1 Measuring Congestion Responsiveness of Windows Streaming Media James Nichols Advisors: Prof. Mark Claypool Prof. Bob Kinicki Reader: Prof. David Finkel Thesis Presentation PEDS - 12/8/03

2 Network Impact of Streaming Media Unlike file transfer or Web browsing, Streaming Media has specific bitrate and timing requirements. Typically, UDP is the default network transport protocol for delivering Streaming Media. UDP does not have any end-to-end congestion control mechanisms.

3 The Dangers of Unresponsiveness Flows in the network which are unresponsive to congestion can cause several undesirable situations: Unfairness when competing with responsive flows for limited resources Unresponsive flows can contribute to congestion collapse Some Streaming Media applications use UDP, but rely on the application layer to provide adaptability to available capacity Performance of these application layer mechanisms is unknown

4 Intelligent Streaming Application layer mechanism of Windows Streaming Media (WSM) to adapt to network conditions Can “thin” streams by sending fewer frames If the content producer has encoded multiple bitrates into the stream, IS can choose an appropriate one Chung et al. suggests that technologies like IS may provide responsiveness to congestion, even TCP-friendliness Performance of Intelligent Streaming is unknown

5 Research Goals No measurement studies have been completed where researchers had total control over: The streaming server Content-encoding parameters Network conditions at or close to the server We seek to characterize the bitrate response function of Windows Streaming Media in response to congestion in the network. Want to precisely quantify relationship between content encoding rate and performance.

6 Outline Introduction Related Work  Methodology Results & Analysis Conclusions Future Work

7 Related Work Some research has been done in the general area of Streaming Media: Traffic characterization studies [VAM+02, dMSK02] performed through log analysis Empirical studies using custom tools [CCZ03, WCZ01, LCK02] Characterization of streaming content available on the Web [MediaCrawler] None had control of the server, client, and network conditions

8 Need control over the server Not having server limits possible data set of content to study For example, [LCK02], measured IP packet fragmentation when streaming WSM clips but packet size can be tuned server-side Other research [CCZ03] had to stream over the public Internet while measuring network performance

9 Outline Introduction Related Work Methodology  Results & Analysis Conclusions Future Work

10 Methodology Construct testbed Create/adapt tools Encode content Systematic control Examine SBR clip Range of SBR clips MBR clips Vary loss and latency

11 Results and Analysis Single Bitrate Clip

12 Experiments Single bitrate (SBR) clip in detail  Range of SBR clips Multiple bitrate (MBR) clips Additional experiments performed but not discussed here

13 Single Bitrate Clip Experiment Hypothesis: SBR clips are unresponsive to congestion Latency: 45 ms Induced loss: 0% Bottleneck capacity: 725 Kbps Start a TCP flow through the link 10 Seconds later stream a WSM clip Measure achieved bitrates and loss rates for each flow

Kbps Clip - Bottleneck Capacity 725 Kbps < packet loss After 15 seconds TCP- Friendly?

Kbps Clip - Bottleneck Capacity 725 Kbps ~ packet loss for WSM ~ packet loss for TCP after 15 seconds Not TCP- Friendly!

Kbps Clip - Bottleneck Capacity 725 Kbps Responsive!

17 Network Topology

18 Measuring Buffering Performance Parse packet capture for RTSP PLAY message Examine MediaTracker output and measure how long it took from the start of streaming to when the buffer is reported to be full PLAY + interval = buffering period

19 Experiments SBR clip in detail Range of SBR clips  MBR clips

20 Comparison of Single Bitrate Clips Want to precisely quantify relationship between content encoding rate and performance Repeat the previous experiment, but for a range of single bitrate clips: 28, 43, 58, 109, 148, 282, 340, 548, 764, 1128 Kbps Vary network capacity: 250, 750, 1500 Kbps Measure performance during and after buffering

21 SBR Clips - Bottleneck Capacity 725 Kbps Buffering Period

22 SBR Clips - Bottleneck Capacity 725 Kbps Playout Period

23 Results and Analysis Multiple Bitrate Clips

24 Multiple Bitrate Clips Hypothesis: Multiple Bitrates make WSM more responsive to congestion Same experiment as before, but with different encoded content Vary network capacity: 250, 725, 1500 Kbps Created two sets of 10 multiple bitrate clips Experiments with lots of other MBR clips

25 Multiple Bitrate Content First set of clips (adding lower): 1128 Kbps Kbps Kbps … Kbps Second set of clips (adding higher): 28 Kbps Kbps Kbps … Kbps

26 Adding lower bitrates to clip Kbps Bottleneck Capacity - Buffering Period

27 Adding lower bitrates to clip Kbps Bottleneck Capacity - Playout Period

28 Adding lower bitrates to clip Kbps Bottleneck Capacity BufferingPlayout

29 Adding higher bitrates to clip Kbps Bottleneck Capacity BufferingPlayout

30 Additional experiments Not enough time to discuss all the results Different bottleneck capacities Carefully choose 2 or 3 bitrates to include in MBR clips Vary loss rate Vary latencies Also look at other network level metrics: interarrival times, burst lengths, and IP fragmentation

31 Conclusions Prominent buffering period means WSM cannot be modeled as a simple CBR flow WSM single bitrate clips: During buffering WSM responds to capacity only when the encoding rate is less than capacity Otherwise, high loss rates are induced During playout WSM responds to available capacity Thin if necessary If rate is less then capacity, will still be responsive to high loss rates (5%)

32 Conclusions WSM multiple bitrate clips: During buffering WSM responds to capacity only when content contains a suitable bitrate to choose Chosen bitrate is largest that capacity allows Otherwise, still tries to fit the smallest available, again resulting in high amounts of loss During playout WSM is responsive to available capacity Either because it chose the proper rate, or because it thins if proper rate isn’t encoded in clip However, the chosen bitrate probably isn’t fair to TCP

33 Future Work Run the same experiments with other streaming technologies: RealVideo and Quicktime Examine the effects of different content types Build NS simulation model of streaming media for use in future research

34 Questions