C.Burmeister
Internet Draft R.Hakenberg
draft-burmeister-avt-rtcp-feedback-sim-00.txt A.Miyazaki
Expires: April 2002 Matsushita
J.Ott
University of Bremen TZI
N.Sato
S.Fukunaga
Oki
November 2001
Extended RTP Profile for RTCP-based Feedback
- Results of the Timing Rule Simulations -
Status of this Memo
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Abstract
This document describes the results we achieved when simulating the
timing rules of the Extended RTP Profile for RTCP-based Feedback.
Unicast and multicast topologies are considered as well as several
protocol and environment configurations. The results show that the
timing rules result in better performance regarding feedback delay
and still preserve the well accepted RTP rules regarding allowed bit
rates for control traffic.
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Table of Contents
Status of this Memo
Abstract
1 Introduction
2 Conventions used in this document
3 Timing rules of the extended RTP profile for RTCP-based feedback
4 Simulation Environment
4.1 Network Simulator Version 2
4.2 RTP Agent
4.3 Scenarios
4.4 Topologies
5 RTCP Bit Rate Measurements
5.1 Unicast
5.2 Multicast
5.3 Summary of the RTCP bit rate measurements
6 Feedback Measurements
6.1 Unicast
6.2 Multicast
6.2.1 Shared Losses vs Distributed Losses
6.2.2 Sender vs. Receiver
7 Investigations on "k"
7.1 Feedback Suppression Performance
7.2 Loss Report Delay
7.3 Summary of "k" investigations
8 Investigations on "l"
8.1 Feedback Suppression Performance
8.2 Loss Report Delay
8.3 Summary of "l" investigations
9 Applications Using AVPF
9.1 NEWPRED Implementation in NS2
9.2 Simulation
9.2.1. Simulation A - Constant Packet Loss Rate
9.2.2. Simulation B - Packet Loss due to Congestion
9.3 Summary
10 Summary
References
Authors Addresses
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1 Introduction
The Real-time Transport Protocol (RTP) is widely used for the
transmission of real-time or near real-time media data over the
Internet. While it was originally designed to work well for
multicast groups in very large scales, its scope is not limited to
that. More and more applications use RTP for small multicast groups
(e.g. video conferences) or even unicast (e.g. media streaming
applications).
RTP comes together with its companion protocol Real-time Transport
Control Protocol (RTCP), which is used to monitor the transmission
of the media data and provide feedback of the reception quality.
What is more it can be used for a loosely session control. Having
the scope of large multicast groups in mind, the rules when to send
feedback were much restricted to avoid feedback explosion or
feedback related congestion in the network. RTP and RTCP have proven
to work well in the Internet, especially in large multicast groups,
which is shown by its tremendous usages today.
However the applications that transmit the media data only to small
multicast groups or unicast, may benefit from more frequent
feedback. The source of the packets might be able to react to
changes in the reception quality, which might be due to congestion
in the network or other sudden changes. Possible reactions include
sending rate adaptation according to a congestion control algorithm
or the invocation of error resilience features for the media stream
(e.g. retransmissions, reference picture selection, NEWPRED, etc.).
As said before, more feedback would be needed to increase the
reception quality, but RTP restricts the use of RTCP feedback very
much. Hence it was decided to create a new extended RTP profile,
which redefines some of the RTCP timing rules, but keeps most of the
algorithms for RTP and RTCP, which have proven to work well. The new
rules should scale from unicast to multicast, where unicast or small
multicast applications have the most gain from it. A detailed
description of the new profile and its timing rules can be found in
[1].
This document investigates the new algorithms by the means of
simulations. We show that the new timing rules scale and behave
network friendly. Therefore we first describe roughly the key
features of the new RTP profile, which are important for our
simulations, in Section 3. After that we describe the environment
that is used to conduct the simulations in Section 4. Section 5
describes simulation results that show the backwards compatibility
to RTP and that the new profile is network friendly in terms of used
bit rate for feedback and other control traffic. In Section 6 we
show the benefit that applications could get from implementing the
new profile. In Section 7 and 8 we show the merit for some special
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parameters settings and finally in section 9 we show the performance
gain we could get for a special application, namely NEWPRED in
MPEG-4.
2 Conventions used in this document
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.
3 Timing rules of the extended RTP profile for RTCP-based feedback
As said above, RTP restricts the usage of RTCP feedback. The main
rules that restrict the feedback are as follows:
- RTCP messages are sent in compound packets, i.e. every RTCP packet
contains at least one sender report (SR) or receiver report (RR)
message and a source description (SDES) message.
- The RTCP compound packets are sent in time intervals (T_rr), which
is computed as a function of the average packet size, the number
of senders and receivers in the group and the session bandwidth.
(-> 5% of the session bandwidth is used for RTCP messages; this
bandwidth is shared between all session members, where the senders
might get more than the receivers.)
- The minimum interval between two RTCP packets from the same source
is 5 seconds.
We see that these rules prevent feedback explosion and scale to very
large multicast groups. However they do not allow timely feedback at
all. While the second rule scales also to small groups or unicast
(in this cases the interval might be as small as a few
milliseconds), the third rule prevents the receivers from sending
feedback in time.
The timing rules to send RTCP feedback from the new RTP profile [1]
consists of two key components. First the minimum interval of 5
seconds is abolished. Second, receivers get once during their (now
quite small) RTCP interval the chance to send an RTCP packet
"early", i.e. not according to the calculated interval, but
virtually immediately. It is important to note that the RTCP
interval calculation is still inherited from the original RTP
specification.
The specification and all the details of the extended timing rules
can be found in [1]. We do not want to describe the algorithms here,
but rather reference these from the original specification where
needed. Therefore we use also the same variable names and
abbreviations as in [1].
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4 Simulation Environment
This section describes the simulator that was used for the
investigations and its key features. The extensions to the
simulator, that were necessary are described roughly.
4.1 Network Simulator Version 2
The simulations were conducted using the network simulator version 2
(ns2). ns2 is an open source project, written in a combination of
Tool Command Language (TCL) and C++. The scenarios are set-up using
TCL. In the scripts it is possible to specify the topologies (nodes
and links, bandwidths, queue sizes or error rates for links) and the
parameters of the "agents", i.e. protocol configurations. The
protocols itself are implemented in C++ in the agents, which are
connected to the nodes. A detailed description of ns2 and a
downloadable newest version can be found at [4].
4.2 RTP Agent
We implemented a new agent, based on RTP/RTCP. RTP packets are sent
at a constant packet rate with the correct header sizes. RTCP
packets are sent according to the timing rules of [2] and also its
algorithms for group membership maintenance are implemented. Sender
and receiver reports are sent and the senders use these reports to
maintain a RTT estimation to the other group members, as it is
described in [2].
Further we extended the agent to support the extended profile [1].
The use of the new timing rules can be turned on and off via
parameter settings in TCL.
4.3 Scenarios
The scenarios that are simulated are defined in TCL scripts. We set-
up several different topologies, ranging from unicast with two
session members to multicast with up to 25 session members.
Depending on the used sending rates and the corresponding link
bandwidths congestion losses may occur. In some scenarios, bit
errors are inserted on certain links. We simulated groups with
RTP/AVP agents, RTP/AVPF agents and mixed groups.
The feedback messages are generally NACK messages as defined in [1]
and are triggered by packet loss.
