1. 1 / 21 Network Characteristics of Video Streaming Traffic Ashwin Rao †, Yeon-sup Lim *, Chadi Barakat †, Arnaud Legout †, Don Towsley *, and Walid Dabbous † † INRIA Sophia Antipolis France * University of Massachusetts Amherst, USA

2. 2 / 21 Video Streaming Services Containers Desktop BrowsersNative Mobile Applications What are the Network Characteristics of Video Streaming Traffic?

3. 3 / 21 Objective What exactly happens during video streaming? –Arrival of data packets –Strategies to stream videos –Potential Impact

4. 4 / 21 Introduction and Motivation Datasets and Measurement Techniques Streaming Strategies Impact of Streaming Strategies Outline

5. 5 / 21 Datasets YouTube videos –Flash, HTML5, and HD (Flash) –Mobile Netflix videos - Silverlight –Desktop –Mobile

6. 6 / 21 Measurement Technique 802.11 Packet Capture

7. 7 / 21 Measurement Locations France –Academic (Wired; Wi-fi for mobile) –Residential (Wi-fi) USA –Academic (Wired; Wi-fi for mobile) –Residential (Wired) YouTube YouTube and Netflix Similar Traffic Characteristics at Each Location

8. 8 / 21 Outline Introduction and Motivation Datasets and Measurement Techniques Streaming Strategies Impact of Streaming Strategies

9. 9 / 21 Generic Behavior of Video Streaming Download Amount Time Buffering Block Size On Off Steady State Average rate ∝ Video encoding rate

10. 10 / 21 We Identified Three Streaming Strategies No On Off Cycles Long On Off Cycles OFF Short On Off Cycles Streaming strategies vastly different

11. 11 / 21 Streaming Strategies Used ServiceYouTubeNetflix ContainerFlashHD (Flash)HTML5Silverlight IE 9ShortNoShort FirefoxShortNo Short ChromeShortNoLongShort iOS (native) --Based on encoding rate Short Android (native) --Long Streaming strategy differs with application type and container

12. 12 / 21 Features Controlling Arrival of Data Packets Buffering Amount Block Size Accumulation Ratio Average download rate in steady state phase Video encoding rate =

13. 13 / 21 Arrival of Packets for Short ON OFF Strategy 64 kB 40 sec. of playback Server side rate control with absence of ACK clocks 1.25 Buffering independent of encoding rate Browser throttles rate 256 kB Significant differences between implementations

14. 14 / 21 Outline Introduction and Motivation Datasets and Measurement Techniques Streaming Strategies Impact of Streaming Strategies

15. 15 / 21 Impact of Streaming Strategies No On OffLong On OffShort On Off TCP FriendlyYes – TCP File Transfer Yes – Periodic File Transfer Unknown traffic not ack-clocked Playout buffer occupancy LargeModerateSmall Unused bytes on user interruptions Large amount Moderate amount Small amount Strategy Metric

16. 16 / 21 Model for Aggregate Rate of Streaming Traffic Objective –Capture statistical properties of aggregate streaming traffic Barakat et al., A flow-based model for Internet backbone traffic, In IMW’02. Uses –Dimension the network –Quantify impact of user interruptions

17. 17 / 21 Aggregate Rate of Video Streaming Traffic Aggregate Rate Arrival Rate of streaming sessions (Poisson) Amount of data downloaded

18. 18 / 21 Insights from Model No User Interruptions –Aggregate rate (mean, variance, etc.) independent of streaming strategy –Dimensioning rules do not change –Strategy to optimize other goals (server load, etc.) Users Interruptions –Impact of buffering amount and accumulation ratio on wasted bandwidth

19. 19 / 21 Summary Most popular clients and containers for video streaming Streaming strategy differs with client applications and container –HTML5 streaming vastly differs with client applications Model to study impact of streaming strategies

20. 20 / 21 Open Questions for the CCN community Should CCN nodes be aware of the underlying streaming strategy? What is the optimal streaming strategy for CCN? Is there an optimal caching strategy for a given streaming strategy? What is the impact of user interruptions due to lack of interest on CCN caches?

21. 21 / 21 THANK YOU ashwin.rao@inria.fr Network Characteristics of Video Streaming Traffic

22. B-22 BACKUPS

23. B-23 Short or Long Block Size – Threshold 2.5 MB Short Long OFF Long

24. B-24 ACK Clocks Source sends packets on receiving ACK ACKs as an indication of available bandwidth 46 packets sent in the first RTT after an OFF period of more than 500 ms

25. 25 / 21 Conclusion Most popular clients and containers for video streaming Streaming strategy differs with client applications and container –HTML5 streaming vastly differs with client applications Model to study impact of streaming strategies

26. B-26 User Interruptions Video duration Playback time downloaded in buffering phase 1Accumulation ratioFraction of video watched - X > Video download will be in progress when

27. B-27 Impact of Losses Merging of cycles Playback can freeze Longer buffering phase

28. B-28 HTML5 Primary - webM Very few - h.264

29. B-29 Netflix Streaming Strategies ContainerSilverlightSilverlight for Mobile Devices ApplicationAny Web Browser iOS (native)Android (native) StrategyShort Long Buffering Amount 30 MB to 150 MB 10 to 20 MB35 to 45 MB Block Size0.5 MB to 2 MB 0.5 to 2.5 MB4.5 to 6 MB

30. B-30 YouTube Streaming Strategies ContainerFlashHTML5 ApplicationAny Web Browser IE 9FirefoxGoogle Chrome iOS (native) Android (native) StrategyShort NoLongMultipleLong Buffering Amount 40 sUp to 15 MB Video Size Up to 15 MB 40 s of playback or up to 20 MB Up to 10 MB Block Size64 kB256 kB NA5 MB to 8 MB 64 kB2 MB to 8 MB

31. B-31 Tradeoff Migration from one strategy to another can have a non-negligible impact Raw File Transfer vs Periodic Buffering vs No ack-clock

32. B-32 Video Streaming in the Internet 20 % to 40 % of all Internet traffic –Traffic share steadily increasing in recent years Streaming over HTTP – using TCP –Firewall configurations –TCP flows assumed to be fair