio, video, and data -- will likely result in substantial
new Internet traffic. Due to the projected volume of this traffic,
as well as the fact that it is more likely to use unprovisioned
capacity, it is essential that it is transmitted with robust and
effective congestion control mechanisms.
Designing congestion control mechanisms that perform well under a
wide variety of traffic mixes and over network paths with widely
varying characteristics is not easy. Prevention of congestion
collapse can be achieved through a "circuit breaker" mechanism (see,
for example, [3]), but for media flows that are supposed to coexist
with a user's other ongoing communication sessions, a congestion
control mechanism that shares capacity fairly in the presence of a
mix of TCP, UDP, and other protocol flows is needed.
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Many additional complications arise. Here are some examples:
1. Real-time interactive media sessions require low latencies,
whereas streaming media can use large play-out buffers.
2. In an RTP session, feedback exchanged via the RTP Control
Protocol (RTCP) typically arrives much less frequently than, for
example, TCP ACKs for a given TCP connection. Theoretically, the
RTP/RTCP control loop can lead to a longer reaction time.
3. Media codecs can usually only adjust their output rates in a much
more coarse-grained fashion than, for example, TCP, and user
experience suffers if encoding rates are switched too frequently.
Codecs typically have a minimum sending rate as well.
4. Some bits of an encoded media stream are more important than
others. For example, losing or dropping an I-frame of a video
stream is more problematic than dropping a P-frame [40].
5. Ramping up the transmission rate can be problematic. Simply
increasing the output rate of the codec without knowing whether
the network path can sustain transmission at the increased rate
runs the danger of incurring a significant amount of packet loss
that can cause playback artifacts.
6. A congestion control scheme for interactive media needs to handle
bundles of interrelated flows (audio, video, and data) in a way
that accommodates the preferences of the application in the event
of congestion.
7. The desire to provide a congestion control mechanism that can be
efficiently implemented inside an application imposes additional
restrictions. For example, a web browser is not able to take the
protocol interactions of a software download happening in another
application into account.
8. There are explicit congestion signals (such as Explicit
Congestion Notification (ECN) [19]), and there are implicit
indications of congestion (e.g., packet delay and loss). Care
must be taken to account for each of these signals, particularly
if various applications react on the same set of signals.
9. Large buffers are often used in network elements and end device
operating systems to better support TCP-based applications.
These buffers introduce additional communication delay, which
harms the small delay budget available for interactive real-time
applications.
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2. Workshop Structure
The IETF has a long history of work on congestion control mechanisms.
With ongoing standardization work on real-time interactive media
communication on the web, new challenges have emerged that have
refocused engineering attention on congestion control issues. To
take a deeper look at congestion control in light of the growth of
real-time traffic, workshop participants were invited to submit
position papers that were then used to organize the workshop agenda
into three principal components: a keynote talk given by Mark Handley
describing the history of the work on congestion control for real-
time media followed and his views of current problems; a presentation
of simulations and data demonstrating current problems and solutions;
and a discussion of desirable solution properties and challenges in
deploying solutions.
2.1. History and Current Challenges
Mark Handley argued that since 1988, the Internet has remained
functional despite exponential growth, routers that are sometimes
buggy or misconfigured, rapidly changing applications and usage
patterns, and flash crowds. This is largely because most
applications use TCP, and TCP implements end-to-end congestion
control.
TCP's congestion control adapts the window to fit the capacity
available in the network and accomplishes approximate fairness
between two competing flows over a period of time. Mark indicated
that the provided level of fairness is not necessarily what we want:
The 1/round-trip-time relationship in TCP is not ideal since it means
that network operators can decide to lower packet loss by adding
bigger buffers (which unfortunately leads to bufferbloat problems;
see [31] and [39]). The 1/sqrt(packet drop rate) relationship is
also not necessarily desirable since TCP initially did not work
particularly well for high-speed flows (which had been the subject of
much TCP research).
TCP controls the congestion window in bytes. For bulk transfer,
usually this results in controlling the number of 1500-byte packets
sent per second. Real-time media is different since it has its own
time constraints. For audio, one wants to send one packet per 20 ms
and for video, the ideal value would be 25 to 30 frames per second.
One, therefore, wants to avoid additional sending delay.
As an example, in case of video, to relieve congestion one has to
reduce the number of packets-per-second transmission rate rather than
transmit smaller packets, since at higher bitrates on WiFi the time
it takes to send a packet is almost negligible compared to the time
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that is spent with Media Access Control (MAC) layer operations.
Reducing the packet size makes little difference to the available
capacity. For a serial line, it does not matter how big the packets
are.
From a network point of view, the goals of congestion control
therefore are:
1. Avoid congestion collapse
2. Avoid starvation of TCP flows
3. Avoid starvation of real-time flows, specifically in the case
where TCP and real-time flows share the same FIFO queue.
From an application point of view, the goals of congestion control
are different, namely:
1. Robust behavior. One wants to have a good throughput when the
network is working well and passable performance when the network
is working poorly.
2. Predictable behavior. This matters from a usability point of
view since variable media creates a bad user experience.
3. Low latency. With large buffers along the end-to-end path,
latency will increase when interactive real-time flows compete
with TCP flows. This results in TCP filling up the buffers;
increased buffering will lead to additional delays for the
delivery of the interactive real-time media.