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4.4 Topologies
Mainly four different topologies are simulated to show the key
features of the extended profile. However for some specific
simulations we used, different topologies, which is then indicated
at the description of the simulation results. The main four
topologies are named after the number of participating RTP agents,
i.e. T-2, T-4, T-8 and T-16, where T-2 is a unicast scenario, T-4
contains four agents, etc. The figures below illustrate the main
topologies.
A5
A5 | A6
/ | /
/ | /--A7
/ |/
A2 A2-----A6 A2--A8
/ / / A9
/ / / /
/ / / /---A10
A1-----A2 A1-----A3 A1-----A3-----A7 A1------A3<
\ \ \ \---A11
\ \ \ \
\ \ \ A12
A4 A4-----A8 A4--A13
|\
| \--A14
| \
| A15
A16
T-2 T-4 T-8 T-16
Figure 1: Simulated Topologies.
5 RTCP Bit Rate Measurements
The new timing rules allow more frequent RTCP feedback for small
multicast groups. In large groups the algorithm behaves similar to
usual RTP. While it is generally good to have more frequent feedback
it cannot be allowed at all to increase the bit rate used for RTCP
above a fixed limit, i.e. 5% of the total RTP bandwidth according to
RTP. This section shows that with the new timing rules we keep the
5% limit for all investigated scenarios, topologies and group sizes.
What is more, we show that mixed groups, i.e. some members use AVP
some use AVPF, can be allowed and that each session member behaves
fair according to its corresponding specification.
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5.1 Unicast
First we measured the RTCP bandwidth share in the unicast topology
T-2. Even for a fixed topology and group size, there are several
protocol parameters which are varied to simulate a large range of
different scenarios. First we varied the RTP session bandwidth. For
large session bandwidths, the allowed RTCP bit rate increases also
and thus more RTCP packets can be sent. Second we changed the number
of agents that are pure receivers or also senders. This has also
some influence on the RTCP feedback, because on the one hand pure
receivers do not have an RTT estimation and one the other hand they
do not send sender reports. Third we varied the configurations of
the agents in that sense that the agents may use the AVP or AVPF.
Thereby it is possible that one agent uses AVP and the other AVPF in
one RTP session. This is done to test the backwards compatibility.
First we consider scenarios where no losses occur. In this case both
RTP session members transmit the RTCP compound packets at regular
intervals, calculated as T_rr, if they use the AVPF, and use the
minimum interval of 5s if they implement the AVP. No early packets
are sent, because the need to send feedback is not given. Still it
is important to see that not more than 5% of the session bandwidth
is used for RTCP and that AVP and AVPF members can co-exist without
interference. The results can be found in table 1.
| | | | | | Used RTCP Bit Rate |
| Session | Send | Rec. | AVP | AVPF | (% of session bw) |
|Bandwidth|Agents|Agents|Agents|Agents| A1 | A2 | sum |
+---------+------+------+------+------+------+------+------+
| 2 Mbps | 1 | 2 | - | 1,2 | 2.42 | 2.56 | 4.98 |
| 2 Mbps | 1,2 | - | - | 1,2 | 2.49 | 2.49 | 4.98 |
| 2 Mbps | 1 | 2 | 1 | 1,2 | 0.01 | 2.49 | 2.50 |
| 2 Mbps | 1,2 | - | 1 | 1,2 | 0.01 | 2.48 | 2.49 |
| 2 Mbps | 1 | 2 | 1,2 | 1,2 | 0.01 | 0.01 | 0.02 |
| 2 Mbps | 1,2 | - | 1,2 | 1,2 | 0.01 | 0.01 | 0.02 |
|200 kbps | 1 | 2 | - | 1,2 | 2.42 | 2.56 | 4.98 |
|200 kbps | 1,2 | - | - | 1,2 | 2.49 | 2.49 | 4.98 |
|200 kbps | 1 | 2 | 1 | 1,2 | 0.06 | 2.49 | 2.55 |
|200 kbps | 1,2 | - | 1 | 1,2 | 0.08 | 2.50 | 2.58 |
|200 kbps | 1 | 2 | 1,2 | 1,2 | 0.06 | 0.06 | 0.12 |
|200 kbps | 1,2 | - | 1,2 | 1,2 | 0.08 | 0.08 | 0.16 |
| 20 kbps | 1 | 2 | - | 1,2 | 2.44 | 2.54 | 4.98 |
| 20 kbps | 1,2 | - | - | 1,2 | 2.50 | 2.51 | 5.01 |
| 20 kbps | 1 | 2 | 1 | 1,2 | 0.58 | 2.48 | 3.06 |
| 20 kbps | 1,2 | - | 1 | 1,2 | 0.77 | 2.51 | 3.28 |
| 20 kbps | 1 | 2 | 1,2 | 1,2 | 0.58 | 0.61 | 1.19 |
| 20 kbps | 1,2 | - | 1,2 | 1,2 | 0.77 | 0.79 | 1.58 |
Table 1: Unicast simulations without packet loss.
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We can see that in configurations, where both Agents use the new
timing rules each of them uses about 2.5% of the session bandwidth
for RTP, which sums up to 5% of the session bandwidth for both. This
is achieved regardless of the agent being a sender or a receiver. In
the cases where Agent1 uses AVP and Agent2 AVPF, the total RTCP
session bandwidth is decreased. This is due to the fact that Agent1
can send RTCP packets only with a minimum interval of 5 seconds.
Thus only a small fraction of the session bandwidth is used for its
RTCP packets. For a high bit rate session (session bandwidth = 2
Mbps) the fraction of the RTCP packets from Agent one is as small as
0.01%. For smaller session bandwidths the fraction increases,
because the same amount of RTCP data is sent. The bandwidth share
that is used by RTCP packets from Agent 2 is not different from what
was used, when both Agents implemented the AVPF. Thus the
interaction of AVP and AVPF agents is not problematic in these
scenarios at all.
In our second unicast experiment, we show that the allowed RTCP
bandwidth share is not exceeded, even if packet loss occurs. We
simulated a constant byte error rate (BYER) on the link. The byte
errors are inserted randomly with a uniform distribution. Packets
with byte errors are discarded on the link; hence the receiving
agents will not see the loss immediately. The agents detect packet
loss by a gap in the sequence number.
When the agents detect a packet loss, they feel the need to send
feedback. In unicast T_dither_max is always zero, hence an early
packet can be sent immediately if allow_early is true. If the last
packet was already an early one (i.e. allow_early = false), the
feedback might be appended to the next regularly scheduled receiver
report. The max_feedback_delay parameter (which we set to 1 second
in our simulations) determines if that is allowed.
The results are shown in table 2, where we can see that there is no
difference in the RTCP bandwidth share, whether losses occur or not.
This is what we expected, because even though the RTCP packet size
grows and early packets are sent, the interval between the packets
increases and thus the RTCP bandwidth stays the same. Only the RTCP
bandwidth of the Agents that use the AVP increases slightly. This is
because the interval between the packets is still 5 seconds, but the
packet size increased because of the feedback that is appended.
