Internet DRAFT - draft-huang-xrblock-rtcweb-rtcp-xr-metrics
draft-huang-xrblock-rtcweb-rtcp-xr-metrics
XR Block Working Group R. Huang
Internet-Draft R. Even
Intended status: Standards Track Huawei
Expires: January 5, 2015 V. Singh
Aalto University
D. Romascanu
Avaya
L. Deng
China Mobile
July 4, 2014
Considerations for Selecting RTCP Extended Report (XR) Metrics for the
RTCWEB Statistics API
draft-huang-xrblock-rtcweb-rtcp-xr-metrics-04
Abstract
This document describes monitoring features related to RTCWEB. It
provides a list of RTCP XR metrics, which are useful and may need to
be supported in some RTCWEB implementations. It also describes a
list of additional identifiers for WebRTC's statistics API. These
identifiers are a set of RTCP XR metrics related to the transport of
multimedia flows.
Status of This Memo
This Internet-Draft is submitted in full conformance with the
provisions of BCP 78 and BCP 79.
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This Internet-Draft will expire on January 5, 2015.
Copyright Notice
Copyright (c) 2014 IETF Trust and the persons identified as the
document authors. All rights reserved.
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Table of Contents
1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . 3
2. Terminology . . . . . . . . . . . . . . . . . . . . . . . . . 3
3. RTP Statistics in WebRTC Implementations . . . . . . . . . . 3
4. Considerations for Impact of Measurement Interval . . . . . . 4
5. Candidate Metrics . . . . . . . . . . . . . . . . . . . . . . 5
5.1. Network Impact Metrics . . . . . . . . . . . . . . . . . 5
5.1.1. Loss and Discard Packet Count Metric . . . . . . . . 5
5.1.2. Burst/Gap Pattern Metrics for Loss and Discard . . . 6
5.1.3. Run Length Encoded Metrics for Loss, Discard . . . . 7
5.2. Application Impact Metrics . . . . . . . . . . . . . . . 7
5.2.1. Discard Octets Metric . . . . . . . . . . . . . . . . 7
5.2.2. Frame Impairment Summary Metrics . . . . . . . . . . 7
5.2.3. Jitter Buffer Metrics . . . . . . . . . . . . . . . . 8
5.3. Recovery metrics . . . . . . . . . . . . . . . . . . . . 8
5.3.1. Post-repair Packet Count Metrics . . . . . . . . . . 9
5.3.2. Run Length Encoded Metric for Post-repair . . . . . . 9
6. Candidate XR Block Metrics for WebRTC Statistics API . . . . 9
6.1. Variables from XR Blocks . . . . . . . . . . . . . . . . 10
6.1.1. Packets and Octets Discarded . . . . . . . . . . . . 10
6.1.2. Cumulative Number of Packets Repaired . . . . . . . . 10
6.1.3. Burst Packet Loss or Discarded . . . . . . . . . . . 10
6.1.4. Frame Impairment Metrics . . . . . . . . . . . . . . 11
7. IANA Considerations . . . . . . . . . . . . . . . . . . . . . 11
8. Security Considerations . . . . . . . . . . . . . . . . . . . 11
9. Acknowledgements . . . . . . . . . . . . . . . . . . . . . . 11
10. References . . . . . . . . . . . . . . . . . . . . . . . . . 11
10.1. Normative References . . . . . . . . . . . . . . . . . . 12
10.2. Informative References . . . . . . . . . . . . . . . . . 13
Appendix A. Change Log . . . . . . . . . . . . . . . . . . . . . 13
A.1. changes in draft-huang-xrblock-rtcweb-rtcp-xr-metrics-04 14
Authors' Addresses . . . . . . . . . . . . . . . . . . . . . . . 14
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1. Introduction
Web-based real-time communication (WebRTC) deployments are emerging
and applications need to be able to estimate the service quality. If
sufficient information (metrics or statistics) are provided to the
applications, it can attempt to improve the media quality.
[I-D.ietf-rtcweb-use-cases-and-requirements] specifies a requirement
for statistics:
F38 The browser must be able to collect statistics, related to the
transport of audio and video between peers, needed to estimate
quality of experience.
The [I-D.alvestrand-rtcweb-stats-registry] describes a registration
procedure for metrics reported by the WebRTC Stats API
[W3C.WD-webrtc-20130910]. It currently lists basic metrics reported
in the RTCP Sender and Receiver Report (SR/RR) [RFC3550] to fulfill
this requirement. However, the basic metrics from RTCP SR/RR are not
sufficient for precise quality monitoring, or diagnosing potential
issues.