Attempts to provide congestion control for interactive real-time
media have previously been made in the IETF, for example, with the
work on TCP Friendly Rate Control (TFRC) [12]. TFRC illustrates the
challenges quite well. TFRC tries to accomplish the same throughput
as TCP, but with a smoother transmission rate. It measures the loss
and the round-trip time but follows a similar model as TCP to
determine the sending rate.
In a link with low statistical multiplexing, TCP can lead to bad
oscillations. The sending rate hits the maximum rate of a bottleneck
link, a lot of loss occurs, and then the sending rate peaks again.
For very small buffers the result is acceptable, but bigger buffers
lead to oscillations. The result is bad for networks and for
applications. To deal with large buffers on these links, a short-
term rate adaptation based on round-trip time (RTT) information is
utilized in TRFC, but this requires good short-term RTT measurements.
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TRFC works pretty well in theory. TFRC assumes the network is in
charge of the codec and that the codec can produce data at the
demanded rate. Modern video codecs inherently produce variable-
bitrate video streams based on the content being encoded, and it is
hard to produce data at exactly the desired bitrate without excessive
buffering or ugly quality changes.
What if the codec is put in charge instead of the network? The
network tells the codec the mean rate, but it does not worry about
what happens in short time scales, and the codec matches the mean
rate and does not worry whether it is over or under the rate for a
relatively short time scale. This again leads to the low statistical
multiplexing problem and leads to oscillations.
Known congestion control mechanisms work well if they can respond
quickly enough to changes and if they do not bump into the low
statistical multiplexing problem.
To avoid the low statistical multiplexing problem, techniques for
inferring link speed are needed. The work from Van Jacobson's
pathchar [37] (and successors) serve as valuable input. The idea is
to send short packet trains, to measure timing accurately, and to
infer the link speed from the relative delay. If we know the link
speed, we can avoid exceeding it. Congestion control can give us an
approximate rate, but we must not exceed link speed. This is a
hybrid between codec being in charge (most of the time) and the
network being in charge. These work well for some links, but not for
others. Wireless links where speed can change in less than a single
RTT because of fading, bitrate adaption, etc., cause problems. We
would like to have the codec and the network be in charge. However,
they both cannot be in charge at the same time.
Mark indicated that he is not entirely sure whether RTCP is suitable
for congestion control. RTCP gives feedback, but it cannot send it
often enough to avoid bumping into link speed. Circuit breakers [3],
on the other hand, do not help to give good performance on an
uncongested path. With circuit breakers, the sender measures the
loss rate and RTT, and runs with a loose "cap."
In conclusion, Mark Handley claimed that we know how to do good
congestion control, but only if congestion control is in charge, and
that's not acceptable for real-time applications. We only know how
to do good congestion control if we change the packet/sec rate and
not the packet size.
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2.2. Simulations and Measurements
This second part of the workshop was focused on the presentation and
the discussion of data gathered from simulations and real-world
measurements.
Keith Winstein started the discussion with his presentation of
measurements performed in cellular operator networks in the US [22].
The measurements indicate that the analyzed cellular networks showed
varying RTT with transient latency spikes to hundreds of
milliseconds, link speed that varies by a factor of 10 in a short
time scale, and buffers that do not drop packets until they contain
5-10 seconds of data at bottleneck link speed.
Zaheduzzaman Sarker [21] presented results from real-time video
communication in a Long Term Evolution (LTE) simulator utilizing ECN-
based packet marking and adaptation using implicit methods like
packet loss and delay. ECN marking provides ways for the network to
explicitly signal congestion and hence distributes the cost of
congestion well and helps achieve lower latency. However, although
RFC 3168 [19] was finalized in 2001, the deployment of ECN is still
lacking as investigated by Bauer, et al. [25]. A few participants
noted that they believe that the deployment of LTE networks will also
increase the deployment of ECN with the recent work on ECN for RTP
over UDP [11].
Mo Zahaty [20] discussed TFRC [12] and TFRC with weighted fairness
(MulTFRC) [4], which tunes TFRC to consider multiple flows, and
showed the impact of RTT and loss rates on the type of video quality
that can be achieved under those conditions. TFRC requires frequent
feedback, which RTCP does not provide even when considering the
extended RTP profile for RTCP-based feedback (RFC 4585 [5]). Mo
argued that application-specified weighted fairness is important but
while MulTFRC provides better performance than TFRC, it is not clear
whether the added complexity over an n-times-TFRC approach is indeed
worth the effort.
Markku Kojo shared analysis results of how real-time audio is
affected by competing TCP flows. In the experiments shown in
Figure 2 of [27], a real-time interactive audio stream had to compete
against one TCP flow and, as a comparison, against six TCP flows.
With one concurrent TCP flow, voice is impacted on startup and six
TCP flows destroy the quality of the call. Two types of losses were
analyzed, namely losses that result from a packet being dropped in
the network (e.g., due to congestion or link errors) and losses that
result from the delayed arrival of the packet (due to buffering) when
the audio packet misses the deadline for the codec to decode and play
the transmitted content. Consequently, even a moderate number of TCP
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flows typically used by browsers to retrieve content on web pages in
parallel causes irreparable harm for audio transfers. The size of
the initial window (IW) also impacts interactive real-time
communication since a larger TCP IW size (e.g., IW10 with ten
segments, as proposed in [18], instead of three) leads to a bigger
burst of packets because of the initial window transmission. Note
that the study in [24] does not necessarily lead to the same
conclusion. It claims that the increased initial window size leads
to no impact or only modest impact for buffering in the majority of
cases.