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| | | | | | Used RTCP Bit Rate |
| Session | Send | Rec. | AVP | AVPF | (% of session bw) |
|Bandwidth|Agents|Agents|Agents|Agents| A1 | A2 | sum |
+---------+------+------+------+------+------+------+------+
| 2 Mbps | 1 | 2 | - | 1,2 | 2.42 | 2.56 | 4.98 |
| 2 Mbps | 1,2 | - | - | 1,2 | 2.49 | 2.49 | 4.98 |
| 2 Mbps | 1 | 2 | 1 | 1,2 | 0.01 | 2.49 | 2.50 |
| 2 Mbps | 1,2 | - | 1 | 1,2 | 0.01 | 2.48 | 2.49 |
| 2 Mbps | 1 | 2 | 1,2 | 1,2 | 0.01 | 0.02 | 0.03 |
| 2 Mbps | 1,2 | - | 1,2 | 1,2 | 0.01 | 0.01 | 0.02 |
|200 kbps | 1 | 2 | - | 1,2 | 2.42 | 2.56 | 4.98 |
|200 kbps | 1,2 | - | - | 1,2 | 2.50 | 2.49 | 4.99 |
|200 kbps | 1 | 2 | 1 | 1,2 | 0.06 | 2.50 | 2.56 |
|200 kbps | 1,2 | - | 1 | 1,2 | 0.08 | 2.49 | 2.57 |
|200 kbps | 1 | 2 | 1,2 | 1,2 | 0.06 | 0.07 | 0.13 |
|200 kbps | 1,2 | - | 1,2 | 1,2 | 0.09 | 0.08 | 0.17 |
| 20 kbps | 1 | 2 | - | 1,2 | 2.42 | 2.57 | 4.99 |
| 20 kbps | 1,2 | - | - | 1,2 | 2.52 | 2.51 | 5.03 |
| 20 kbps | 1 | 2 | 1 | 1,2 | 0.58 | 2.54 | 3.12 |
| 20 kbps | 1,2 | - | 1 | 1,2 | 0.83 | 2.43 | 3.26 |
| 20 kbps | 1 | 2 | 1,2 | 1,2 | 0.58 | 0.73 | 1.31 |
| 20 kbps | 1,2 | - | 1,2 | 1,2 | 0.86 | 0.84 | 1.70 |
Table 2: Unicast simulations with packet loss.
5.2 Multicast
Next we investigated the RTCP bandwidth share in multicast
scenarios, i.e. we simulated the topologies T-4, T-8 and T-16 and
measured the fraction of the session bandwidth that was used for
RTCP packets. Again we considered different situations and protocol
configurations (e.g. with or without bit errors, groups with AVP
and/or AVPF agents, etc.). For reasons of readability, we present
only selected results. For a documentation of all results, see [5].
The simulations of the different topologies in scenarios, where no
losses occur, neither through bit errors nor through congestion,
show a similar behavior as the unicast scenarios. For all group
sizes the maximum used RTCP bit rate share is 5.06% of the session
bandwidth in a simulation of 16 session members in a low bit rate
scenario (session bandwidth = 20kbps) with several senders. In all
other scenarios without losses the used RTCP bit rate share is below
that. Thus the requirement, that not more than 5% of the session bit
rate should be used for RTCP is fulfilled in reasonable accuracy.
Simulations, were bit errors are randomly inserted in RTP and RTCP
packets and the corrupted packets are discarded, give the same
results. The 5% rule is kept (at maximum 5.07% of the session
bandwidth is used for RTCP).
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Finally we conducted simulations, where we reduced the link
bandwidth and thereby caused congestion related losses. These
simulations are different from the previous bit error simulations,
in that the losses occur more in bursts and are more correlated,
also between different agents. The correlation and burstness of the
packet loss is due to the queuing discipline in the routers we
simulated; we used simple FIFO queues with a drop-tail strategy to
handle congestion. Random Early Detection (RED) queues may enhance
the performance, because the burstness of the packet loss might be
reduced, however this is not subject of our investigations, but is
left for future research. The delay between the agents, which also
influence RTP and RTCP packets, is much more variable because of the
added queuing delay. Still the used RTCP bit rate share does not
increase beyond 5.09% of the session bandwidth. Thus also for these
special cases the requirement is fulfilled.
5.3 Summary of the RTCP bit rate measurements
We have shown that for unicast and reasonable multicast scenarios,
feedback explosion does not happen. The requirement that at maximum
5% of the session bandwidth is used for RTCP is fulfilled for all
investigated scenarios.
6 Feedback Measurements
In this chapter we describe the results of feedback delay
measurements, we conducted in the simulations. Therefore we use two
metrics for measuring the performance of the algorithms, these are
the mean "waiting time" (MWT) and the number of feedback that is
sent, suppressed or not allowed. The waiting time is the time,
measured at a certain agent, between the detection of a packet loss
and the time when the corresponding feedback is sent. Assuming that
the value of the feedback decreases with its delay, we think that
the mean waiting time is a good metric to measure the performance
gain we could get by using AVPF instead of AVP.
The feedback an agent wants to send can be either sent or not sent.
If it was not sent, this could be due to the feedback suppression,
i.e. another receiver already sent the same feedback or because the
feedback was not allowed, i.e. the max_feedback_delay was exceeded.
We traced for every detected loss, if the agent sent the
corresponding feedback or not and if not, why. The more feedback was
not allowed, the worse the performance of the algorithm. Together
with the waiting times, this gives us a good hint of the overall
performance of the scheme.
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6.1 Unicast
In the unicast case, the maximum dithering interval T_Dither_max is
fixed and set to zero. This is due to the fact that it does not make
sense for a unicast receiver to wait for other receivers if they
have the same feedback to send. But still feedback can be delayed or
might not be permitted to be sent at all. The dithering interval is
a parameter for the early packets, but at maximum every second
packet can be an early packet. The regularly scheduled packets are
spaced according to T_rr, which depends in the unicast case mainly
on the session bandwidth.
Table 3 shows the mean waiting times (MWT) for some configurations
of the unicast topology T-2. The number of feedback packets that are
sent or discarded is listed also (feedback sent (sent) or feedback
discarded (disc)). We do not list suppressed packets, because for
the unicast case feedback suppression does not apply. In the
simulations, agent 1 was a sender and agent 2 a pure receiver. We
did not vary this, because the only difference in being a sender or
pure receiver, is that the sender has an RTT estimation to the
receivers. However the RTT estimation is used for the T_Dither_max
calculations only in the multicast cases.
| | | Feedback Statistics |
| Session | | AVP | AVPF |
|Bandwidth| PLR | sent |disc| MWT | sent |disc| MWT |
+---------+-------+------+----+-------+------+----+-------+
| 2 Mbps | 0.001 | 781 | 0 | 2.604 | 756 | 0 | 0.015 |
| 2 Mbps | 0.01 | 7480 | 0 | 2.591 | 7548 | 2 | 0.006 |
| 2 Mbps | cong. | 25 | 0 | 2.557 | 1741 | 0 | 0.001 |
| 20 kbps | 0.001 | 79 | 0 | 2.472 | 74 | 2 | 0.034 |
| 20 kbps | 0.01 | 780 | 0 | 2.605 | 709 | 64 | 0.163 |
| 20 kbps | cong. | 780 | 0 | 2.590 | 687 | 70 | 0.162 |
Table 3: Feedback Statistics for the unicast simulations.
From the table above we see that the mean waiting time can be
decreased dramatically by using AVPF instead of AVP. While the
waiting times for agents using AVP is always around 2.5 seconds
(half the minimum interval) it can be decreased to a few ms for most
of the AVPF configurations.
In the cases of high session bandwidth normally all feedback is
sent. This is because the packet size is quite large (1000byte) and
thus per lost packet, more RTCP bandwidth is available. There are
only very few exceptions, which are probably due to two packet
losses within one RTCP interval, where the first loss was by chance
sent quite early. In this case it might be possible that the second
feedback is detected after the early packet was sent, but too early
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to append it to the next regularly scheduled report, because of the
limitation of the max_feedback_delay. This is different for the
cases with a small session bandwidth. Here we have a small packet
size (100byte) and thus many packets are transmitted, while the RTCP
bandwidth share is quite low. T_rr is thus quite large. After an
early packet was sent the time to the next regularly scheduled
packet can be very high. We saw that in some cases the time was
larger than than max_feedback_delay, because in these cases the
feedback is not allowed to be sent at all.
