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

P2P-TV 2007 Darshan Purandare 2 Outline Chunk based P2P models Current Issues Proposed peering scheme Discussion and summary

P2P-TV 2007 Darshan Purandare 3 Chunk based P2P models Server … … … … … … … … 1 3 Stream is split into pieces Stream is split into pieces

P2P-TV 2007 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

P2P-TV 2007 Darshan Purandare 5 Outline Chunk based P2P models Current Issues Proposed peering scheme Discussion and summary

P2P-TV 2007 Darshan Purandare 6 Current Issues Quality of Service Quality of Service can improve [Hei et al. 06] Long start up time Peer Lag Unfairness Unfairness [Ali et al. 06] Uplink bandwidth distribution uneven Sub-optimal uplink utilization May affect QoS & Scalability Can we do better ?

P2P-TV 2007 Darshan Purandare 7 Outline Chunk based P2P models Current Issues Proposed peering scheme Discussion and summary

P2P-TV 2007 Darshan Purandare 8 Proposed Model Chunk based paradigm but overlay formation using alliances Nodes cluster in groups of 4-8 to form alliances Power Media server relays content to Power nodes BEAM: Bit strEAMing

P2P-TV 2007 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 Power nodes Server relays stream content to Power nodes Utility Factor Power nodes changes periodically based on Utility Factor (UF) A nodes UF computed using: Cumulative share ratio (CSR) Temporal share ratio (TSR)

P2P-TV 2007 Darshan Purandare 10 Alliance Formation 6, 17, 23 Peerlist of Node 1:: 6, 17, 23 12, 22, 43 Peerlist of Node 6: 12, 22, 43

P2P-TV 2007 Darshan Purandare 11 Alliance Properties A node can be a member of multiple alliances H H: Maximum number of nodes in an Alliance K K: Maximum number of alliances a node can join Number of neighbors = K(H-1)

P2P-TV 2007 Darshan Purandare 12 Alliance Functionality H = 5 K = 2

P2P-TV 2007 Darshan Purandare 13 Alliance Functionality H = 5 K = 2

P2P-TV 2007 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

P2P-TV 2007 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]

P2P-TV 2007 Darshan Purandare 16 Simulator Details Streaming rate = 512 Kbps Media Servers 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

P2P-TV 2007 Darshan Purandare 17 QoS: Average Jitter Rate

P2P-TV 2007 Darshan Purandare 18 QoS: Average Latency

P2P-TV 2007 Darshan Purandare 19 Uplink Utilization

P2P-TV 2007 Darshan Purandare 20 Fairness: Share Ratio Range

P2P-TV 2007 Darshan Purandare 21 Fairness: Jitter Factor Range

P2P-TV 2007 Darshan Purandare 22 Fairness: Latency Range

P2P-TV 2007 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.

P2P-TV 2007 Darshan Purandare 24 Questions or Comments

Thank You!