Cullen Jennings [28] presented measurement results showing
interactions between RTP and TCP flows for several widely deployed
video communication products: Apple FaceTime, Google Hangout, Cisco
Movi, and Microsoft Skype. While all tested products implemented
some form of congestion control, none of the applications did
additive increase and multiplicative decrease (AIMD). In general, it
was observable that video adapts more slowly than AIMD to changes in
available bandwidth because most codecs cannot make small increases
in sending rates when available bandwidth increases, and do not make
large decreases in sending rates when available bandwidth decreases,
in order to improve the user's experience.
Stefan Holmer [43] investigated the difference between loss-based and
delay-based congestion control algorithms. The suitability of loss-
based congestion control schemes for interactive real-time
communication systems heavily depends on buffer sizes and the
deployment of active queue management mechanisms. If most routers
are using tail-drop queuing, then loss-based congestion control
cannot fulfill the requirements of interactive real-time applications
since those flows will effectively increase the bitrate until a loss
event is identified, which only happens when the bottleneck queue is
full.
2.3. Design Aspects of Problems and Solutions
During the remaining part of the workshop, the participants discussed
design aspects of both the problem and solution spaces. The
discussions started with a presentation by Jim Gettys about problems
related to bufferbloat [31][36]. Bufferbloat is "a phenomenon in
packet-switched networks, in which excess buffering of packets causes
high latency and packet delay variation (also known as jitter), as
well as reducing the overall network throughput" [39]. A certain
amount of buffering is helpful to improve the efficiency. Not
dropping packets in the event of congestion leads to increasing
delays for interactive real-time communication.
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Packets may get buffered at various places along the end-to-end path
including in the operating system/device drivers, customer premise
equipment (such as cable modem and DSL routers), base stations, and
routers. While the understanding of too large buffers has improved
over the last few years, workshop participants were still concerned
that many equipment manufacturers and network operators do not yet
acknowledge the existence of the problem. This lack of understanding
is caused by the strong focus on throughput network performance
measurements that do not take latency into account. For example,
only recently the Federal Communications Commission (FCC) has added
latency tests to their test suites [41].
Active queue management (AQM) aims to prevent queues from growing too
large. This is accomplished by monitoring queue length and informing
the sender by dropping or marking packets to lower their transmission
rate. Random Early Detection (RED) [9] is one such AQM algorithm,
but it has not been widely deployed in routers largely because of
challenges to configure it correctly [32]. According to [23], RED
does not work with the default settings as it is "too "gentle" to
handle fast changes due to TCP slow start, when the aggregate traffic
is limited." There may also be a lack of incentives to deploy AQM
algorithms. Participants speculated about the time it takes to
update network equipment (to support AQM algorithms), considering the
different replacement cycles of these devices.
One outcome of that discussion on AQM at the workshop was a Birds of
a Feather ("BoF") meeting on "Active Queue Management and Packet
Scheduling" at IETF 87 (July 28 - August 5, 2013, Berlin, Germany).
The AQM WG [35] was chartered a few weeks later and is now designing
AQM and network infrastructure improvements to deal with bufferbloat
and related issues.
Measurement tools that allow an end user to determine the performance
of his or her network, including latency, is seen as a promising
approach to motivate network operators to upgrade their equipment and
to make use of AQM algorithms. Measurement tools would allow users
to determine how bad their networks perform and to complain to their
ISP, thereby creating a market force. As to what the right
performance measurement metrics are, it was noted that the intent of
the IETF IP Performance Metrics (IPPM) working group [33] was to
develop such metrics to qualify networks. That work may have begun
before its time, but there have been recent attempts to revisit the
measurement work and an effort by the FCC has gotten a lot of
attention recently (see [7] and [42]).
Matt Mathis and others argued that the traffic of throughput-
maximizing and delay-minimizing applications need to be in separate
queues (segregated queuing). Requiring segregated queues assumes you
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are sharing the network with other greedy traffic.
Quality-of-Service (QoS) signaling is a way to deploy segregated
queuing, but there are several simpler alternatives, such as
Stochastic Fair Queuing [38]. The Controlled Delay (CoDel) AQM
algorithm [6] can also be used in combination with stochastic fair
queuing. Note that queue segregation is not necessary for every
router to implement; using it at the edge of a network where
bottleneck links are located is already sufficient.
It was noted that current interactive voice usage over the Internet
works most of the time satisfactorily. In typical networks, the
reason voice works is because networks are underloaded. As long as
there is idle capacity and the queue is empty when packets arrive,
traffic does not need to be separated into distinct queues. Further
explanations were offered as to why many networks work surprisingly
well: Low Extra Delay Background Transport (LEDBAT) [8] is used for
the download of software updates, voice traffic contributes only a
small percentage of the overall Internet traffic, and users employ
"human protocols" (e.g., parents asking their kids to get off the
network during the time of a conference call).