With a different setting of max_feedback_delay it is possible to
have either more feedback that is not allowed and a decreased mean
waiting time or more feedback that is sent but an increased waiting
time. Thus the parameter should be set with care according to the
application's needs.
6.2 Multicast
In this section we describe some measurements of feedback statistics
in the multicast simulations. We picked out certain characteristic
and representative results. Therefore we considered the topology T-
16. Different scenarios and applications are simulated for this
topology. The parameters of the different links are set as follows.
The agents A2, A3 and A4 are connected to the middle node of the
multicast tree, i.e. agent A1, via high bandwidth and low delay
links. The other agents are connected to the nodes 2, 3 and 4 via
different link characteristics. The agents connected to node 2
represent mobile users. They suffer in certain configurations from a
certain byte error rate on their access links and the delays are
quite high. The agents that are connected to node 3 have low
bandwidth access links, but do not suffer from bit errors. The last
agents, that are connected to node 4 have quite high bandwidth and
quite low delay.
6.2.1 Shared Losses vs Distributed Losses
In our first investigation, we wanted to see the influence the loss
characteristic on the algorithm's performance, i.e. we wanted to
investigate the cases where packet loss occurs for several users
simultaneously or totally independently. Therefore we first define
agent A1 to be the sender. In the shared-loss-case we insert a
constant byte error rate on one of the middle links, i.e. the link
between A1 and A2. In the case of distributed losses we inserted the
same byte error rate on all links downstream of A2.
This scenario is especially interesting, because of the feedback
suppression algorithm. When all receivers share the same loss, it is
only necessary for one of them to send the loss report. Hence if a
member receives feedback with the same content that it has scheduled
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to be sent, it suppresses the scheduled feedback. Of course this
suppressed feedback does not contribute to the mean waiting times.
So we expect reduced waiting times for shared losses, because the
probability is high that one of the receivers can send the feedback
more or less immediately. The results are shown in the following
table.
| | Feedback Statistics |
| | Shared Losses | Distributed Losses |
|Agent|sent|fbsp|disc|sum | MWT |sent|fbsp|disc|sum | MWT |
+-----+----+----+----+----+-----+----+----+----+----+-----+
| A2 | 274| 351| 25| 650|0.267| -| -| -| -| -|
| A5 | 231| 408| 11| 650|0.243| 619| 2| 32| 653|0.663|
| A6 | 234| 407| 9| 650|0.235| 587| 2| 32| 621|0.701|
| A7 | 223| 414| 13| 650|0.253| 594| 6| 41| 641|0.658|
| A8 | 188| 443| 19| 650|0.235| 596| 1| 32| 629|0.677|
Table 4: Feedback statistics for multicast simulations.
Table 4 shows the feedback statistics for the simulation of a large
group size. All 16 agents of topology T-16 joined the RTP session.
However only agent A1 acts as an RTP sender, the other agents are
pure receivers. Only 4 or 5 agents suffer from packet loss, i.e. A2,
A5, A6, A7 and A8 for the case of shared losses and A5, A6, A7 and
A8 in the case of distributed losses. Since the number of session
members is the same for both cases, T_rr is also the same on the
average. Still the mean waiting times are reduced by more than 50%
in the case of shared losses. This proves our assumption that shared
losses enhance the performance of the algorithm.
The feedback suppression mechanism seems to be working quite fine.
Even though some feedback is sent from different receivers (i.e.
1150 loss reports are sent in total and only 650 packets were lost,
resulting in loss report being received on the average 1.8 times)
most of the redundant feedback was suppressed. I.e. 2023 loss
reports were suppressed from 3250 individual detected losses, which
means that more than 60% of the feedback was actually suppressed.
6.2.2 Sender vs. Receiver
RTP senders are able to maintain a RTT measurement to all receivers,
which send receiver reports. This is done by the means of the ntp
timestamp in the sender report and the repetition of this value
together with the delay since last sender report value in the
receiver report. However RTP session members that do not send RTP
packets are not an RTP sender and thus do not send sender reports.
Therefore pure receivers do not have an RTT measurement to the
senders or other receivers. This fact is considered in AVPF, by
giving two possibilities to calculate T_dither_max.
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If the RTP member has an RTT measurement to the sender of the packet
it wants to provide feedback to, it calculates T_dither_max = k *
T_rtt/2 * members, with k = 1. Thus t_dither_max is increased with
the number of session members and the RTT. The rational for RTT/2 is
that the distance to the sender is a good measure how long to wait
at maximum. Other receivers, who are more far away, i.e. have a
larger RTT estimation, will detect the packets later and also the
feedback from those would arrive later and hence have less value.
Thus the nearest receivers get the chance first to send their
feedback. Because of the larger distance of the other receivers to
the sender, they will probably wait longer (probably, because of the
randomness, i.e. we calculate T_dither_max, from which T_dither is
picked randomly). While those are waiting, it is likely that they
receive the feedback from the receivers that are nearer to the
source. With this it is possible to find a good compromise between
waiting time and feedback suppression. To let the algorithm scale to
large group sizes, the number of session members is included. The
number of members is the maximum number of receivers that shared the
same loss. The more members are in the session, the higher is the
probability that other receivers share the loss and thus the higher
is the value of waiting longer, because the probability is increased
that feedback suppression will work. If all receivers calculate the
same T_dither_max ( i.e. have a similar RTT estimation) and pick a
T_dither from this interval randomly with a uniform distribution, it
is likely that one feedback is sent within the first RTT interval.
In case the RTP session member does not have an RTT measurement,
i.e. it is a pure receiver, is calculates T_dither_max = l * T_rr,
with l = 0.5. The rational for this is that the receiver, if it has
no RTT estimation, does not know at all how long it should wait for
other receivers to send feedback. The feedback suppression algorithm
would certainly fail, if the time is selected too short. However the
waiting time is increased unnecessarily (and thus the value of the
feedback is decreased!) in case the time is chosen too long. It
would be good to find the optimum time (which is tried to be done
with the RTT estimation), but it is not dangerous if the optimum
time is not chosen. Decreased feedback value and a failure of the
feedback suppression mechanism do not hurt the network stability. We
have shown for the cases of distributed losses that the overall
bandwidth constraints are kept in any case and thus we could only
loose some performance by choosing the wrong time. A good measure
for T_dither_max however is the RTCP interval T_rr. This value
increases with the number of session members. Also we know that we
can send feedback at least every T_rr. Thus increasing T_dither max
beyond T_rr would certainly make no sense. So by choosing T_rr/2 we
guarantee that at least sometimes (i.e. when a loss is detected in
the first half of the interval between two regularly scheduled RTCP
packets) we are allowed to send early packets. Because of the
randomness of T_dither we still have a good chance to send the early
packet in time.
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Having said that, we assume that the RTP members who have an RTT
measurement would perform better regarding the feedback suppression.
We want to show that by simulating the same scenario of the previous
section, but enabling all receivers that suffer from packet loss to
maintain a RTT measurement. We do this by declaring the
corresponding agents to RTP senders. However we do not send RTP
packets from this agents, to be comparable to the previous results.
