Coupled congestion control for RTP media
draft-welzl-rmcat-coupled-cc-00
The information below is for an old version of the document.
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| Author | Michael Welzl | ||
| Last updated | 2013-01-19 | ||
| Replaced by | draft-ietf-rmcat-coupled-cc, RFC 8699 | ||
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draft-welzl-rmcat-coupled-cc-00
RTP Media Congestion Avoidance M. Welzl
Techniques (rmcat) University of Oslo
Internet-Draft January 19, 2013
Intended status: Experimental
Expires: July 23, 2013
Coupled congestion control for RTP media
draft-welzl-rmcat-coupled-cc-00
Abstract
When multiple congestion controlled RTP sessions traverse the same
network bottleneck, it can be beneficial to combine their controls
such that the total on-the-wire behavior is improved. This document
describes such a method for flows that have the same sender, in a way
that is as flexible and simple as possible while minimizing the
amount of changes needed to existing RTP applications.
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
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and may be updated, replaced, or obsoleted by other documents at any
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material or to cite them other than as "work in progress."
This Internet-Draft will expire on July 23, 2013.
Copyright Notice
Copyright (c) 2013 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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publication of this document. Please review these documents
carefully, as they describe your rights and restrictions with respect
to this document. Code Components extracted from this document must
include Simplified BSD License text as described in Section 4.e of
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the Trust Legal Provisions and are provided without warranty as
described in the Simplified BSD License.
1. Introduction
When there is enough data to send, a congestion controller must
increase its sending rate until the path's available capacity has
been reached; depending on the controller, sometimes the rate is
increased further, until packets are ECN-marked or dropped. In the
public Internet, this is currently the only way to get any feedback
from the network that can be used as an indication of congestion.
This process inevitably creates undesirable queuing delay -- an
effect that is amplified when multiple congestion controlled
connections traverse the same network bottleneck. When such
connections originate from the same host, it would therefore be ideal
to use only one single sender-side congestion controller which
determines the overall allowed sending rate, and then use a local
scheduler to assign a proportion of this rate to each RTP session.
This way, priorities could also be implemented quite easily, as a
function of the scheduler; honoring user-specified priorities is, for
example, required by rtcweb [rtcweb-usecases].
The Congestion Manager (CM) [RFC3124] provides a single congestion
controller with a scheduling function just as described above. It
is, however, hard to implement because it requires an additional
congestion controller and removes all per-connection congestion
control functionality, which is quite a significant change to
existing RTP based applications. This document presents a method
that is easier to implement than the CM and also requires less
significant changes to existing RTP based applications. It attempts
to roughly approximate the CM behavior by sharing information between
existing congestion controllers, akin to "Ensemble Sharing" in
[RFC2140].
2. Definitions
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 RFC 2119 [RFC2119].
Available Bandwidth:
The available bandwidth is the nominal link capacity minus the
amount of traffic that traversed the link during a certain time
interval, divided by that time interval.
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Bottleneck:
The first link with the smallest available bandwidth along the
path between a sender and receiver.
Flow:
A flow is the entity that congestion control is operating on.
It could, for example, be a transport layer connection, an RTP
session, or a subsession that is multiplexed onto a single RTP
session together with other subsessions.
Flow Group Identifier (FGI):
A unique identifier for each subset of flows that is limited by
a common bottleneck.
Flow State Exchange (FSE):
The entity which maintains information that is exchanged
between flows.
Flow Group (FG):
A group of flows having the same FGI.
Shared Bottleneck Detection (SBD):
The entity that determines which flows traverse the same
bottleneck in the network, or the process of doing so.
3. Limitations
Sender-side only:
Coupled congestion control as described here only operates
inside a single host on the sender side. This is because,
irrespective of where the major decisions for congestion
control are taken, the sender of a flow needs to eventually
decide the transmission rate. Additionally, the necessary
information about how much data an application can currently
send on a flow is typically only available at the sender side,
making the sender an obvious choice for placement of the
elements and mechanisms described here. It is recognized that
flows that have different senders but the same receiver, or
different senders and different receivers can also share a
bottleneck; such scenarios have been omitted for simplicity,
and could be incorporated in future versions of this document.