Cullen Jennings raised a concern that although interactive voice may
be functional without a congestion control mechanism, the potentially
large uptake of interactive video spurred on by Real-Time
Communications on the Web (RTCWEB) could create substantially more
significant problems. In the class of space where voice is currently
working, video may fail. Ted Hardie countered by saying that RTCWEB
is trying to replace existing proprietary technologies. It may ramp
up the amount of use we are expecting, but it is not doing much that
was not being done by Adobe Flash or Skype. RTCWEB is not a totally
novel context of Internet usage. Magnus Westerlund added that RTCWEB
might be the driver for the moment, but web browsers are not the only
consumers of such congestion control algorithm.
Furthermore, Ted Hardie noted that applications will not produce
media streams that grow to 10 Mbps because their sending rate is auto
rate limited by the production of the video. He suggested to ask
ourselves if we are trying to get TCP to be friendly to media streams
that are already rate limited or if we are asking media streams that
are already rate limited to be TCP friendly. To quote Andrew
McGregor: "It's really not good to be TCP friendly because it's not
going to return the favor." If the desired properties we want are no
starvation, fairness, and effective goodput for the offered loads,
are we only willing to consider changes in RTP control, or are we
willing to consider changes in TCP congestion control?
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This led to a discussion about whether the development of a
congestion control algorithm for interactive real-time applications
provides any value if network equipment suffers from bufferbloat. Is
there something that can be done today to help interactive real-time
media or do we have to wait to get the network updated first?
Replacing home routers and updating routers with modern AQM
algorithms was seen as a longer-term effort. Also, the time scale
for changing TCP's congestion control is on the same time scale as
deploying ECN [19]. Colin Perkins noted that we cannot change TCP
quickly; the way TCP is being used is changing quickly, and we can
impact the way TCP is used. When TCP is used for file transfer, it
will send data as fast as it can, but when TCP is used for
WebSockets, the dynamics are different. WebSockets and SPDY are
clearly changing the behavior of TCP. Also, Netflix-style video-
streaming applications are huge users of TCP and those applications
can change rather quickly. Matt Mathis added that real-time
videoconferencing almost always produces video streams at a lower
bitrate than downloading equivalent-sized stored video using best-
effort file-sharing.
Bill Ver Steeg suggested to consider three different deployment
environments, namely:
1. Flows competing with flows from the host ("self-inflicted queuing
delay")
2. Flows competing with flows in the same subnetwork (e.g., home
network)
3. Flows competing with flows from other networks (e.g., traffic
from different households that utilize the same DSL provider)
The narrowest problem domain that makes sense is to avoid self-
inflicted queuing delay. Michael Welzl indicated that this requires
an information exchange (called flow-state exchange) inside a browser
(at the level of the same host or even beyond, as described in [29])
to synchronize congestion control of different audio, video, and data
flows. Although it would provide great benefits if one could share
information about a bottleneck with all the flows sharing that
bottleneck, this is considered challenging even within a single host.
John Leslie [30] also noted: "We're acting as if we believe
congestion will magically be solved by a new transport algorithm. It
won't." Instead, an interaction between the network layer, transport
layer, and the application layer is needed whereby the application
layer is the only practical place to balance what piece(s) to
constrain to lower bandwidths. All flows relating to a user session
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should have a common congestion controller. For many applications,
audio is much more critical than video. In those cases, the video
may back off, but the audio transmission remains unchanged.
Mo Zanaty pointed to the importance of the media start-up behavior,
which is an area where the exchange of real-time interactive media is
different from a TCP-based file transfer. The instantaneous
experience in the first part of a video call is highly determinative
of people's perception of the call quality. Vendors are using vague
heuristics, for example, data from the last call to figure out what
to do on the next call. Lars Eggert highlighted that the start-up
behavior of an application affects ongoing performance of other flows
if, for example, an application blasts at line rate at the beginning
of a video stream. You need to start slow enough to not cause
congestion to others. Randell Jesup argued that for an interactive
real-time video application, you really need to have most of your
bandwidth right away. Colin Perkins agreed and added that on startup
you need good quality video quickly, but perhaps not as quickly as
voice. The requirements are likely going to be different from audio
to video and maybe even vary between different applications. Various
protocol exchanges take place before media is exchanged between
endpoints (such as Session Traversal Utilities for NAT (STUN) packets
[13] as part of the Interactive Connectivity Establishment (ICE) [15]
or a Datagram Transport Layer Security (DTLS) handshake [14]) and may
be used to obtain simple start-up measurements.
The group agreed that it is feasible to design a congestion control
algorithm that works on mostly idle networks. In the view of the
participants, upgrades of the network infrastructure can happen in
parallel. This view was later confirmed at the RTP Media Congestion
Avoidance Techniques (RMCAT) BoF meeting at IETF 84 (July 29 - August
3, 2012, Vancouver, BC, Canada) that led to the formation of the
RMCAT working group [34].
3. Recommendations
The participants suggested to explore two primary solution tracks:
changes to network infrastructure and the development of algorithms
to avoid self-inflicted queuing. These are discussed below. A third
approach recommended by some participants was to change the way TCP
is used in browsers and other HTTP-based applications. For example,
by not opening too many concurrent TCP connections, and by improving
the interaction with other non-real-time applications (such as video
streaming and file sharing), additional improvements can be made.
The work on HTTP 2.0 with SPDY [16] is already a step in the right
direction since SPDY makes use of a more aggressive form of
multiplexing instead of opening a larger number of TCP connections.