The only difference to the previous simulations is that sender
reports are sent, which enables the sender to maintain a RTT
measurement.
| | Feedback Statistics |
| | Shared Losses | Distributed Losses |
|Agent|sent|fbsp|disc|sum | MWT |sent|fbsp|disc|sum | MWT |
+-----+----+----+----+----+-----+----+----+----+----+-----+
| A2 | 582| 43| 7| 632|0.100| -| -| -| -| -|
| A5 | 70| 562| 0| 632|0.121| 644| 1| 1| 646|0.576|
| A6 | 60| 572| 0| 632|0.114| 638| 5| 1| 644|0.575|
| A7 | 73| 559| 0| 632|0.109| 607| 3| 1| 611|0.567|
| A8 | 63| 569| 0| 632|0.108| 626| 3| 0| 629|0.589|
Table 5: Feedback statistics for multicast simulations, where the
agents that suffer from packet loss do have an RTT estimation to the
sender.
Table 5 shows the results of the simulations. As assumed, we see
that the performance regarding the waiting time is increased
significantly. In case of shared losses, the mean time is less than
half of the mean waiting times of the receivers that do not have a
RTT estimation. Also for the case of distributed losses, we see a
slight gain in performance, however not as big as for the shared
losses. But still we see that the calculation of T-dither_max, using
the RTT estimation finds a better tradeoff between waiting time and
feedback suppression. The waiting time is reduced and the feedback
suppression increased where possible. Thus for both cases, whether
feedback suppression is possible or not, the performance is
increased. Feedback suppression in the case of shared losses is
working much better with a RTT estimation. From 3160 individual
detected losses only 848 loss reports are sent.
7 Investigations on "k"
The parameter k in the formula how to calculate T_Dither_max if an
RTT estimation is available has some influence of the performance of
the algorithm. Thus we investigated the effect and tried to find an
optimum value for k. Therefore we defined a sample scenarios and
tried to find an optimum value for k.
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We define three representative sample scenarios. We use the topology
from the previous section. Most of the agents however contribute
only little to the simulations, because we introduced an error rate
only on the link between the sender A1 and the agent A2.
The first scenario represents cases, where losses are shared between
two agents. One agent is located upstream on the path between the
other agent and the sender. Therefore agent A2 and agent A5 see the
same losses, that are introduce on the link between the sender and
agent A2. Agent A6, A7 and A8 do not join the RTP session. From the
other agents only agents A3 and A9 join. Both agent A2 and A5 are
declared as RTP senders, in order to have an RTT estimation to the
sender A1.
The second scenario represents also cases, where losses are shared
between two agents, but this time the agents are located on
different branches of the multicast tree. The delays to the sender
are roughly of the same magnitude. Agent A5 and A6 share the same
losses. Agents A3 and A9 join the RTP session, but are pure
receivers and do not see any losses.
Also in the third scenario, the losses re shared between two agents,
A5 and A6. The same agents as in the second scenario are active.
However the delays of the links are different. The delay of the link
between agent A2 and A5 is reduced to 20ms and between A2 and A6 to
40ms. Thus the RTT estimations of agents A5 and A6 to the sender are
reduced significantly.
7.1 Feedback Suppression Performance
First we consider the fraction of feedback that the agent An
suppresses (Feedback Suppression Rate). An is thereby the agent
nearer to the source. The simulation results can be seen from
Table 7. In general it can be seen that agent An suppresses more
feedback if the differences between the delays to the source are
smaller. This is reasonable, because the feedback from other
receivers will be faster received in that case. It can also be seen
that the feedback suppression rate increases with k. This is due to
the fact that T_dither_max increases with k. Thus the agents will
wait longer on the average before sending their feedback. By
increasing the waiting time for all agents, the time were feedback
suppression is possible at all is increased.
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| | Feedback Suppression Rate |
| k | Scen. 1 | Scen. 2 | Scen. 3 |
+------+---------+---------+---------+
| 0.10 | 0.070 | 0.039 | 0.064 |
| 0.25 | 0.068 | 0.063 | 0.065 |
| 0.50 | 0.062 | 0.114 | 0.124 |
| 0.75 | 0.047 | 0.172 | 0.129 |
| 1.00 | 0.056 | 0.234 | 0.176 |
| 1.25 | 0.056 | 0.282 | 0.233 |
| 1.50 | 0.047 | 0.315 | 0.251 |
| 1.75 | 0.040 | 0.331 | 0.245 |
| 2.00 | 0.048 | 0.297 | 0.284 |
| 3.00 | 0.047 | 0.347 | 0.330 |
| 4.00 | 0.063 | 0.347 | 0.353 |
Table 7: Fraction of feedback that was suppressed at agent An of the
total number of feedback the agent wanted to send
In Table 8 the results for the feedback suppression of agent Af are
depicted. Again we see that the number of feedback suppressions
increase with k. Only in scenario 1 the number is more or less
constant. However by increasing the waiting times, the probability
that the feedback is suppressed is decreased at agent Af. k=1 seems
to be a threshold, where the feedback suppression does not change
anymore significantly in the given scenarios. This is because for
the given parameters, the early packets will not be sent any more,
because the next regularly scheduled RTCP packet will we within the
T_dither_max interval.
| | Feedback Suppression Rate |
| k | Scen. 1 | Scen. 2 | Scen. 3 |
+------+---------+---------+---------+
| 0.10 | 0.736 | 0.064 | 0.071 |
| 0.25 | 0.814 | 0.079 | 0.119 |
| 0.50 | 0.859 | 0.162 | 0.239 |
| 0.75 | 0.865 | 0.222 | 0.376 |
| 1.00 | 0.844 | 0.290 | 0.401 |
| 1.25 | 0.850 | 0.338 | 0.429 |
| 1.50 | 0.849 | 0.316 | 0.473 |
| 1.75 | 0.868 | 0.316 | 0.505 |
| 2.00 | 0.843 | 0.376 | 0.487 |
| 3.00 | 0.845 | 0.345 | 0.502 |
| 4.00 | 0.820 | 0.345 | 0.493 |
Table 8 Fraction of feedback that was suppressed at agent Af of the
total number of feedback the agent wanted to send
In Table 9 the ration of feedback suppression failures is
illustrated. In general the observations from the figures above are
summarized. The ratio of feedback failures decreases with an
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increasing k for the scenarios 2 and 3. In scenario 1 the ratio is
hardly influenced at all by k. The simulations show a kind of steady
state at k larger two or three, where the rationale for this is that
for very large k, T_dither_max becomes equal or more than T_rr and
thus no early packets are send any more. The maximum dithering
interval is for these cases limited by the next regularly scheduled
RR.
| |Feedback Suppr. Failure Rate |
| k | Scen. 1 | Scen. 2 | Scen. 3 |
+------+---------+---------+---------+
| 0.10 | 0.194 | 0.897 | 0.865 |
| 0.25 | 0.117 | 0.858 | 0.816 |
| 0.50 | 0.079 | 0.725 | 0.638 |
| 0.75 | 0.088 | 0.606 | 0.495 |
| 1.00 | 0.100 | 0.468 | 0.423 |
| 1.25 | 0.094 | 0.381 | 0.338 |
| 1.50 | 0.104 | 0.369 | 0.276 |
| 1.75 | 0.092 | 0.353 | 0.250 |
| 2.00 | 0.110 | 0.328 | 0.229 |
| 3.00 | 0.108 | 0.308 | 0.169 |
| 4.00 | 0.116 | 0.308 | 0.154 |
Table 8: The ratio of feedback suppression failures.
Summarizing, it can be said, that the feedback suppression
performance is highly dependent on the topology, the parameters and
configurations.