Note that limiting the flows on which coupled congestion
control operates merely limits the benefits derived from the
mechanism.
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Shared bottlenecks do not change quickly:
As per the definition above, a bottleneck depends on cross
traffic, and since such traffic can heavily fluctuate,
bottlenecks can change at a high frequency (e.g., there can be
oscillation between two or more links). This means that, when
flows are partially routed along different paths, they may
quickly change between sharing and not sharing a bottleneck.
For simplicity, here it is assumed that a shared bottleneck is
valid for a time interval that is significantly longer than the
interval at which congestion controllers operate. Note that,
for the only SBD mechanism defined in this document
(multiplexing on the same five-tuple), the notion of a shared
bottleneck stays correct even in the presence of fast traffic
fluctuations: since all flows that are assumed to share a
bottleneck are routed in the same way, if the bottleneck
changes, it will still be shared.
4. Architectural overview
Figure 1 shows the elements of the architecture for coupled
congestion control: the Flow State Exchange (FSE), Shared Bottleneck
Detection (SBD) and Flows. The FSE is a storage element. It is
passive in that it does not actively initiate communication with
flows and the SBD; its only active role is internal state maintenance
(e.g., an implementation could use soft state to remove a flow's data
after long periods of inactivity). Every time a flow's congestion
control mechanism would normally update its sending rate, the flow
instead updates information in the FSE and performs a query on the
FSE, leading to a sending rate that is often different from what the
congestion controller originally determined. Using information
about/from the currently active flows, SBD updates the FSE with the
correct Flow Group Identifiers (FGIs).
------- <--- Flow 1
| FSE | <--- Flow 2 ..
------- <--- .. Flow N
^
| |
------- |
| SBD | <-------|
-------
Figure 1: Coupled congestion control architecture
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Since everything shown in Figure 1 is assumed to operate on a single
host (the sender) only, this document only describes aspects that
have an influence on the resulting on-the-wire behavior. It does,
for instance, not define how many bits must be used to represent
FGIs, or in which way the entities communicate. Implementations can
take various forms: for instance, all the elements in the figure
could be implemented within a single application, thereby operating
on flows generated by that application only. Another alternative
could be to implement both the FSE and SBD together in a separate
process which different applications communicate with via some form
of Inter-Process Communication (IPC). Such an implementation would
extend the scope to flows generated by multiple applications. The
FSE and SBD could also be included in the Operating System kernel.
5. Roles
This section gives an overview of the roles of the elements of
coupled congestion control, and provides an example of how coupled
congestion control can operate.
5.1. SBD
SBD uses knowledge about the flows to determine which flows belong in
the same Flow Group (FG), and assigns FGIs accordingly. This
knowledge can be derived from measurements, by considering
correlations among measured delay and loss as an indication of a
shared bottleneck, or it can be based on the simple assumption that
packets sharing the same five-tuple (IP source and destination
address, protocol, and transport layer port number pair) are
typically routed in the same way. The latter method is the only one
specified in this document: SBD MUST consider all flows that use the
same five-tuple to belong to the same FG. This classification
applies to certain tunnels, or RTP flows that are multiplexed over
one transport (cf. [transport-multiplex]). In one way or another,
such multiplexing will probably be recommended for use with rtcweb
[rtcweb-rtp-usage]. Port numbers are needed as part of the
classification due to mechanisms like Equal-Cost Multi-Path (ECMP)
routing which use different paths for packets towards the same
destination, but are typically configured to keep packets from the
same transport connection on the same path.
5.2. FSE
The FSE contains a list of all flows that have registered with it.