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3.1. Changes to Network Infrastructure
As for all other traffic on the network, better data plane
infrastructure improves the perceived quality of the best-effort
service that the Internet provides for RTCWEB flows. The IETF has
already developed several technologies that would be of immediate
usefulness if they were to be deployed. The workshop participants
expressed the hope that due to the volume and importance of RTCWEB
traffic, some of these technologies might finally see widespread use.
The first and by far most important improvement is traffic
segregation: the ability to use different queues for different
traffic types. Specifically, jitter- and delay-sensitive protocols
would benefit from being in different queues from throughput-
maximizing protocols. It is not possible for a single queue/AQM to
be optimal for both.
Furthermore, ECN allows routers along the end-to-end path to signal
the onset of congestion and allows applications to respond early,
avoiding losses and keeping queue sizes short and, therefore,
end-to-end delay low. ECN is implemented on some end system stacks
and routers, but is frequently not enabled. The participants
expressed the importance of increasing the deployment of ECN, even if
used initially only in closed environments, such as data centers (as
with Data Center TCP (DCTCP) [26]).
Different mechanisms have been developed to facilitate traffic
segregation. Differentiated Services [10] is one possibility in this
space. If applications start to mark outgoing traffic appropriately
and routers segregate traffic accordingly, browsers could more
directly control the relative importance of their various flows and
avoid self-competition. Compared to ECN, however, DiffServ is far
more difficult to deploy meaningfully end to end, especially given
that Differentiated Services Code Points (DSCPs) have no defined end-
to-end meaning and packets can be re-marked.
QoS signaling together with resource reservation facilities would
enable a fine-grained and flexible way to indicate resource needs to
network elements, but it is also by far the most heavyweight
proposal, and unlikely to be viable in the global Internet. However,
as mentioned in Section 2.3, QoS signaling is not the only way to
accomplish traffic segregation. Further investigations regarding
stochastic fair queuing and new AQM algorithms are seen as desirable.
In any case, network infrastructure updates will take time,
particularly if the interest of the involved stakeholders is not
aligned (as is often the case for network operators when dealing with
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over-the-top real-time traffic). It is, therefore, imperative that
RTCWEB congestion control provides adequate improvement in the
absence of any of the aforementioned schemes.
3.2. Avoiding Self-Inflicted Queuing
This approach tries to ensure that the network does not suffer from
congestion collapse and that one data flow from a single host does
not harm another data flow from the same host. A single congestion
manager within the end host or the browser could help to coordinate
various congestion control activities and to ensure a more
coordinated approach between different applications and different
flows.
The following design and testing aspects were considered relevant to
this approach:
Reacting to All Congestion Signals:
To initiate the congestion control process, it is important to
detect congestion in the communication path. Congestion can be
detected using either an explicit mechanism or an implicit
mechanism. An explicit mechanism involves direct congestion
signaling usually from the congested network node, such as ECN.
In case of an implicit mechanism, packet-loss events or observed
delay increases are used as an indication for congestion. These
measurements can also be made available in a variety of different
protocols, such as RTCP reports or transport protocols. It is
recommended for applications to take all available congestion
signals into account and to couple the congestion control
algorithm, the codec, and the application so that better
information exchange between these components is possible since
there are constraints on how quickly a codec can adapt to a
specific sending rate.
Delay- and Loss-Based Algorithms:
The main goal of designing a congestion control algorithm for
real-time conversational media is to achieve low latency.
Explicit congestion signals provide the most reliable way for
applications to react, but due to the lack of ECN deployment,
delay-based algorithms are needed. Since there is large delay
variation in wireless networks (even in a non-congested network),
the workshop participants recommended that more research should be
done to better understand non-congestion-related delay variation
in the network. General consensus among the workshop participants
was that latency-based congestion control algorithms are needed
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due to the lack of loss indications caused by large buffers, even
though loss-based techniques dominate latency-based techniques
when the two are competing for bandwidth.
Algorithm Evaluation:
The Internet consists of heterogeneous networks, which include
misconfigured and unmanaged network nodes. Bandwidth and latency
vary a lot. Different services deployed using RTP/UDP have
different requirements in terms of media quality. A congestion
control algorithm needs to perform well not only in simulators but
also in the deployed Internet. To achieve this, it is recommended
to test the algorithms with real-world loss and delay figures to
ensure that the desired audio/video rates are attainable using the
proposed algorithms for the desired services.
Media Characteristics:
Interactive real-time voice and video data are inherently
variable. Usually the content of the media and service
requirements dictate the media coding. The codec may be bursty
and not all frames are equally important (e.g., I-frames are more
important than P-frames). Thus, codecs have limited room for
adaptation. Congestion control for audio and video codecs is,
therefore, different from congestion control applied to bulk file
transfers where buffering is not a problem and the transmission
rate can be changed to any rate suitable for the congestion
control algorithm. In the workshop, these limitations were
brought up and the workshop participants recommended that a
congestion controller needs to be aware of these constraints.
However, further investigation is needed to decide what
information needs to be exchanged between a codec and the
congestion manager.
Start-up Behavior:
The start-up media quality is very important for real-time
interactive applications and for user-perceived application
performance. The start-up behavior of these is also different
from other traffic. By nature, real-time interactive
communication applications want to provide a smooth user
experience and maintain the best media quality possible to ease
the interaction. While it may be desirable from a user-experience
point of view to immediately start streaming video with high-
definition quality and audio of a wideband codec, this will have
impacts on the bandwidth of the already ongoing flows. As such,
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it would be ideal to start slow enough to avoid causing excessive
congestion to other flows but fast enough to offer a good user
experience. The sweet spot, however, yet has to be found.