In this document, we provide some guidelines on choosing additional
RTP metrics for the WebRTC Stats API [W3C.WD-webrtc-20130910].
Furthermore, we expose additional RTCP XR metrics to complement the
identifiers that already exist in the statistics registry
[I-D.alvestrand-rtcweb-stats-registry].
2. Terminology
The key words "MUST", "MUST NOT", "REQUIRED", "SHALL", "SHALL NOT",
"SHOULD", "SHOULD NOT", "RECOMMENDED", "MAY", and "OPTIONAL" in this
document are to be interpreted as described in [RFC2119].
3. RTP Statistics in WebRTC Implementations
Currently, the statistics registry
[I-D.alvestrand-rtcweb-stats-registry] exposes the basic RTCP SR and
RR metrics for the local and remote media streams. The exposed
identifiers are: SentPacketCount, SentOctetCount, packetsLost,
Jitter, ReceivedPacketCount, ReceivedOctetCount. However, these
metrics provides only partial or limited information, which may not
be sufficient for diagnosing problems or quality monitoring. For
example, it may be useful to distinguish between packets lost and
packets discarded due to late arrival, even though they have the same
impact on the multimedia quality, it helps in diagnosing and
identifying issues.
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RTP Control Protocol Extended Reports [RFC3611] and other extensions
discussed in the XRBLOCK working group provide more detailed
statistics, which complement the basic metrics reported in the RTCP
Sender and Receiver Reports. Section Section 5 discusses the use of
XR metrics that may be useful for monitoring the performance of
WebRTC applications.
The WebRTC application extracts the statistic from the browser by
querying the Stats API [W3C.WD-webrtc-20130910], but the browser
currently only reports the local variables i.e., the statistics
related to the outgoing RTP media streams and the incoming RTP media
streams. Without the support of RTCP XRs or some other signaling
mechianism, the WebRTC application cannot expose the remote
endpoints' statistics. At the moment [I-D.ietf-rtcweb-rtp-usage]
does not mandate the use of any RTCP XRs and since their usage is
optional. If the use of RTCP XRs is successfully negotiated between
endpoints (via SDP), thereafter the application has access to both
local and remote statistics. Alternatively, once the WebRTC
application gets the local information, they can report it to an
application server or a third-party monitoring system, which provides
quality estimations or diagnosis services for application developers.
The exchange of statistics between endpoints or between a monitoring
server and an endpoint is outside the scope of this document.
4. Considerations for Impact of Measurement Interval
RTCP extensions like RTCP XR usually share the same timing interval
with the RTCP SR/RR, i.e., they are sent as compound packets,
together with the RTCP SR/RR. Alternatively, if the RTCP XR uses a
different measurement interval, all XRs using the same measurement
interval are compounded together and the measurement interval is
indicated in a specific measurement information block defined in
[RFC6776].
When using WebRTC Statistics APIs (see section 7 of
[W3C.WD-webrtc-20130910]), the applications can query this
information at arbitrary intervals. For the statistics reported by
the remote endpoint, e.g., those conveyed in an RTCP SR/RR/XR, these
will not change until the next RTCP report is received. Some
applications may choose 1 second or a different polling interval, but
the statistics from the remote endpoint may not change when using
intervals shorter than the average RTCP reporting interval. However,
statistics generated by the local endpoint have no such restrictions
as long as the endpoint is sending and receiving media.
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5. Candidate Metrics
Since following metrics are all defined in RTCP XR which is not
mandated in WebRTC, all of them are local. However, if RTCP XR is
supported by negotiation between two browsers, following metrics can
also be generated remotely and be sent to local by RTCP XR packets.
Following metrics are classified into 3 categories: network impact
metrics, application impact metrics and recovery metrics. Network
impact metrics are the statistics recording the information only for
network transmission. They are useful for network problem diagnosis.
Application impact metrics mainly collect the information in the
viewpoint of application, e.g., bitrate, frames rate or jitter
buffers. Recovery metrics reflect how well the repair mechanisms,
e.g. loss concealment, retransmission or FEC, perform. All of the 3
types of metrics are useful for quality estimations of services in
WebRTC implementations. WebRTC application can use these metrics to
better calculate MoS values or Media Delivery Index (MDI) for their
services.
