SOP: An SIU-based Overlay Proxy Service for Peer-to-Peer Streaming

1. SOP: An SIU-based Overlay Proxy Service for Peer-to-Peer Streaming 研究生: 邱世雄 指導教授: 鍾添曜 博士

2. Outline • Introduction • SOP Architecture • Online Scheduling Algorithm • Cache Replacement Algorithm • Simulation • Conclusion

3. Introduction - Background • Multimedia Streaming characteristics • High Bandwidth • Limited service latency • Large data size • Video server • The main bottleneck in server/client model.

4. Introduction - Background • P2P networks • A peer node can be server and client. • P2P networks are at the application level. • Peer nodes can reduce server load by • build a application level multicast tree • play as a proxy server

5. Introduction – Motivation • Users can access the film at any time. • Users’ behavior are unpredictably. • A peer proxy server has limited service time. • Peer nodes have different capability. • Mostly of peers’ network link are asymmetrical (Uplink<downlink). • The peer proxy server may not be able to provide service by itself.

6. Introduction – Related Work (1) • Multicast • IP multicast • Application level multicast • Batching and patching • Period broadcast • Suit for live streaming or NVoD system

7. Introduction – Related Work (2) • Proxy service • Infrastructure-base • High cost • Non-scalable • Film segmentation • Fixed size • Variable size • Cache replacement algorithm

8. Introduction - Goal • Provide an online scheduling to real-time choosing the peer cache server and scheduled each film segment for smoothing playback. • Propose an efficient caching replacement algorithm for SOP system. • Proxies cooperate to using the resource efficiently.

9. Preliminary (1) • SOP Architecture • Over a cluster base P2P network. • Synchronization interval unit (SIU) base film segmentation. • SIU : Group of pictures • Three main components • Source server • Proxy server • Superobject server (SOS)

10. SOP Architecture

11. Preliminary (2) • Three transition modes : • B (buffer constraint)->B • B->R (rate constraint)

12. Preliminary (3) • B->R->R

13. SuperObject Server (SOS) • SOS provides the SIU cache information. • A peer requests cache information from SOS at the beginning. • A peer will periodically update the cache information. • SOS can record other information such as peer access time, the peer’s capacity (bandwidth), etc.

14. Online Scheduling Algorithm • A real-time scheduling is necessary because: • Peers dynamic up and leave. • SIUs cache or replace in each peer change over time. • Grasp the state of current network.

15. Online Scheduling Algorithm Peer A Peer B Peer C R B B B SIU i SIU (i-1) t SIU (i-3) SIU (i-2) t (i) t (i-3) t (i-2) t (i-1) SIU(i-1) earliest transmission time

16. Online Scheduling Algorithm Peer A Peer B Peer C Peer D Peer E Peer F SIU1 SIU2 SIU4 SIU3 SIU5 t SIU6 t1 t2 t3 t4 t5 t6 System initial play play

17. Cache Replacement Algorithm • The peer caching is not a long-term caching. • A peer’s capacity (bandwidth) and service time is limited. • Peers may access at any time. • The SOS can provide much helpful information. • Peers access time • Peer’s capacity

18. Cache Replacement Algorithm • Access Un-awareCaching • Access-aware caching • Local access-awarecaching • Region access-aware caching • Region cooperative caching

19. Terminology Definition • The variables defined as : • : Free cache size • : The SIU number of film • : The size of SIUi • : SIUi’s BB_rate • : Uplink bandwidth • : Film residual time

20. Access Un-awareCaching (1) • Peers will determine to cache this SIU if: • It was download from the source server • If the SIU contains the peak rate, and the peer has not enough cache space -> try replacement

21. Access Un-awareCaching (2) • Replacement : • A peer computes the total size as follow: : total free size : can remove SIU’s size • If , do replacement

22. Access Un-awareCaching Start Enough bandwidth? Yes Enough Cache Space? Contain peak rate? Yes No Yes Compute total size No No Yes Total size >= SIU size? Yes Cache this SIU No Replacement End

23. Local Access-awareCaching (1) • Think about the user behavior, the prefix SIUs have higher access rate in the film. • SIU cache priority (SPi ) is defined as

24. Local Access-awareCaching (2) • Defined the residual time of film as a revenue window (w). • Define as the number of peers in SIUi’s revenue window.

25. Local Access-awareCaching (3) SIU A revenue window T2 T1 SIUA = T1 * average arrival rate + the number of peers in T2

26. Local Access-awareCaching (4) • At first, a peer node caches all the SIUs as it can. Until cache space becomes insufficient to caching current SIU, the peer node will try replacement. • A peer node computes each SIU’s value using the following cost function: • A proxy replaces SIUs so that

27. Region Access-aware Caching • SOS provides all the peer access time in the cluster. • Cost function : Where is the number of peers in the SIUi’s revenue window in whole cluster.

28. Region Cooperation Caching • SOS provides the number of proxies and number of duplicates. • The cost function is modified as: • We defined the total duplicates capacity (DC) as :

29. Access-awareCaching Start Enough Cache Space? No Compute each SIU’s value by cost function Yes Cache this SIU Replacement, keep the total of value is maximum End

30. Multi-Source downloading (1) • The peer’s capacity is limited, it may be unable to satisfy the required transmission rate. • A peer downloads an SIU from multiple proxies to ensure smooth playback.

31. Multi-Source downloading (2)

32. Simulation

33. Simulation

34. Simulation

35. Simulation – system performance (single source)

36. Simulation – system performance (multi-source)

37. Simulation – Multi-source

38. Simulation – Arrival rate and periodical update time

39. Simulation – SOS load (1)

40. Simulation – SOS load (2)

41. Simulation – Cache size (1)

42. Simulation – Cache size (2)

43. Simulation – Clustering (1)

44. Simulation – Clustering (2)

45. Simulation – Peak rate

46. Conclusion • The system can reduce equally 20% server load. • Local access aware caching algorithm has highest hit rate in SOP system. • The multi-source mechanism can enhance 3%~5% hit rate. • Setting 64MB cache size and 60 sec. update cycle, the system will more efficient and has the better performance.