4. Security Considerations
Two position papers focused on security, but these papers were not
discussed during the workshop. As such, nothing beyond the material
contained in those position papers can be reported.
5. Acknowledgments
We would like to thank the participants and the paper authors of the
position papers for their input.
Additionally, we would like to thank the following persons for their
review comments: Michael Welzl, John Leslie, Mirja Kuehlewind, Matt
Mathis, Mary Barnes, Spencer Dawkins, Dave Thaler, and Alissa Cooper.
6. Informative References
[1] Eggert, L. and G. Fairhurst, "Unicast UDP Usage Guidelines for
Application Designers", BCP 145, RFC 5405, November 2008.
[2] Floyd, S., "Congestion Control Principles", BCP 41, RFC 2914,
September 2000.
[3] Perkins, C. and V. Singh, "Multimedia Congestion Control:
Circuit Breakers for Unicast RTP Sessions", Work in Progress,
February 2014.
[4] Welzl, M., Damjanovic, D., and S. Gjessing, "MulTFRC: TFRC with
weighted fairness", Work in Progress, July 2010.
[5] Ott, J., Wenger, S., Sato, N., Burmeister, C., and J. Rey,
"Extended RTP Profile for Real-time Transport Control Protocol
(RTCP)-Based Feedback (RTP/AVPF)", RFC 4585, July 2006.
[6] Nichols, K. and V. Jacobson, "Controlled Delay Active Queue
Management", Work in Progress, March 2014.
[7] Schulzrinne, H., Johnston, W., and J. Miller, "Large-Scale
Measurement of Broadband Performance: Use Cases, Architecture
and Protocol Requirements", Work in Progress, September 2012.
[8] Shalunov, S., Hazel, G., Iyengar, J., and M. Kuehlewind, "Low
Extra Delay Background Transport (LEDBAT)", RFC 6817, December
2012.
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RFC 7295 Congestion Control Workshop Report July 2014
[9] 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.
[10] Blake, S., Black, D., Carlson, M., Davies, E., Wang, Z., and W.
Weiss, "An Architecture for Differentiated Services", RFC 2475,
December 1998.
[11] Westerlund, M., Johansson, I., Perkins, C., O'Hanlon, P., and
K. Carlberg, "Explicit Congestion Notification (ECN) for RTP
over UDP", RFC 6679, August 2012.
[12] Floyd, S., Handley, M., Padhye, J., and J. Widmer, "TCP
Friendly Rate Control (TFRC): Protocol Specification", RFC
5348, September 2008.
[13] Rosenberg, J., Mahy, R., Matthews, P., and D. Wing, "Session
Traversal Utilities for NAT (STUN)", RFC 5389, October 2008.
[14] Rescorla, E. and N. Modadugu, "Datagram Transport Layer
Security Version 1.2", RFC 6347, January 2012.
[15] Rosenberg, J., "Interactive Connectivity Establishment (ICE): A
Protocol for Network Address Translator (NAT) Traversal for
Offer/Answer Protocols", RFC 5245, April 2010.
[16] Belshe, M., Peon, R., and M. Thomson, "Hypertext Transfer
Protocol version 2", Work in Progress, June 2014.
[17] Floyd, S. and J. Kempf, "IAB Concerns Regarding Congestion
Control for Voice Traffic in the Internet", RFC 3714, March
2004.
[18] Chu, J., Dukkipati, N., Cheng, Y., and M. Mathis, "Increasing
TCP's Initial Window", RFC 6928, April 2013.
[19] Ramakrishnan, K., Floyd, S., and D. Black, "The Addition of
Explicit Congestion Notification (ECN) to IP", RFC 3168,
September 2001.
[20] Zanaty, M., "Fairness Considerations for Congestion Control for
Interactive Real-Time Communication (IRTC)", IAB/ RTF Workshop
on Congestion Control for Interactive Real-Time Communication,
July 2012.
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RFC 7295 Congestion Control Workshop Report July 2014
[21] Sarker, Z. and I. Johansson, "Improving the Interactive
Real-Time Video Communication with Network Provided Congestion
Notification", IAB/IRTF Workshop on Congestion Control for
Interactive Real-Time Communication, July 2012.
[22] Winstein, K., Sivaraman, A., and H. Balakrishnan, "Congestion
Control for Interactive Real-Time Flows on Today's Internet",
IAB/IRTF Workshop on Congestion Control for Interactive
Real-Time Communication, July 2012.
[23] Jarvinen, I., Ding, A., Nyrhinen, A., and M. Kojo, "Harsh RED:
Improving RED for Limited Aggregate Traffic", In Proceedings of
the 26th IEEE International Conference on Advanced Information
Networking and Applications (AINA 2012), March 2012.
[24] Allman, M., "Comments on Bufferbloat", In ACM SIGCOMM Computer
Communication Review, Volume 43, Issue 1, pp. 30-37, January
2013, <http://dl.acm.org/citation.cfm?doid=2427036.2427041>.
