An Alliance based Peering Scheme for P2P Live Media Streaming

1. An Alliance based Peering Scheme for P2P Live Media Streaming Darshan Purandare Ratan Guha University of Central Florida August 31, 2007 @ P2P-TV, Kyoto

2. Outline • Chunk based P2P models • Current Issues • Proposed peering scheme • Discussion and summary Darshan Purandare

3. Chunk based P2P models … 1 … Server 3 2 … … … 5 4 … … 1 … • Stream is split into pieces 3 Darshan Purandare

4. Working Philosophy • Peers exchange buffer map of data availability • Retrieve the missing pieces and upload pieces to neighbors • Scheduling algorithm finds which pieces to retrieve and from whom • Partnership refinement helps to obtain better peers in terms of uploading rate Darshan Purandare

5. Outline • Chunk based P2P models • Current Issues • Proposed peering scheme • Discussion and summary Darshan Purandare

6. Current Issues • Quality of Service can improve [Hei et al. 06] • Long start up time • Peer Lag • Unfairness [Ali et al. 06] • Uplink bandwidth distribution uneven • Sub-optimal uplink utilization • May affect QoS & Scalability • Can we do better ? Darshan Purandare

7. Outline • Chunk based P2P models • Current Issues • Proposed peering scheme • Discussion and summary Darshan Purandare

8. Proposed Model • Chunk based paradigm but overlay formation using alliances • Nodes cluster in groups of 4-8 to form alliances • Media server relays content to Powernodes • BEAM: Bit strEAMing Darshan Purandare

9. BEAM: Working Philosophy • A new node upon arrival obtains peerlist from Tracker • Peerlist contains nodes in similar bandwidth range and similar network (if possible) • Contacts peers for stream content • Starts joining alliances or creates one • Server relays stream content to Power nodes • Power nodes changes periodically based on Utility Factor (UF) • A node’s UF computed using: • Cumulative share ratio (CSR) • Temporal share ratio (TSR) Darshan Purandare

10. Alliance Formation Peerlist of Node 6: 12, 22, 43 Peerlist of Node 1:: 6, 17, 23 Darshan Purandare

11. Alliance Properties • A node can be a member of multiple alliances • H: Maximum number of nodes in an Alliance • K: Maximum number of alliances a node can join • Number of neighbors = K(H-1) Darshan Purandare

12. H = 5 K = 2 Alliance Functionality Darshan Purandare

13. H = 5 K = 2 Alliance Functionality Darshan Purandare

14. Why form Alliances ? • Clustering into alliances forms a small world network graph • Short Path Length • Robust to network perturbations such as churn • Close knit group ensures streaming content is readily available within alliances • Alliance members have common trust & treaty Darshan Purandare

15. Small World Network • Dense local clustering (high clustering coefficient) • Some links to other part of the graph (non local) • Overlay distance is near-optimal • Robust to churn • [Watts et al., Nature,98] Darshan Purandare

16. Simulator Details • Streaming rate = 512 Kbps • Media Server’s Uplink = 1536 Kbps (3 links) • Heterogeneous bandwidth class • (512,128), (768,256), (1024, 512), (1536,768), (2048, 1024) • H, K = 4, 2 (6 neighbor nodes) • Each node buffers content for 120 sec Darshan Purandare

17. QoS: Average Jitter Rate Darshan Purandare

18. QoS: Average Latency Darshan Purandare

19. Uplink Utilization Darshan Purandare

20. Fairness: Share Ratio Range Darshan Purandare

21. Fairness: Jitter Factor Range Darshan Purandare

22. Fairness: Latency Range Darshan Purandare

23. Summary • Alliance based peering scheme is an effective technique to group peers • QoS, Uplink throughput and fairness results are at par or even better than CoolStreaming • Peer lag can be improved using BEAM • Initial buffering time can be slightly improved • Our research is complementary to advance source and channel coding techniques. Darshan Purandare

24. Questions or Comments Darshan Purandare

25. Thank You!