For each flow, it stores:
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o a unique flow number to identify the flow
o the FGI of the FG that it belongs to (based on the definitions in
this document, a flow has only one bottleneck, and can therefore
be in only one FG)
o a priority P, which here is assumed to be represented as a
floating point number in the range from 0.1 (unimportant) to 1
(very important). A negative value is used to indicate that a
flow has terminated.
o The calculated rate CR, i.e. the rate that was most recently
calculated by the flow's congestion controller.
o The desired rate DR. This can be smaller than the calculated rate
if the application feeding into the flow has less data to send
than the congestion controller would allow. In case of a greedy
flow, DR must be set to CR. A DR value that is larger than CR
indicates that the flow has taken leftover bandwidth from a non-
greedy flow.
o S_CR, the sum of the calculated rates of all flows in the same FG
(including the flow itself), as seen by the flow during its last
rate update.
The information listed here is enough to implement the sample flow
algorithm given below. FSE implementations could easily be extended
to store, e.g., a flow's current sending rate for statistics
gathering or future potential optimizations.
5.3. Flows
Flows register themselves with SBD and FSE when they start,
deregister from the FSE when they stop, and carry out an UPDATE
function call every time their congestion controller calculates a new
sending rate. Via UPDATE, they provide the newly calculated rate and
the desired rate (less than the calculated rate in case of non-greedy
flows, the same otherwise). UPDATE returns a rate that should be
used instead of the rate that the congestion controller has
determined.
Below, an example algorithm is described. While other algorithms
could be used instead, the same algorithm must be applied to all
flows. The way the algorithm is described here, the operations are
carried out by the flows, but they are the same for all flows. This
means that the algorithm could, for example, be implemented in a
library that provides registration, deregistration functions and the
UPDATE function. To minimize the number of changes to existing
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applications, one could, however, also embed this functionality in
the FSE element.
5.3.1. Example algorithm
(1) When a flow starts, it registers itself with SBD and the FSE.
CR and DR are initialized with the congestion controller's
initial rate. SBD will assign the correct FGI. When a flow is
assigned an FGI, its S_CR is initialized to be the sum of the
calculated rates of all the flows in its FG.
(2) When a flow stops, it sets its DR to 0 and negates P.
(3) Every time the flow's congestion controller determines a new
sending rate new_CR, assuming the flow's new desired rate new_DR
to be "infinity" in case of a greedy flow with an unknown
maximum rate, the flow calls UPDATE, which carries out the
following tasks:
(a) For all the flows in its FG (including itself), it
calculates the sum of all the absolute values of all
priorities, S_P, the sum of all desired rates, S_DR, and
the sum of all the calculated rates, new_S_CR.
(b) It updates CR if new_CR is smaller than the already stored
CR value, or if new_S_CR is smaller or equal to the flow's
stored S_CR value. This restriction on updating CR ensures
that only one flow can make S_CR increase at a time.
(c) It updates new_S_CR using its own updated CR, and updates
S_CR with new_S_CR.
(d) It subtracts DR from S_DR, updates DR to min(new_DR, CR),
and adds the updated DR to S_DR.
(e) It initializes the total leftover rate TLO to 0. Then, for
every other flow i in its FG that has DR(i) < CR(i), it
calculates the leftover rate as abs(P(i))/S_P * S_CR -
DR(i), adds the flow's leftover rate to TLO, and sets DR(i)
to CR(i). This makes flow i look like a greedy flow and
ensures that the leftover rate can only once be taken from
it. Finally, if P(i) is negative, it removes flow i's
entry from the FSE.
(f) It calculates the new sending rate as min(new_DR, P/S_P *
S_CR + TLO). This gives the flow the correct share of the
bandwidth based on its priority, applies an upper bound in
case of an application-limited flow, and adds any
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potentially leftover bandwidth from non-greedy flows.
(g) If the flow's new sending rate is greater than DR, then it
updates DR with the flow's new sending rate.