[25] Bauer, S., Beverly, R., and A. Berger, "Measuring the state of
ECN readiness in servers, clients,and routers", In Proceedings
of the 2011 ACM SIGCOMM conference on Internet measurement
conference (IMC '11), New York, NY, USA, pp. 171-180, February
2011, <http://dl.acm.org/citation.cfm?doid=2068816.2068833>.
[26] Bauer, S., Greenberg, A., Maltz, D., Padhye, J., Patel, P.,
Prabhakar, B., Sengupta, S., and M. Sridharan, "Data center TCP
(DCTCP)", In Proceedings of the ACM SIGCOMM 2010 conference
(SIGCOMM '10), New York, NY, USA, pp. 63-74, August 2010,
<http://dl.acm.org/citation.cfm?doid=1851182.1851192>.
[27] Jarvinen, I., Chemmagate, B., Daniel, L., Ding, A., Kojo, M.,
and M. Isomaki, "Impact of TCP on Interactive Real- Time
Communication", IAB/IRTF Workshop on Congestion Control for
Interactive Real-Time Communication, July 2012.
[28] Jennings, C., Nandakumar, S., and H. Phan, "Vendors Considered
Harmfull", IAB/IRTF Workshop on Congestion Control for
Interactive Real-Time Communication, July 2012.
[29] Welzl, M., "One control to rule them all", IAB/IRTF Workshop on
Congestion Control for Interactive Real-Time Communication,
July 2012.
[30] Leslie, J., "There is No Magic Transport Wand", IAB/IRTF
Workshop on Congestion Control for Interactive Real-Time
Communication, July 2012.
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RFC 7295 Congestion Control Workshop Report July 2014
[31] Gettys, J. and J. Gettys, "Bufferbloat: Dark Buffers in the
Internet", IEEE Internet Computing, Volume 15, Issue 3, pp.
95-96, May/June 2011.
[32] Feng, W., Shin, K., Kandlur, D., and D. Saha, "The BLUE active
queue management algorithms", In IEEE/ACM Transactions on
Networking, Volume 10, Issue 4, pp. 513-528, August 2002.
[33] IETF, "IP Performance Metrics (ippm) Working Group", January
2012, <http://datatracker.ietf.org/wg/ippm/charter/>.
[34] IETF, "RTP Media Congestion Avoidance Techniques (rmcat)
Working Group", January 2012,
<http://datatracker.ietf.org/wg/rmcat/charter/>.
[35] IETF, "Active Queue Management and Packet Scheduling (aqm)
Working Group", September 2013,
<http://datatracker.ietf.org/wg/aqm/charter/>.
[36] Gettys, J. and K. Nichols, "Bufferbloat: Dark Buffers in the
Internet", Communications of the ACM, Vol. 55, No. 1, pp.
57-65, January 2012,
<http://cacm.acm.org/magazines/2012/1/144810-bufferbloat/>.
[37] Jacobson, V., "pathchar - a tool to infer characteristics of
Internet paths", Presented at the Mathematical Sciences
Research Institute, April 1997,
<ftp://ftp.ee.lbl.gov/pathchar/msri-talk.pdf>.
[38] McKenney, P., "Stochastic Fairness Queuing", In IEEE INFOCOM'90
Proceedings, Volume 2, pp. 733-740, June 1990.
[39] Wikipedia, "Bufferbloat", May 2014, <http://en.wikipedia.org/w/
index.php?title=Bufferbloat&oldid=608805474>.
[40] Wikipedia, "Video compression picture types", March 2014,
<http://en.wikipedia.org/w/index.php?
title=Video_compression_picture_types&oldid=602183340>.
[41] FCC, "Methodology - Measuring Broadband America July Report
2012", July 2012, <http://www.fcc.gov/
measuring-broadband-america/2012/methodology-july-report-2012>.
[42] IETF, "lmap -- Large Scale Measurement of Access network
Performance Mailing List", 2012,
<https://www.ietf.org/mailman/listinfo/lmap>.
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RFC 7295 Congestion Control Workshop Report July 2014
[43] Holmer, S., "On Fairness, Delay and Signaling of Different
Approaches to Real-time Congestion Control", IAB/IRTF Workshop
on Congestion Control for Interactive Real-Time Communication,
July 2012.
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Appendix A. Program Committee
This workshop was organized by Harald Alvestrand, Bernard Aboba, Mary
Barnes, Gonzalo Camarillo, Spencer Dawkins, Lars Eggert, Matthew
Ford, Randell Jesup, Cullen Jennings, Jon Peterson, Robert Sparks,
and Hannes Tschofenig.