In general a larger value for k increases the probability that the
feedback suppression works, however the performance gain decreases
with an increasing k. For a certain threshold, depending on the
configuration and environment, an increasing k does not lead to any
performance gain any more.
7.2 Loss Report Delay
In this section we investigate the influence of the parameter k on
the loss report delay. Therefore we measured for the three sample
scenarios the mean loss report delay as seen by the sender, i.e. the
sender calculates for every loss report, it receives for the first
time the delay since the corresponding packet was sent.
The results are depicted in Table 9. In general it can be said, that
the loss report delay increases with k. This is only natural,
because T_Dither_max is proportional to k. Thus the agents wait on
the average longer to send their early packets. In cases of very
large k values, the report delay does not increase significantly any
more. In these cases nearly no early packets are sent, because the
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next regularly scheduled packet is within the T_dither_max interval.
The threshold of k, from which on the delay will not increase, is
dependent on the RTT estimation. For increasing RTT values, the
threshold decreases. We see that in scenario 1 the threshold lies
between k=2 and k=3. For the scenarios with smaller RTT, the
threshold is higher.
Summarizing it can be said, that the report delay increases with an
increasing k. From a certain threshold the increase is not
significant, however this threshold is highly dependent on topology
and environment parameters.
| | Mean Loss Report Delay |
| k | Scen. 1 | Scen. 2 | Scen. 3 |
+------+---------+---------+---------+
| 0.10 | 0.128 | 0.282 | 0.431 |
| 0.25 | 0.135 | 0.266 | 0.430 |
| 0.50 | 0.150 | 0.264 | 0.497 |
| 0.75 | 0.160 | 0.286 | 0.538 |
| 1.00 | 0.194 | 0.305 | 0.613 |
| 1.25 | 0.203 | 0.329 | 0.661 |
| 1.50 | 0.208 | 0.363 | 0.690 |
| 1.75 | 0.209 | 0.387 | 0.739 |
| 2.00 | 0.242 | 0.412 | 0.764 |
| 3.00 | 0.243 | 0.507 | 0.790 |
| 4.00 | 0.287 | 0.568 | 0.790 |
Table 9: The mean loss report delay, measured at the sender.
7.3 Summary of "k" investigations
We have shown by simulations that the parameter k influence the
feedback performance. While in general the feedback suppression
performance increases with k, the report delay increases also. Hence
we need to find a tradeoff, between the amount of feedback that is
sent and the delay of the feedback, when it is received at the
sender. Since we have shown that the performance curves for the
feedback suppression as well as the report delay is highly variable
for different topologies and environments, it is not possible to
give an optimized parameter value for k. We think that k=1 is a
compromise, which should be acceptable for most of our considered
cases. At least we guarantee with k=1 that no feedback explosion
will occur and thus keep the network stability untouched.
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8 Investigations on "l"
In this section we want to investigate the influence of the
parameter "l" from the T_Dither_max calculation in agents that do
not have an RTT estimation to the sender. As we have done in the
previous section for the parameter "k", we investigate the feedback
suppression performance as well as the report delay for three sample
scenarios. For simplicity we use the same scenarios as in the
previous section, but this time the all agents beside agent A1 are
pure RTP receivers. Thus these agents do not have an RTT estimation
to the source. T_Dither_Max is calculated with the other formula,
depending only on T_rr and l, which means that all agents should
calculate roughly the same T_Dither_Max.
8.1 Feedback Suppression Performance
The results for the feedback suppression rate of the agent Af that
is more far away from the sender, are depicted in Table 10. In
general it can be seen that the feedback suppression rate increases
with an increasing l. However there is a threshold, depending on the
environment, from which the additional gain is not significant any
more.
| | Feedback Suppression Rate |
| l | Scen. 1 | Scen. 2 | Scen. 3 |
+------+---------+---------+---------+
| 0.10 | 0.671 | 0.051 | 0.089 |
| 0.25 | 0.582 | 0.060 | 0.210 |
| 0.50 | 0.524 | 0.114 | 0.361 |
| 0.75 | 0.523 | 0.180 | 0.370 |
| 1.00 | 0.523 | 0.204 | 0.369 |
| 1.25 | 0.506 | 0.187 | 0.372 |
| 1.50 | 0.536 | 0.213 | 0.414 |
| 1.75 | 0.526 | 0.215 | 0.424 |
| 2.00 | 0.535 | 0.216 | 0.400 |
| 3.00 | 0.522 | 0.220 | 0.405 |
| 4.00 | 0.522 | 0.220 | 0.405 |
Table 10: Fraction of feedback that was suppressed at agent An of
the total number of feedback the agent wanted to send
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Similar results can be seen for the agent that is nearer to the
sender in Table 11.
| | Feedback Suppression Rate |
| l | Scen. 1 | Scen. 2 | Scen. 3 |
+------+---------+---------+---------+
| 0.10 | 0.056 | 0.056 | 0.090 |
| 0.25 | 0.063 | 0.055 | 0.166 |
| 0.50 | 0.116 | 0.099 | 0.255 |
| 0.75 | 0.141 | 0.141 | 0.312 |
| 1.00 | 0.179 | 0.175 | 0.352 |
| 1.25 | 0.206 | 0.176 | 0.361 |
| 1.50 | 0.193 | 0.193 | 0.337 |
| 1.75 | 0.197 | 0.204 | 0.341 |
| 2.00 | 0.207 | 0.207 | 0.368 |
| 3.00 | 0.196 | 0.203 | 0.359 |
| 4.00 | 0.196 | 0.203 | 0.359 |
Table 11: Fraction of feedback that was suppressed at agent An of
the total number of feedback the agent wanted to send
The rate of feedback suppression failure is depicted in Table 12.
The trend that the additional performance increase is not
significant from a certain threshold, depending on the environment
is here as well visible.
| |Feedback Suppr. Failure Rate |
| l | Scen. 1 | Scen. 2 | Scen. 3 |
+------+---------+---------+---------+
| 0.10 | 0.273 | 0.893 | 0.822 |
| 0.25 | 0.355 | 0.885 | 0.624 |
| 0.50 | 0.364 | 0.787 | 0.385 |
| 0.75 | 0.334 | 0.679 | 0.318 |
| 1.00 | 0.298 | 0.621 | 0.279 |
| 1.25 | 0.289 | 0.637 | 0.267 |
| 1.50 | 0.274 | 0.595 | 0.249 |
| 1.75 | 0.274 | 0.580 | 0.235 |
| 2.00 | 0.258 | 0.577 | 0.233 |
| 3.00 | 0.282 | 0.577 | 0.236 |
| 4.00 | 0.282 | 0.577 | 0.236 |
Table 12: The ratio of feedback suppression failures.
Summarizing the feedback suppression results it can be said that in
general the feedback suppression performance increases with an
increasing l. However from a certain threshold, depending on
environment parameters such as propagation delays or session
bandwidth, the additional increase is not significant anymore.
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8.2 Loss Report Delay
In this section we show the results for the measured report delay
during the simulations of the three sample scenarios. This
measurement is a metric of the performance of the algorithms,
because the value of the feedback for the sender typically decreases
with the delay of its reception. The loss report delay is measured
as the time at the sender between sending a packet and receiving the
first corresponding loss report.
| | Mean Loss Report Delay |
| l | Scen. 1 | Scen. 2 | Scen. 3 |
+------+---------+---------+---------+
| 0.10 | 0.124 | 0.282 | 0.210 |
| 0.25 | 0.168 | 0.266 | 0.234 |
| 0.50 | 0.243 | 0.264 | 0.284 |
| 0.75 | 0.285 | 0.286 | 0.325 |
| 1.00 | 0.329 | 0.305 | 0.350 |
| 1.25 | 0.351 | 0.329 | 0.370 |
| 1.50 | 0.361 | 0.363 | 0.388 |
| 1.75 | 0.360 | 0.387 | 0.392 |
| 2.00 | 0.367 | 0.412 | 0.400 |
| 3.00 | 0.368 | 0.507 | 0.398 |
| 4.00 | 0.368 | 0.568 | 0.398 |
Table 13: The mean loss report delay, measured at the sender.