The goals of the flow algorithm are to achieve prioritization,
improve network utilization in the face of non-greedy flows, and
impose limits on the increase behavior such that the negative impact
of multiple flows trying to increase their rate together is
minimized. It does that by assigning a flow a sending rate that may
not be what the flow's congestion controller expected. It therefore
builds on the assumption that no significant inefficiencies arise
from temporary non-greedy behavior or from quickly jumping to a rate
that is higher than the congestion controller intended. How
problematic these issues really are depends on the controllers in use
and requires careful per-controller experimentation. The coupled
congestion control mechanism described here also does not require all
controllers to be equal; effects of heterogeneous controllers, or
homogeneous controllers being in different states, are also subject
to experimentation.
There are more potential issues with the algorithm described here.
Rule 3 b) leads to a conservative behavior: it ensures that only one
flow at a time can increase the overall sending rate. This rule is
probably appropriate for situations where minimizing delay is the
major goal, but it may not fit for all purposes; it also does not
incorporate the magnitude by which a flow can increase its rate.
Notably, despite this limitation on the overall rate of all flows per
FGI, immediate rate jumps of single flows could become problematic
when the FSE is used in a highly asynchronous manner, e.g. when flows
have very different RTTs. Rule 3 e) gives all the leftover rate of
non-greedy flows to the first flow that updates its sending rate,
provided that this flow needs it all (otherwise, its own leftover
rate can be taken by the next flow that updates its rate). Other
policies could be applied, e.g. to divide the leftover rate of a flow
equally among all other flows in the FGI.
5.3.2. Example operation
In order to illustrate the operation of the coupled congestion
control algorithm, this section presents a toy example of two flows
that use it. Let us assume that both flows traverse a common 10
Mbit/s bottleneck and use a simplistic congestion controller that
starts out with 1 Mbit/s, increases its rate by 1 Mbit/s in the
absence of congestion and decreases it by 2 Mbit/s in the presence of
congestion. For simplicity, flows are assumed to always operate in a
round-robin fashion. Rate numbers below without units are assumed to
be in Mbit/s. For illustration purposes, the actual sending rate is
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also shown for every flow in FSE diagrams even though it is not
really stored in the FSE.
Flow #1 begins. It is greedy and considers itself to have top
priority. This is the FSE after the flow algorithm's step 1:
---------------------------------------------
| # | FGI | P | CR | DR | S_CR | Rate |
| | | | | | | |
| 1 | 1 | 1 | 1 | 1 | 1 | 1 |
---------------------------------------------
Its congestion controller gradually increases its rate. Eventually,
at some point, the FSE should look like this:
---------------------------------------------
| # | FGI | P | CR | DR | S_CR | Rate |
| | | | | | | |
| 1 | 1 | 1 | 10 | 10 | 10 | 10 |
---------------------------------------------
Now another flow joins. It is also greedy, and has a lower priority
(0.5):
-----------------------------------------------
| # | FGI | P | CR | DR | S_CR | Rate |
| | | | | | | |
| 1 | 1 | 1 | 10 | 10 | 10 | 10 |
| 2 | 1 | 0.5 | 1 | 1 | 11 | 1 |
-----------------------------------------------
Now assume that the first flow updates its rate to 8, because the
total sending rate of 11 exceeds the total capacity. Let us take a
closer look at what happens in step 3 of the flow algorithm.
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new_CR = 8. new_DR = infinity.
3 a) S_P = 1.5; S_DR = 11; new_S_CR = 11.
3 b) new_CR < CR, hence CR = 8.
3 c) new_S_CR = 9; S_CR = 9.
3 d) DR = CR = 8; S_DR = 9.
3 e) TLO = 0; there are no other flows with DR < CR.
3 f) new sending rate: min(infinity, 1/1.5 * 9 + 0) = 6.
3 g) does not apply.
The resulting FSE looks as follows:
-----------------------------------------------
| # | FGI | P | CR | DR | S_CR | Rate |
| | | | | | | |
| 1 | 1 | 1 | 8 | 8 | 9 | 6 |
| 2 | 1 | 0.5 | 1 | 1 | 11 | 1 |
-----------------------------------------------
The effect is that flow #1 is sending with 6 Mbit/s instead of the 8
Mbit/s that the congestion controller derived. Let us now assume
that flow #2 updates its rate. Its congestion controller detects
that the network is not fully saturated (the actual total sending
rate is 6+1=7) and increases its rate.
new_CR=2. new_DR = infinity.