5.1. Network Impact Metrics
5.1.1. Loss and Discard Packet Count Metric
In multimedia transport, packets which are received abnormally are
classified into 3 types: lost, discarded and duplicate packets.
Packet loss may be caused by network device breakdown, bit-error
corruption or network congestion (packets dropped by an intermediate
router queue). Duplicate packets may be a result of network delays,
which causes the sender to retransmit the original packets.
Discarded packets are packets that have been delayed long enough
(perhaps they missed the playout time) and are considered useless by
the receiver. Lost and discarded packets cause problems for
multimedia services, as missing data and long delays can cause
degradation in service quality, e.g., missing large blocks of
contiguous packets (lost or discarded) may cause choppy audio, and
long network transmission delay time may cause audio or video
buffering. The RTCP SR/RR defines a metric for counting the total
number of RTP data packets that have been lost since the beginning of
reception. But this statistic does not distinguish lost packets from
discarded and duplicate packets. Packets that arrive late will be
discarded and are not reported as lost, and duplicate packets will be
regarded as a normally received packet. Hence, the loss metric can
be misleading if many duplicate packets are received or packets are
discarded, which causes the quality of the media transport to appear
okay from the statistic point of view, but meanwhile the users may
actually be experiencing bad service quality. So in such cases, it
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is better to use more accurate metrics in addition to those defined
in RTCP SR/RR.
The lost packets and duplicated packets metrics defined in Statistics
Summary Report Block of [RFC3611] extend the information of loss
carried in standard RTCP SR/RR. They explicitly give an account of
lost and duplicated packets. Lost packets counts are useful for
network problem diagnosis. It is better to use the loss packets
metrics of [RFC3611] to indicate the packet lost count instead of the
cumulative number of packets lost metric of [RFC3550]. Duplicated
packets are usually rare and have little effect on QoS evaluation.
So it may not be suitable for use in WebRTC.
Using loss metrics without considering discard metrics may result in
inaccurate quality evaluation, as packet discard due to jitter is
often more prevalent than packet loss in modern IP networks. The
discarded metric specified in [RFC7002] counts the number of packets
discarded due to the jitter. It augments the loss statistics metrics
specified in standard RTCP SR/RR. For those RTCWEB services with
jitter buffer requiring precise quality evaluation and accurate
troubleshooting, this metric is useful as a complement to the metrics
of RTCP SR/RR.
5.1.2. Burst/Gap Pattern Metrics for Loss and Discard
RTCP SR/RR defines coarse metrics regarding loss statistics, the
metrics are all about per call statistics and are not detailed enough
to capture some transitory nature of the impairments like bursty
packet loss. Even if the average packet loss rate is low, the lost
packets may occur during short dense periods, resulting in short
periods of degraded quality. Distributed burst provides a higher
subjective quality than a non-burst distribution for low packet loss
rates whereas for high packet loss rates the converse is true. So
capturing burst gap information is very helpful for quality
evaluation and locating impairments. If the WebRTC application needs
to evaluate the services quality, burst gap metrics provides more
accurate information than RTCP SR/RR.
[RFC3611] introduces burst gap metrics in VoIP report block. These
metrics record the density and duration of burst and gap periods,
which are helpful in isolating network problems since bursts
correspond to periods of time during which the packet loss/discard
rate is high enough to produce noticeable degradation in audio or
video quality. Burst gap related metrics are also introduced in
[RFC7003] and [RFC6958] which define two new report blocks for usage
in a range of RTP applications beyond those described in [RFC3611].
These metrics distinguish discarded packets from loss packets that
occur in the bursts period and provides more information for
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diagnosing network problems. Additionally, the block reports the
frequency of burst events which is useful information for evaluating
the quality of experience. Hence, if WebRTC application need to do
quality evaluation and observe when and why quality degrades, these
metrics should be considered.
5.1.3. Run Length Encoded Metrics for Loss, Discard
Run-length encoding uses a bit vector to encode information about the
packet. Each bit in the vector represents a packet and depending on
the signaled metric it defines if the packet was lost, duplicated,
discarded, or repaired. An endpoint typically uses the run length
encoding to accurately communicate the status of each packet in the
interval to the other endpoint. [RFC3611], [RFC7097] define run-
length encoding for lost and duplicate packets, and discarded
packets, respectively.
The WebRTC application could benefit from the additional information.
If losses occur after discards, an endpoint may be able to correlate
the two run length vectors to identify congestion-related losses,
i.e., a router queue became overloaded causing delays and then
overflowed. If the losses are independent, it may indicate bit-error
corruption. For the WebRTC StatsAPI, these types of metrics are not
recommended for use due to the large amount of data and the
computation involved.