As can be seen from Table 13 the delay increases in general with an
increasing value of l. However a similar effect as for the feedback
suppression performance is visible: from a certain threshold, the
additional increase in delay is not significant anymore. The
threshold is environment dependent and seems to be related to the
threshold, where the feedback suppression gain would not increase
anymore.
8.3 Summary of "l" investigations
We have shown that theoretically the performance of the feedback
suppression mechanisms is increasing with an increasing value of l.
The same applies for the report delay, which increases also with an
increasing l. This leads to a threshold where both the performance
and the delay does not increase any further. The threshold is
environment dependent.
So finding an optimum value of l is not possible because it is
always a tradeoff between delay and feedback suppression
performance. With l=0.5 we think that a tradeoff was found that is
acceptable for typical applications and environments.
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9 Applications Using AVPF
NEWPRED is one of the error resilience tools, which is defined in
both ISO/IEC MPEG-4 visual part and ITU-T H.263. NEWPRED achieves
fast error recovery using feedback messages. We simulated the
behavior of NEWPRED in the network simulator environment as
described above and measured the waiting time statistics, in order
verify that the extended RTP profile for RTCP-based feedback
(AVPF)[1] is appropriate for the NEWPRED feedback messages.
Simulation results, which present in the following sections, show
that the waiting time is enough small to get the satisfactory
performance of NEWPRED.
9.1 NEWPRED Implementation in NS2
The agent that performs the NEWPRED functionality, called NEWPRED
agent, is different from the RTP agent we described above. Some of
the added features and functionalities are described in the
following points:
Application Feedback
The "Application Layer Feedback Messages" format is used to
transmit the NEWPRED feedback messages. Thereby the NEWPRED
functionality is added to the RTP agent. The NEWPRED agent creates
one NACK message for each lost segment of a video frame, and then
assembles plural number of NACK messages corresponding to the
segments in the same video frame, into one Application Layer
Feedback Message. Although there are two modes, namely NACK mode
and ACK mode in NEWPRED [6][7], only NACK mode is used in these
simulations.
The parameters of NEWPRED agent are as follows:
f: Frame Rate(frames/sec)
seg: Number of segments in one video frame
bw: RTP session bandwidth(kbps)
Generation of NEWPRED's NACK Messages
The NEWPRED agent generates NACK messages when segments are lost.
a. The NEWPRED agent generates plural number of NACK messages per
one video frame when plural number of segments are lost. These
are assembled into one FCI message per video frame. If there is
no lost segment, no message is generated and sent.
b. The length of one NACK message is 4 bytes. Let num be the
number of NACK messages in one video frame(1 <= num <= seg).
Thus, 12+4*num bytes is the size of the low delay RTCP feedback
message.
Measurements
We defined two values to be measured:
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- Recovery time
The recovery time is measured as the time between the detection
of a lost segment and reception of a recovered segment. We
measured this "recovery time" for each lost segment.
- Waiting time
The waiting time is the additional delay due to the feedback
limitation of RTP.
Fig.1 depicts the behavior of a NEWPRED agent when a loss occurs.
The recovery time is approximated as follows:
(Recovery time) = (Waiting time) +
(Transmission time for feedback message) +
(Transmission time for media data)
Therefore, the waiting time is derived as follows:
(Waiting time) = (Recovery time) - (Round-trip delay), where
(Round-trip delay ) = (Transmission time for feedback message) +
(Transmission time for media data)
Picture Reference |: Picture Segment
____________________ %: Lost Segment
/_ _ _ _ \
v/ \ / \ / \ / \ \
v \v \v \v \ \
Sender ---|----|----|----|----|----|---|------------->
\ \ ^ \
\ \ / \
\ \ / \
\ v / \
\ x / \
\ Lost / \
\ x / \ _____
v x / NACK v
Receiver ---------------|----%===-%----%----%----|----->
|-a-| |
|------- b -------|
a: Waiting time
b: Recover time (%: Video segments are lost)
Fig.1: Relation between the measured values at the NEWPRED agent
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9.2 Simulation
We conducted two simulations (Simulation A and Simulation B). In
Simulation A, the packets are dropped with a fixed packet loss rate
on a link between two NEWPRED agents. In Simulation B, packet loss
occurs due to congestion from other traffic sources, i.e. ftp
sessions.
9.2.1. Simulation A - Constant Packet Loss Rate
The network topology, used for this simulation is shown in Fig.2.
Link 1 Link 2 Link 3
+--------+ +------+ +------+ +--------+
| Sender |------|Router|-------|Router|------|Receiver|
+--------+ +------+ +------+ +--------+
10(msec) x(msec) 10(msec)
Fig2. Network topology that is used for Simulation A
Link1 and link3 are error free, and each link delay is 10 msec.
Packets may get dropped on link2. The packet loss rates (Plr) and
link delay (D) are as follows:
D [ms] = {10, 50, 100, 200, 500}
Plr = {0.005, 0.01, 0.02, 0.03, 0.05, 0.1, 0.2}
Session band width, frame rate and the number of segments are
shown in Table 14
+------------+----------+-------------+-----+
|Parameter ID| bw(kbps) |f (frame/sec)| seg |
+------------+----------+-------------+-----+
| 32k-4-3 | 32 | 4 | 3 |
| 32k-5-3 | 32 | 5 | 3 |
| 64k-5-3 | 64 | 5 | 3 |
| 64k-10-3 | 64 | 10 | 3 |
| 128k-10-6 | 128 | 10 | 6 |
| 128k-15-6 | 128 | 15 | 6 |
| 384k-15-6 | 384 | 15 | 6 |
| 384k-30-6 | 384 | 30 | 6 |
| 512k-30-6 | 512 | 30 | 6 |
| 1000k-30-9 | 1000 | 30 | 9 |
| 2000k-30-9 | 2000 | 30 | 9 |
+------------+----------+-------------+-----+
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Table 14: Parameter sets of the NEWPRED agents
Figure3 shows the packet loss rate vs. mean of waiting time. A
plotted line represents a parameter ID ( "[session bandwidth] -
[frame rate] - [the number of segments] - [link2 delay]" ).
E.g. 384k-15-9-100 means the session of 384kbps session bandwidth,
15 frames per second, 9 segments per frame and 100msec link delay.
When the packet loss rate is 5% and the session bandwidth is 32kbps,
the waiting time is around 400msec, which is just allowable for
reasonable NEWPRED performance.
When the packet loss rate is less than 1%, the waiting time is less
than 200msec. In such a case, the NEWPRED allows as much as 200msec
additional link delay.
When the packet loss rate is less than 5% and the session bandwidth
is 64kbps, the waiting time is also less than 200msec.
In 128kbps cases, the result shows that when the packet loss rate is
20%, the waiting time is around 200msec. In cases with more than
512kbps session bandwidth, there is no significant delay. This means
that the waiting time due to the feedback limitation of RTCP is
neglectable for the NEWPRED performance.