3 a) S_P = 1.5; S_DR = 9; new_S_CR = 9.
3 b) new_CR > CR but new_S_CR < S_CR, hence CR = 2.
3 c) new_S_CR = 10; S_CR = 10.
3 d) DR = CR = 2; S_DR = 10.
3 e) TLO = 0; there are no other flows with DR < CR.
3 f) new sending rate: min(infinity, 0.5/1.5 * 10 + 0) = 3.33.
3 g) new sending rate > DR, hence DR = 3.33.
The resulting FSE looks as follows:
-----------------------------------------------
| # | FGI | P | CR | DR | S_CR | Rate |
| | | | | | | |
| 1 | 1 | 1 | 8 | 8 | 9 | 6 |
| 2 | 1 | 0.5 | 2 | 3.33 | 10 | 3.33 |
-----------------------------------------------
The effect is that flow #2 is now sending with 3.33 Mbit/s, which is
close to half of the rate of flow #1 and leads to a total utilization
of 6(#1) + 3.33(#2) = 9.33 Mbit/s. Flow #2's congestion controller
has increased its rate faster than the controller actually expected.
Now, flow #1 updates its rate. Its congestion controller detects
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that the network is not fully saturated and increases its rate.
Additionally, the application feeding into flow #1 limits the flow's
sending rate to at most 2 Mbit/s.
new_CR=9. new_DR=2.
3 a) S_P = 1.5; S_DR = 11.33; new_S_CR = 10.
3 b) new_CR > CR and new_S_CR > S_CR, hence CR is not updated
(since flow #2 has just increased S_CR, flow #1 cannot also
increase it in this iteration).
3 c) new_S_CR = 10; S_CR = 10.
3 d) DR = 2; S_DR = 5.33.
3 e) TLO = 0; there are no other flows with DR < CR.
3 f) new sending rate: min(2, 1/1.5 * 10 + 0) = 2. Note that,
without the 2 Mbit/s limitation from the application, the new
sending rate for flow #1 would now be 6.66 Mbit/s, leading to
perfect network saturation (6.66 + 3.33 = approx. 10).
3 g) does not apply.
The resulting FSE looks as follows:
-----------------------------------------------
| # | FGI | P | CR | DR | S_CR | Rate |
| | | | | | | |
| 1 | 1 | 1 | 8 | 2 | 10 | 2 |
| 2 | 1 | 0.5 | 2 | 3.33 | 10 | 3.33 |
-----------------------------------------------
Now, the total rate of the two flows is 2 + 3.33 = 5.33 Mbit/s, i.e.
the network is significantly underutilized due to the limitation of
flow #1. Flow #2 updates its rate. Its congestion controller
detects that the network is not fully saturated and increases its
rate.
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new_CR=3. new_DR = infinity.
3 a) S_P = 1.5; S_DR = 5.33; new_S_CR = 10.
3 b) new_CR > CR but new_S_CR = S_CR, hence CR = 3.
3 c) new_S_CR = 11; S_CR = 11.
3 d) DR = 3; S_DR = 5.
3 e) TLO = 0; flow #1 has DR < CR, hence TLO += 1/1.5 * 11
- 2 = 5.33.
DR of flow #1 is set to 8. Flow #1 does not have a negative
P(i) value, so its entry is not deleted.
3 f) new sending rate: min(infinity, 0.5/1.5*11 + 5.33) = 9.
3 g) new sending rate > DR, hence DR = 9.
The resulting FSE looks as follows:
-----------------------------------------------
| # | FGI | P | CR | DR | S_CR | Rate |
| | | | | | | |
| 1 | 1 | 1 | 8 | 8 | 10 | 2 |
| 2 | 1 | 0.5 | 3 | 9 | 11 | 9 |
-----------------------------------------------
Now, the total rate of the two flows is 2 + 9 = 11 Mbit/s, exceeding
the total capacity by the 1 Mbit/s by which the congestion controller
of flow #2 has increased its rate. Note that, had flow #1 been
greedy, the same total rate would have resulted after this iteration.