5.2. Application Impact Metrics
5.2.1. Discard Octets Metric
The metric reports the cumulative size of the packets discarded in
the interval, it is complementary to number of discarded packets. An
application measures sent octets and received octets to calculate
sending rate and receiving rate, respectively. The application can
calculate the actual bitrate in a particular interval by subtracting
the discarded octets from the received octets.
For WebRTC, discarded octets supplements the sent and received octets
and provides an accurate method for calculating the actual bitrate
which is an important parameter to reflect the quality of the media.
The discarded bytes metric is defined in [RFC7243].
5.2.2. Frame Impairment Summary Metrics
RTP has different framing mechanisms for different payload types.
For audio streams, a single RTP packet may contain one or multiple
audio frames, each of which has a fixed length. On the other hand,
in video streams, a single video frame may be transmitted in multiple
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RTP packets. The size of each packet is limited by the Maximum
Transmission Unit (MTU) of the underlying network. However,
statistics from standard SR/RR only collect information from
transport layer, which may not fully reflect the quality observed by
the application. Video is typically encoded using two frame types
i.e., key frames and derived frames. Key frames are normally just
spatially compressed, i.e., without prediction from other pictures.
The derived frames are temporally compressed, i.e., depend on the key
frame for decoding. Hence, Key frames are much larger in size than
derived frames. The loss of these key frames results in a
substantial reduction in video quality. Thus it is reasonable to
consider this application layer information in WebRTC
implementations, which influence sender strategies to mitigate the
problem or require the accurate assessment of users' quality of
experience.
The following metrics can also be considered for WebRTC's Statistics
API: number of discarded key frames, number of lost key frames,
number of discarded derived frames, number of lost derived frames.
These metrics can be used to calculate Media Loss Rate (MLR) of MDI.
Details of the definition of these metrics are described in
[RFC7003]. Additionally, the metric provides the rendered frame
rate, an important parameter for quality estimation.
5.2.3. Jitter Buffer Metrics
The size of the jitter buffer affects the end-to-end delay on the
network and also the packet discard rate. When the buffer size is
too small, slower packets are not played out and dropped, while when
the buffer size is too large, packets are held longer than necessary
and consequently reduce conversational quality. Measurement of
jitter buffer should not be ignored in the evaluation of end user
perception of conversational quality. Jitter buffer related metrics,
such as maximum and nominal jitter buffer, could be used to show how
the jitter buffer behaves at the receiving endpoint. They are useful
for providing better end-user quality of experience (QoE) when jitter
buffer factors are used as inputs to calculate MoS values. Thus for
those cases, jitter buffer metrics should be considered. The
definition of these metrics is provided in [RFC7005].
5.3. Recovery metrics
[Editor's Note: Concealment Metrics are currently not considered.]
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5.3.1. Post-repair Packet Count Metrics
Error-resilience mechanisms, like RTP retransmission or FEC, are
optional in RTCWEB because the overhead of the repair bits adding to
the original streams. But they do help to greatly reduce the impact
of packet loss and enhance the quality of transmission. Web
applications could support certain repair mechanism after negotiation
between both sides of browsers when needed. For these web
applications using repair mechanisms, providing some statistic
information for the performance of their repair mechanisms could help
to have a more accurate quality evaluation.
The un-repaired packets count and repaired loss count defined in
[I-D.ietf-xrblock-rtcp-xr-post-repair-loss-count] provide the
recovery information of the error-resilience mechanisms to the
monitoring application or the sending endpoint. The endpoint can use
these metrics to ascertain the ratio of repaired packets to lost
packets. Including this kind of metrics helps the application
evaluate the effectiveness of the applied repair mechanisms.
5.3.2. Run Length Encoded Metric for Post-repair
[RFC5725] defines run-length encoding for post-repair packets. When
using error-resilience mechanisms, the endpoint can correlate the
loss run length with this metric to ascertain where the losses and
repairs occurred in the interval. This provides more accurate
information for recovery mechanisms evaluation than those in
Section 5.3.1. However, it is not suggested to use due to their
enormous amount of data when RTCP XR are supported.