+------------------------------------------------------------+
| | Packet Loss Rate = |
| Bandwidth | 0.005| 0.01 | 0.02 | 0.03 | 0.05 |0.10 |0.20 |
|-----------+------+------+------+------+------+------+------|
| 32k |130- |200- |230- |280- |350- |470- |560- |
| | 180| 250| 320| 390| 430| 610| 780|
| 64k | 80- |100- |120- |150- |180- |210- |290- |
| | 130| 150| 180| 190| 210| 300| 400|
| 128k | 60- | 70- | 90- |110- |130- |170- |190- |
| | 70| 80| 100| 120| 140| 190| 240|
| 384k | 30- | 30- | 30- | 40- | 50- | 50- | 50- |
| | 50| 50| 50| 50| 60| 70| 90|
| 512k | < 50 | < 50 | < 50 | < 50 | < 50 | < 50 | < 60 |
| | | | | | | | |
| 1000k | < 50 | < 50 | < 50 | < 50 | < 50 | < 50 | < 55 |
| | | | | | | | |
| 2000k | < 30 | < 30 | < 30 | < 30 | < 30 | < 35 | < 35 |
+------------------+------+------+------+------+------+------+
Fig. 3 The result of simulation A
9.2.2. Simulation B - Packet Loss due to Congestion
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The configuration of link1, link2, and link3 are the same as in
simulation A except that link2 is also error-free, regarding bit
errors. However in addition, some FTP agents are deployed to
overload link2. See Figure 4 for the simulation topology.
Link1 Link2 Link3
+--------+ +------+ +------+ +--------+
| Sender |------|Router|-------|Router|------|Receiver|
+--------+ /|+------+ +------+|\ +--------+
+---+/ | | \+---+
+-|FTP|+---+ +---+|FTP|-+
| +---+|FTP| ... |FTP|+---+ | ...
+---+ +---+ +---+ +---+
FTP Agents FTP Agents
Fig4. Network Topology of Simulation B
The parameters are defined as for Simulation A with the following
values assigned:
D[ms] ={10, 50, 100, 200, 500}
32 FTP agents are deployed at each edge, and totally 64 FTP
agents are active.
The sets of session bandwidth, frame rate, the number of segments
are the same as in Simulation A (Table 14)
We provide the results for the cases of 64 FTP agents, because these
are the cases where packet losses could be detected stable. The
results are similar to the Simulation A except for a constant
additional offset of 50..100ms. This is due to the delay incurred by
the routers buffers.
9.3 Summary of Application Simulations
We have shown that the limitations of RTP AVPF profile do not
generate such high delay to the feedback messages that the
performance of NEWPRED is degraded in the sessions from 32kbps to
2Mbps. We could see that the waiting time increases with a
decreasing session bandwidth and/or an increasing packet loss rate.
Thereby it is not significant what the packet loss caused.
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Congestion or constant packet loss rates behave similar. Still we
see that for reasonable conditions and parameters the AVPF is well
suited to support the feedback needed for NEWPRED.
10 Summary
The new RTP profile AVPF was investigated regarding performance and
potential dangers to the network stability. Simulations were
conducted using the network simulator, simulating unicast and
different sized multicast topologies. The results were shown in this
document.
Regarding the network stability, it was important to show that the
new profile does not lead to any feedback explosion, or use more
bandwidth as it is allowed. Thus we measured the bandwidth that was
used for RTCP in relation to the RTP session bandwidth. We have
shown that more or less exactly 5% of the session bandwidth is used
for RTCP, in all considered scenarios. The scenarios included
unicast with and without bit errors, different sized multicast
groups, with and without errors or congestion on the links. Thus we
can say that the new profile behaves network friendly in that sense
that it uses only the allowed bandwidth that was assigned by RTP.
Second we have shown that receivers using the new profile experience
a performance gain. We have shown that especially RTP receiver that
do have an RTT estimation to the sender gain from using the new
profile. But also the other receivers could increase their
performance. This was measured by the delay that the sender sees for
the received feedback. Using the new profile this delay can be
decreased by orders of magnitude.
Third we investigated certain parameters of the new algorithms. We
have shown that there does not exist an optimum value for those. The
influence of the parameters is highly environment specific and a
tradeoff between performance of the feedback suppression algorithm
and the experienced delay has to be found. The values that are given
in the draft seem to be reasonable for most applications and
environments.
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References
[1] J.Ott, S.Wenger, S.Fukunaga, N.Sato, K.Yano, A.Miyazaki,
K.Hata, R.Hakenberg, C.Burmeister: Extended RTP Profile for
RTCP-based Feedback, Internet Draft,
draft-ietf-avt-rtcp-feedback-00.txt, Work in Progress,
July 2001.
[2] H.Schulzrinne, S.Casner, R.Frederick, and V.Jacobson:
RTP - A Transport Protocol for Real-time Applications,
Internet Draft, draft-ietf-avt-rtp-new-10.txt, Work in
Progress, July 2001.
[3] H.Schulzrinne, S.Casner: RTP Profile for Audio and Video
Conferences with Minimal Control, Internet Draft,
draft-ietf-avt-profile-new-11.txt, Work in Progress, July 2001.
[4] Network Simulator Version 2 - ns-2, available from
http://www.isi.edu/nsnam/ns
[5] C.Burmeister, T.Klinner: Low Delay Feedback RTCP - Timing Rules
Simulation Results. Technical Report of the Panasonic European
Laboratories, September 2001, available from
http://www.pel.panasonic.de/ietf/docs/SimulationResults-A.pdf
[6] ISO/IEC 14496-2:1999/Amd.1:2000, "Information technology -
Coding of audio-visual objects - Part2: Visual", July 2000.
[7] ITU-T Recommendation, H.263. Video encoding for low bitrate
communication. 1998.
[8] S. Fukunaga, T. Nakai, and H. Inoue, "Error Resilient Video
Coding by Dynamic Replacing of Reference Pictures," IEEE Global
Telecommunications Conference (GLOBECOM), pp.1503-1508, 1996.
[9] Hideaki Kimata, Yasuhiro Tomita, Hiroyuki Yamaguchi, Susumu
Ichinose, and Tadashi Ichikawa, "Receiver-Oriented Real-Time
Error Resilient Video Communication System: Adaptive Recovery
from Error Propagation in Accordance with Memory Size at
Receiver," Electronics and Communications in Japan, Part 1,
vol.84, no.2, pp.8-17, 2001.
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Authors Addresses
Carsten Burmeister
Panasonic European Laboratories GmbH
Monzastr. 4c, 63225 Langen, Germany
mailto:burmeister@panasonic.de
Rolf Hakenberg
Panasonic European Laboratories GmbH
Monzastr. 4c, 63225 Langen, Germany
mailto:hakenberg@panasonic.de
Akihiro Miyazaki
Matsushita Electric Industrial Co., Ltd
1006, Kadoma, Kadoma City, Osaka, Japan
mailto :akihiro@isl.mei.co.jp
J÷rg Ott
Universit„t Bremen TZI
MZH 5180, Bibliothekstr. 1, 28359 Bremen, Germany
{sip,mailto}:jo@tzi.uni-bremen.de
Noriyuki Sato
Oki Electric Industry Co., Ltd.
1-2-27 Shiromi, Chuo-ku, Osaka 540-6025 Japan
mailto:sato652@oki.co.jp
Shigeru Fukunaga
Oki Electric Industry Co., Ltd.
1-2-27 Shiromi, Chuo-ku, Osaka 540-6025 Japan
mailto:fukunaga444@oki.co.jp
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