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A Case for a Coordinated Internet Video Control Plane

A Case for a Coordinated Internet Video Control Plane. Presenter: Piggy 2012.12.17. Outline. Introduction Motivation Framework for Optimization Potential for Improvement Practical Design Simulation Discussion. Introduction. Video traffic has become the dominant Internet traffic

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A Case for a Coordinated Internet Video Control Plane

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  1. A Case for a Coordinated Internet Video Control Plane Presenter: Piggy 2012.12.17

  2. Outline • Introduction • Motivation • Framework for Optimization • Potential for Improvement • Practical Design • Simulation • Discussion

  3. Introduction • Video traffic has become the dominant Internet traffic • Netflix: 20% US Internet traffic • User expectation • Traditional traffic • Latency vs. completion time (throughput) • Streaming video • Sustained quality over extended period

  4. Introduction • Shift of streaming protocols and infrastructure • Traditional • Specialized protocols and infrastructure • Today • HTTP streaming, chunk-based • Mismatch • Video streaming vs. HTTP-based delivery infrastructure

  5. Motivation • Can we improve? • What parameters? • When to optimize or adapt? • Who is in charge? • Potential source of inefficiencies • Variability in client-side • Variability within a single ISP or AS • Variability in CDN performance (temporal and spatial)

  6. Dataset • One week of client-side measurement • Over 200 million viewing sessions • 91 popular video content providers • Live + VoD

  7. Metrics • Average bitrate • Rebuffering ratio • Startup time • Failure rate • Exits before video start

  8. Video Quality Today

  9. Sources of Quality Issues • Client-side variability • Intra- and inter- session

  10. Sources of Quality Issues • CDN variability – space and time

  11. Sources of Quality Issues • CDN variability – space and time

  12. Cause of CDN Variability • Load on CDN!

  13. AS Under Stress

  14. Design Space • What parameters to control? • Choice of bitrate • Choice of CDN/server • When to choose parameters? • Startup time • Midstream • Who decides the values of parameters? • Client-side mechanism • Server-driven mechanism • Control plane (based on global state)

  15. Design Space

  16. Video Control Plane • Measurement component • Performance oracle • Global optimization engine

  17. Potential Improvement • Assume each session makes the best possible choice • Cluster clients using similar attributes • Extrapolate the performance

  18. Estimation • a : client’s attributes • Sa : set of clients sharing same a • Sa, p : set of clients with same choice of parameters • PerfDista, p : empirical distribution

  19. Extrapolation • Parameter with the best performance distribution

  20. Hierarchical Structure • Fine-grained  data sparse

  21. Improvement • Average improvement

  22. Improvement • Improvement under stress • CDN performs poorly or has failures

  23. Practical Design • Impact of bitrate on performance • Additional attribute • Effect of CDN load • Threshold-based • Past estimates to predict future performance • Tractability of global optimization • Specific utility function

  24. Optimization • Goal: fairness vs. efficiency • Two-phases algorithm • Assign clients a fair share of CDN resources using average sustainable bitrate • Incrementally improve total utility

  25. Simulation • Trace-driven • Qualitative benefits • Input • Client arrival pattern • Observed CDN performance distribution in different geographical regions at different load

  26. Simulation • Strategies • Baseline • Global coordination • Hybrid • Scenarios • Average case • CDN performance degradation • Flash crowd

  27. Result • Metrics • Average utility • Failure ratio • Average case

  28. Result • Metrics • Average utility • Failure ratio • CDN degradation

  29. Result • Metrics • Average utility • Failure ratio • Flash crowd

  30. Discussion • Scalability • vs. # of clients • Switching tolerance • Switching frequency • Interaction with CDNs • CDNs do the optimization themselves? • Most CDNs are optimizing latency • Multiple controllers • Exchange information

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