For WebRTC, the application may benefit from the additional
information. If losses occur after discards, an endpoint may be able
to correlate the two run length vectors to identify congestion-
related losses, i.e., a router queue became overloaded causing delays
and then overflowed. If the losses are independent, it may indicate
bit-error corruption. Lastly, when using error-resilience
mechanisms, the endpoint can correlate the loss and post-repair run
lengths to ascertain where the losses and repairs occurred in the
interval. For example, consecutive losses are likely not to be
repaired by a simple FEC scheme.
6. Candidate XR Block Metrics for WebRTC Statistics API
This document describes a list of additional identifiers to
complement the identifiers in Section 4.1 of
[I-D.alvestrand-rtcweb-stats-registry] and these group of identifiers
are defined on a ReportGroup corresponding to an SSRC. In practice
the application MUST be able to query the statistic identifiers on
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both an incoming (remote) and outgoing (local) media stream.
Depending on the support of the corresponding XR report the endpoint
MAY be able to query the reception statistics for its outgoing
(local) media stream.
The following contact information is used for all registrations in
this document:
Contact: Varun Singh
mailto:varun.singh@iki.fi
tel:+358-9-470-24785
6.1. Variables from XR Blocks
6.1.1. Packets and Octets Discarded
Name: PacketsDiscarded
Definition: Cumulative Number of RTP packets discarded due to late or
early-arrival, Appendix A (a) of [RFC7002].
Name: OctetsDiscarded
Definition: Cumulative Number of octets discarded due to late or
early-arrival, Appendix A of [RFC7243]
6.1.2. Cumulative Number of Packets Repaired
Name: PacketsRepaired
Definition: The cumulative number of lost RTP packets repaired after
applying a error-resilience mechanism, Appendix A (b) of
[I-D.ietf-xrblock-rtcp-xr-post-repair-loss-count]. To clarify, the
value is upper bound to the cumulative number of lost packets.
6.1.3. Burst Packet Loss or Discarded
Name: BurstPacketDiscarded
Definition: The total number of RTP packets discarded during discard
bursts, Appendix A (b) of [RFC7003].
Name: BurstPacketLost
Definition: The total number of RTP packets lost during loss bursts,
Appendix A (c) of [RFC6958].
Name: BurstCount
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Definition: The cumulative number of bursts of lost RTP packets,
Appendix A (e) of [RFC6958].
[RFC3611] recommends a Gmin value of 16.
6.1.4. Frame Impairment Metrics
Name: FullFramesLostCount
Definition: Number of full frames lost, Appendix A (i) of [RFC7004]
Name: PartialFramesLostCount
Definition: Number of frames partially lost, Appendix A (j) of
[RFC7004]
Name: FramesDiscardedCount
Definition: Number of full frames discarded, Appendix A (g) of
[RFC7004]
7. IANA Considerations
This document requests IANA to update the registry described in
[I-D.alvestrand-rtcweb-stats-registry] with the identifiers defined
in Section 6.
8. Security Considerations
The monitoring activities are implemented between two browsers or
between a browser and a server. Therefore encryption procedures,
such as the ones suggested for a Secure RTCP (SRTCP), need to be
used. Currently, the monitoring in RTCWEB introduces no new security
considerations beyond those described in [I-D.ietf-rtcweb-rtp-usage],
[I-D.ietf-rtcweb-security], and
[I-D.alvestrand-rtcweb-stats-registry].
9. Acknowledgements
The authors would like to thank Bernard Aboba , Al Morton , Colin
Perkins , and Shida Schubert , for their valuable comments and
suggestions on earlier version of this document.
10. References
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10.1. Normative References
[RFC2119] Bradner, S., "Key words for use in RFCs to Indicate
Requirement Levels", BCP 14, RFC 2119, March 1997.
[I-D.alvestrand-rtcweb-stats-registry]
Alvestrand, H., "A Registry for WebRTC statistics
identifiers", draft-alvestrand-rtcweb-stats-registry-00
(work in progress), September 2012.
[RFC3550] Schulzrinne, H., Casner, S., Frederick, R., and V.
Jacobson, "RTP: A Transport Protocol for Real-Time
Applications", STD 64, RFC 3550, July 2003.
[RFC3611] Friedman, T., Caceres, R., and A. Clark, "RTP Control
Protocol Extended Reports (RTCP XR)", RFC 3611, November
2003.
[RFC4588] Rey, J., Leon, D., Miyazaki, A., Varsa, V., and R.
Hakenberg, "RTP Retransmission Payload Format", RFC 4588,
July 2006.
