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Saamer Akhshabi, Constantine Dovrolis Georgia Institute of Technology An Experimental Evaluation of Rate Adaptation Algorithms in Adaptive Video Streaming.

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Presentation on theme: "Saamer Akhshabi, Constantine Dovrolis Georgia Institute of Technology An Experimental Evaluation of Rate Adaptation Algorithms in Adaptive Video Streaming."— Presentation transcript:

1 Saamer Akhshabi, Constantine Dovrolis Georgia Institute of Technology An Experimental Evaluation of Rate Adaptation Algorithms in Adaptive Video Streaming over HTTP Ali C. Begen Cisco Systems February 3, 2011

2 Outline Overview of adaptive video streaming Experimental methodology Rate adaptation under available bw variations Smooth Streaming player Netflix player OSMF player Live streaming Competition between multiple players Conclusions

3 Outline Overview of adaptive video streaming Experimental methodology Rate adaptation under available bw variations Smooth Streaming player Netflix player OSMF player Live streaming Competition between multiple players Conclusions

4 Other Video Streaming Approaches HTTP Progressive Download

5 RTSP and RTP Other Video Streaming Approaches

6 RTMP Other Video Streaming Approaches

7 Several players support it Several commercial content providers use it Microsoft Smooth Streaming Player Netflix Player Adobe OSMF/Zeri Player Apple Player Adaptive video streaming over HTTP

8 HTTP Adaptive Video Streaming

9 HTTP Adaptive Video Streaming: Manifest File and Fragments

10 HTTP Adaptive Video Streaming: HTTP Request and Response

11 Outline Overview of adaptive video streaming Experimental methodology Rate adaptation under available bw variations Smooth Streaming player Netflix player OSMF player Live streaming Competition between multiple players Conclusions

12 Objectives Examine how commercial adaptive players react to available bw variations Persistent variations Short-term variations (spikes) We control the available bw using Dummynet In parallel, we collect packet traces at the player Identify requested bitrates & measure throughput Also, we estimate playback buffer size (in seconds) Use fragment timestamps (explained later)

13 Experimental Methodology

14 Outline Overview of adaptive video streaming Experimental methodology Rate adaptation under available bw variations Smooth Streaming player Netflix player OSMF player Live streaming Competition between multiple players Conclusions

15 Smooth Streaming Player

16 Sample HTTP Request: GET /mediadl/iisnet/smoothmedia/Experience/BigBuckBunny720 p.ism/QualityLevels( )/Fragments(video= ) HTTP/1.1

17 Smooth Streaming Player Buffering and Steady State One fragment per HTTP request No HTTP pipelining Two states: 1.Buffering state Request fragments as fast as possible 2.Steady-state Request new fragment every T seconds

18 Smooth Streaming Player Behavior under Unrestricted Available Bandwidth Average throughput: running average of instantaneous 2-sec TCP throughput measurements. Fragment throughput: per-fragment throughput measurement

19 Smooth Streaming Player Behavior under Unrestricted Available Bandwidth Two successive, say video, requests sent at times t 1 and t 2 (t 1

20 Smooth Streaming Player Notice: Important variation in fragment sizes The video fragment size varies considerably (VBR encoding) The rate can vary widely around the nominal bitrate (2.75 Mbps) This can be a significant problem for adaptive video streaming!

21 Smooth Streaming Player Behavior under persistent changes in available bandwidth Rate adaptation occurs after long delays The player estimates available bw using a running average of the per-fragment TCP throughput measurements

22 Smooth Streaming Player Playback buffer size under persistent changes in the available bandwidth Playback buffer size decreases when available bandwidth is less than the requested bitrate Playback buffer size increases when player goes into “buffering state” requesting fragments as fast as possible Together with switching to bitrate < available bw

23 The client reacts to some of the spikes by switching to lower bitrate too late Stays at that bitrate for long after the spike has passed Smooth Streaming Player Behavior under short term available bandwidth variations (negative spikes)

24 Outline Overview of adaptive video streaming Experimental methodology Rate adaptation under available bw variations Smooth Streaming player Netflix player OSMF player Live streaming Competition between multiple players Conclusions

25 Netflix Player

26 Sample HTTP Request: GET /sa2/946/ wmv/range/ ?token= \_d6f f1fb6 0cc48eab59ea55\&random= HTTP/1.1

27 NetflixPlayer Behavior under Unrestriced Available Bandwidth Player accumulates 5-min playback buffer!

28 Netflix Player Behavior under persistent changes in the available bandwidth Initially, the player requests fragments at all possible bitrates Occasionally, the player requests higher bitrate than available bw! Utilize large playback buffer size to optimize video quality

29 Smooth Streaming Player Behavior under short term available bandwidth variation with positive spikes Netflix appears to be more aggressive than Smooth Streaming in requesting higher bitrates

30 Outline Overview of adaptive video streaming Experimental methodology Rate adaptation under available bw variations Smooth Streaming player Netflix player OSMF player Live streaming Competition between multiple players Conclusions

31 Adobe OSMF/Zeri Player

32 Adobe OSMF Player Sample HTTP Request: GET /content/inoutedit-mbr/inoutedit\_h264\_3000Seg1- Frag5 HTTP/1.1

33 OSMF Player Behavior under persistent changes in the available bandwidth The client fails to select highest possible bitrate for the given available bw

34 OSMF Player Behavior under persistent changes in the available bandwidth Also, player often oscillates between bitrates Mostly lowest and highest bitrates

35 Outline Overview of adaptive video streaming Experimental methodology Rate adaptation under available bw variations Smooth Streaming player Netflix player OSMF player Live streaming Competition between multiple players Conclusions

36 Smooth Live Streaming No major differences with on-demand streaming Player starts streaming with 8-seconds delay CableTV networks often use 7-second “profanity delay”

37 Smooth Live Streaming Buffer Fill Level Playback delay increases over time whenever playback buffer gets empty Player does not skip fragments

38 Outline Overview of adaptive video streaming Experimental methodology Rate adaptation under available bw variations Smooth Streaming player Netflix player OSMF player Live streaming Competition between multiple players Conclusions

39 Two Smooth Streaming players compete Players keep oscillating between rates even when available bw is constant Synchronization can cause simultaneous bitrate drops

40 Two Smooth Streaming players compete Fairness issue: one stream may get much lower bitrate than the other

41 Outline Overview of adaptive video streaming Experimental methodology Rate adaptation under available bw variations Smooth Streaming player Netflix player OSMF player Live streaming Competition between multiple players Conclusions and future work

42 Summary of the key differences between players Smooth Streaming player Playback buffer size of 10s of seconds Conservative in selecting bitrate (< available bw) Netflix player Playback buffer size of few minutes More aggressive than Smooth player (often > available bw) Zeri player Erratic bitrate selection Under Development (?)

43 Weaknesses in adaptation logic Smooth Streaming player Large delay in responding to persistent available bw variations Erratic rate adaptations under short-term variations Oscillations and unfairness when multiple players compete Netflix player Large delay in responding to persistent available bw variations Erratic rate adaptations under short-term variations Requires large playback buffer Zeri player Adaptation logic seems broken

44 Future Work Continue the analysis of commercial players to understand how they work And identify weaknesses Expand study of multi-player competition Design and implement an adaptive steaming adaptation logic that can address all previous issues


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