Appendix B. Workshop Material
o Main Workshop Page:
http://www.iab.org/activities/workshops/cc-workshop/
o Position Papers:
http://www.iab.org/activities/workshops/cc-workshop/papers/
o Slides:
http://www.iab.org/activities/workshops/cc-workshop/slides/
Appendix C. Accepted Position Papers
1. "One control to rule them all" by Michael Welzl
2. "Congestion Avoidance Through Deterministic" by Pier Luca
Montessoro, Riccardo Bernardini, Franco Blanchini, Daniele
Casagrande, Mirko Loghi, and Stefan Wieser
3. "Congestion Control in Real Time Media - Context" by Harald
Alvestrand
4. "Improving the Interactive Real-Time Video Communication with
Network Provided Congestion Notification" by ANM Zaheduzzaman
Sarker and Ingemar Johansson
5. "Multiparty Requirements in Congestion Control for Real-Time
Interactive Media" by Magnus Westerlund
6. "On Fairness, Delay and Signaling of Different Approaches to
Real-time Congestion Control" by Stefan Holmer
7. "RTP Congestion Control and RTCWEB Application Feedback" by Ted
Hardie
8. "Issues with Using Packet Delays and Inter-arrival Times for
Inference of Internet Congestion" by Wesley M. Eddy
9. "Impact of TCP on Interactive Real-Time Communication" by Ilpo
Jarvinen, Binoy Chemmagate, Laila Daniel, Aaron Yi Ding, Markku
Kojo, and Markus Isomaki
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10. "Security Concerns For RTCWEB Congestion Control" by Dan York
11. "Vendors Considered Harmfull" by Cullen Jennings, Suhas
Nandakumar, and Hein Phan
12. "Network-Assisted Dynamic Adaptation" by Xiaoqing Zhu and Rong
Pan
13. "Congestion Control for Interactive Real-Time Applications" by
Sanjeev Mehrotra and Jin Li
14. "There is No Magic Transport Wand" by John Leslie
15. "Towards Adaptive Congestion Management for Interactive Real-
Time Communications" by Dirk Kutscher and Miriam Kuehlewind
16. "Enlarge the pre-congestion spectrum usage?" by Xavier Marjou
and Emile Stephan
17. "Congestion control for users who don't have first-class
internet access" by Maire Reavy
18. "Realtime Congestion Challenges" by Randell Jesup
19. "Congestion Control for Interactive Media: Control Loops & APIs"
by Varun Singh, Joerg Ott, and Colin Perkins
20. "Some Notes on Threat Modelling Congestion Management" by Eric
Rescorla
21. "Timely Detection of Lost Packets" by Ali C. Begen
22. "Congestion Control Considerations for Data Channels" by Michael
Tuexen
23. "Position paper on CC for Interactive RT" by Matt Mathis
24. "Overall Considerations for Congestion Control" by Mo Zanaty,
Bill VerSteeg, Bent Christensen, David Benham, and Allyn Romanow
25. "Fairness Considerations for Congestion Control" by Mo Zanaty
26. "Media is not Data: The Meaning of Fairness for Competing
Multimedia Flows" by Timothy B. Terriberry
27. "Thoughts on Real-Time Congestion Control" by Murari Sridharan
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28. "Congestion Control for Interactive Real-Time Flows on Today's
Internet" by Keith Winstein, Anirudh Sivaraman, and Hari
Balakrishnan
29. "Congestion Control Principles for CoAP" by Carsten Bormann and
Klaus Hartke
30. "Erasure Coding and Congestion Control for Interactive Real-Time
Communication" by Pierre-Ugo Tournoux, Tuan Tran Thai, Emmanuel
Lochin, Jerome Lacan, and Vincent Roca
31. "Video Conferencing Specific Considerations for RTP Congestion
Control" by Stephen Botzko and Mary Barnes
32. "The Internet is Broken, and How to Fix It" by Jim Gettys
33. "Deployment Considerations for Congestion Control in Real-Time
Interactive Media Systems" by Jari Arkko
Appendix D. Workshop Participants
We would like to thank the following workshop participants for
attending the workshop:
o Mat Ford
o Bernard Aboba
o Alissa Cooper
o Mary Barnes
o Lars Eggert
o Harald Alvestrand
o Gonzalo Camarillo
o Robert Sparks
o Cullen Jennings
o Dirk Kutscher
o Carsten Bormann
o Michael Welzl
o Magnus Westerlund
o Colin Perkins
o Murari Sridharan
o Klaus Hartke
o Pier Luca Montessoro
o Xavier Marjou
o Vincent Roca
o Wes Eddy
o Ali C. Begen
o Mo Zanaty
o Jin Li
o Dave Thaler
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o Bob Briscoe
o Barry Leiba
o Jari Arkko
o Stewart Bryant
o Martin Stiemerling
o Russ Housley
o Marc Blanchet
o Zaheduzzaman Sarker
o Xiaoqing Zhu
o Randell Jesup
o Eric Rescorla
o Suhas Nandakumar
o Hannes Tschofenig
o Bill VerSteeg
o Sean Turner
o Keith Winstein
o Jon Peterson
o Maire Reavy
o Michael Tuexen
o Stefan Holmer
o Joerg Ott
o Timothy Terriberry
o Benoit Claise
o Ted Hardie
o Stephen Botzko
o Matt Mathis
o David Benham
o Jim Gettys
o Spencer Dawkins
o Sanjeev Mehrotra
o Adrian Farrel
o Greg White
o Markku Kojo
We also had remote participants, namely:
o Emmanuel Lochin
o Mark Handley
o Anirudh Sivaraman
o John Leslie
o Varun Singh
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Authors' Addresses
Hannes Tschofenig
Hall, Tirol 6060
Austria
EMail: [email protected]
URI: http://www.tschofenig.priv.at
Lars Eggert
Sonnenallee 1
Kirchheim 85551
Germany
Phone: +49 151 12055791
EMail: [email protected]
URI: http://eggert.org/
Zaheduzzaman Sarker
Lulea SE-971 28
Sweden
Phone: +46 10 717 37 43
EMail: [email protected]
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