[RFC5725] Begen, A., Hsu, D., and M. Lague, "Post-Repair Loss RLE
Report Block Type for RTP Control Protocol (RTCP) Extended
Reports (XRs)", RFC 5725, February 2010.
[RFC6776] Clark, A. and Q. Wu, "Measurement Identity and Information
Reporting Using a Source Description (SDES) Item and an
RTCP Extended Report (XR) Block", RFC 6776, October 2012.
[RFC6958] Clark, A., Zhang, S., Zhao, J., and Q. Wu, "RTP Control
Protocol (RTCP) Extended Report (XR) Block for Burst/Gap
Loss Metric Reporting", RFC 6958, May 2013.
[RFC7002] Clark, A., Zorn, G., and Q. Wu, "RTP Control Protocol
(RTCP) Extended Report (XR) Block for Discard Count Metric
Reporting", RFC 7002, September 2013.
[RFC7003] Clark, A., Huang, R., and Q. Wu, "RTP Control Protocol
(RTCP) Extended Report (XR) Block for Burst/Gap Discard
Metric Reporting", RFC 7003, September 2013.
[RFC7004] Zorn, G., Schott, R., Wu, Q., and R. Huang, "RTP Control
Protocol (RTCP) Extended Report (XR) Blocks for Summary
Statistics Metrics Reporting", RFC 7004, September 2013.
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[RFC7005] Clark, A., Singh, V., and Q. Wu, "RTP Control Protocol
(RTCP) Extended Report (XR) Block for De-Jitter Buffer
Metric Reporting", RFC 7005, September 2013.
[RFC7097] Ott, J., Singh, V., and I. Curcio, "RTP Control Protocol
(RTCP) Extended Report (XR) for RLE of Discarded Packets",
RFC 7097, January 2014.
[RFC7243] Singh, V., Ott, J., and I. Curcio, "RTP Control Protocol
(RTCP) Extended Report (XR) Block for the Bytes Discarded
Metric", RFC 7243, May 2014.
[I-D.ietf-xrblock-rtcp-xr-post-repair-loss-count]
Huang, R. and V. Singh, "RTP Control Protocol (RTCP)
Extended Report (XR) for Post-Repair Loss Count Metrics",
draft-ietf-xrblock-rtcp-xr-post-repair-loss-count-05 (work
in progress), June 2014.
10.2. Informative References
[I-D.ietf-rtcweb-use-cases-and-requirements]
Holmberg, C., Hakansson, S., and G. Eriksson, "Web Real-
Time Communication Use-cases and Requirements", draft-
ietf-rtcweb-use-cases-and-requirements-14 (work in
progress), February 2014.
[W3C.WD-webrtc-20130910]
Bergkvist, A., Burnett, D., Jennings, C., and A.
Narayanan, "WebRTC 1.0: Real-time Communication Between
Browsers", World Wide Web Consortium WD WD-
webrtc-20130910, September 2013,
<http://www.w3.org/TR/2013/WD-webrtc-20130910>.
[I-D.ietf-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-15 (work in progress), May
2014.
[I-D.ietf-rtcweb-security]
Rescorla, E., "Security Considerations for WebRTC", draft-
ietf-rtcweb-security-06 (work in progress), January 2014.
Appendix A. Change Log
Note to the RFC-Editor: please remove this section prior to
publication as an RFC.
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A.1. changes in draft-huang-xrblock-rtcweb-rtcp-xr-metrics-04
o Addressed comments from the London IETF meeting:
o Removed ECN metrics.
o Merged draft-singh-xrblock-webrtc-additional-stats-01
Authors' Addresses
Rachel Huang
Huawei
101 Software Avenue, Yuhua District
Nanjing, CN 210012
China
Email: rachel.huang@huawei.com
Roni Even
Huawei
14 David Hamelech
Tel Aviv 64953
Israel
Email: roni.even@mail01.huawei.com
Varun Singh
Aalto University
School of Electrical Engineering
Otakaari 5 A
Espoo, FIN 02150
Finland
Email: varun@comnet.tkk.fi
URI: http://www.netlab.tkk.fi/~varun/
Dan Romascanu
Avaya
Park Atidim, Bldg. #3
Tel Aviv 61581
Israel
Email: dromasca@avaya.com
Huang, et al. Expires January 5, 2015 [Page 14]
Internet-Draft RTCP XR Metrics for RTCWEB July 2014
Lingli Deng
China Mobile
Email: denglingli@chinamobile.com
Huang, et al. Expires January 5, 2015 [Page 15]