Finally, flow #1 terminates. It sets P to -1 and DR to 0. Let us
assume that it terminated late enough for flow #2 to still experience
the network in a congested state, i.e. flow #2 decreases its rate in
the next iteration.
new_CR = 1. new_DR = infinity.
3 a) S_P = 1.5; S_DR = 9; new_S_CR = 11.
3 b) new_CR < CR hence CR = 1.
3 c) new_S_CR = 9; S_CR = 9.
3 d) DR = 1; S_DR = 1.
3 e) TLO = 0; flow #1 has DR < CR, hence TLO += 1/1.5 * 9 - 0 = 6.
DR of flow #1 is set to 8. Flow #1 has a negative P(i) value, so
its entry is deleted.
3 f) new sending rate: min(infinity, 0.5/1.5 * 9 + 6) = 9.
3 g) new sending rate > DR, hence DR = 9.
The resulting FSE looks as follows:
-----------------------------------------------
| # | FGI | P | CR | DR | S_CR | Rate |
| | | | | | | |
| 1 | 1 | -1 | 8 | 0 | 10 | 2 | (before deletion)
| 2 | 1 | 0.5 | 1 | 9 | 9 | 9 |
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-----------------------------------------------
Now, the total rate, used only by flow #2, is 9 Mbit/s, which is the
rate that it would have had alone upon reacting to congestion after a
sending rate of 11 Mbit/s.
6. Acknowledgements
This document has benefitted from discussions with and feedback from
Stein Gjessing, David Hayes, Safiqul Islam, Naeem Khademi, Andreas
Petlund, and David Ros (who also gave the FSE its name).
7. IANA Considerations
This memo includes no request to IANA.
8. Security Considerations
In scenarios where the architecture described in this document is
applied across applications, various cheating possibilities arise:
e.g., supporting wrong values for the calculated rate, the desired
rate, or the priority of a flow. In the worst case, such cheating
could either prevent other flows from sending or make them send at a
rate that is unreasonably large. The end result would be unfair
behavior at the network bottleneck, akin to what could be achieved
with any UDP based application. Hence, since this is no worse than
UDP in general, there seems to be no significant harm in using this
in the absence of UDP rate limiters.
In the case of a single-user system, it should also be in the
interest of any application programmer to give the user the best
possible experience by using reasonable flow priorities or even
letting the user choose them. In a multi-user system, this interest
may not be given, and one could imagine the worst case of an "arms
race" situation, where applications end up setting their priorities
to the maximum value. If all applications do this, the end result is
a fair allocation in which the priority mechanism is implicitly
eliminated, and no major harm is done.
9. References
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9.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
[RFC2140] Touch, J., "TCP Control Block Interdependence", RFC 2140,
April 1997.
[RFC3124] Balakrishnan, H. and S. Seshan, "The Congestion Manager",
RFC 3124, June 2001.
9.2. Informative References
[rtcweb-rtp-usage]
Perkins, C., Westerlund, M., and J. Ott, "Web Real-Time
Communication (WebRTC): Media Transport and Use of RTP",
draft-ietf-rtcweb-rtp-usage-05.txt (work in progress),
October 2012.
[rtcweb-usecases]
Holmberg, C., Hakansson, S., and G. Eriksson, "Web Real-
Time Communication Use-cases and Requirements",
draft-ietf-rtcweb-use-cases-and-requirements-10.txt (work
in progress), December 2012.
[transport-multiplex]
Westerlund, M. and C. Perkins, "Multiple RTP Sessions on a
Single Lower-Layer Transport",
draft-westerlund-avtcore-transport-multiplexing-04.txt
(work in progress), October 2012.
Author's Address
Michael Welzl
University of Oslo
PO Box 1080 Blindern
Oslo, N-0316
Norway
Phone: +47 22 85 24 20
Email: michawe@ifi.uio.no
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