1. A Practical Performance Analysis of Stream Reuse Techniques in Peer-to-Peer VoD Systems Leonardo B. Pinho and Claudio L. Amorim Parallel Computing Laboratory COPPE Systems Engineering Program Federal University of Rio de Janeiro, Brazil Supported by:

2. 2 /16 Outline Introduction Stream Reuse Techniques GloVE VoD System Experimental Analysis Conclusions and Ongoing Work

3. 3 /16 Video on Demand (VoD) What is this? – Video delivery service Choose a video at any time, fast playback start – Applications Distance learning, home entertainment, … – Basic components Hide VBR and Jitter Prefetch limit

4. 4 /16 Scalability Problem Conventional Systems – Client/Server model – Unicast streams One streamOne receiver How to add scalability to video delivery? – Reuse content delivered by the server One streamMultiple receivers – Several stream reuse techniques proposed Evaluated through simulation Our Goal: Evaluate reuse techniques in practical situations

5. 5 /16 Stream Reuse Techniques Cooperative Video Cache (2001,2003) Dan et al(1996)Hua et al(1998)Sheu et al(1997)

6. 6 /16 Global Video Environment (GloVE) Access Types Smooth, Burst Operation Modes Batching Chaining Patching+Batching CVC+Batching Prefetch limit Send when playing Scalable P2P system Centralized metadata Monitors buffers globally Content sharing Basic techniques

7. 7 /16 Experimental Analysis Test platform – 6-node cluster (PIV 2.4 GHz, 1 GB Ram, Linux kernel 2.4.18) One (CVCS/CVCM), Five (Multiple emulated clients) – 3Com Fast Ethernet switch with IP multicast support Workload – Mpeg-1 Video (1.45Mbps) – Poisson process for clients arrival (6-120 clients/min) – Server (CVCS) with 56 channels Performance results – Metrics: Server usage, Active streams – One/Eight videos, Sensitivity to videos’ popularity – Playout buffers of 8 MB (44s of video), Prefetch limit of 2 MB – Results for 56 active clients Indicates degree of scalability Lower usage, higher scalability Aggregated bandwidth needs Fewer streams, lower needs

8. 8 /16 Server usage for single video At least one channel for each video

9. 9 /16 Active streams for single video At least two streams for each video

10. 10 /16 Server usage for multiple videos At least one channel for each video

11. 11 /16 Active streams for multiple videos At least two streams for each video

12. 12 /16 Sensitivity to popularity for smooth Variations < 20% Uniform distribution Same probability Zipf skew used in VoD literature Zipf without skew Highly concentrated

13. 13 /16 Sensitivity to popularity for burst Even smaller variations

14. 14 /16 Conclusions and Ongoing Work General – Compared the performance of combinations of stream reuse techniques in practical situations using the GloVE P2P system Batching, Chaining, Patching, and CVC – Measured the influence of client access type Smooth and Burst – Analyzed the impact of video popularity distribution Main findings – CVC+Batching mode outperformed the other modes VoD servers with either single or multiple videos – Client access type does not significantly affect CVC+Batching Efficient for different server designs

15. 15 /16 Conclusions and Ongoing Work – Videos' popularity doesn’t impact substantially CVC+Batching Scalable performance for heterogeneous audiences Research directions – Novel mechanisms for VoD systems for mobile environments with heterogeneous devices – Extend GloVE to dynamically self-adapt to variations on network and peer conditions

16. 16 /16 Additional Information http://lcp.coppe.ufrj.br

17. 17 /16 Average Results Extra Slides

18. 18 /16 Average Results Extra Slides

19. 19 /16 Average Results Extra Slides

20. 20 /16 CVC Manager (CVCM) Batching New Stream Derivation + Patch Extra Slides

21. 21 /16 Extra Slides

22. 22 /16 Extra Slides

23. 23 /16 Extra Slides

24. 24 /16 Extra Slides

25. 25 /16 Extra Slides

26. 26 /16 Extra Slides

27. 27 /16 Extra Slides

28. 28 /16 Extra Slides