CoolStreaming/DONet: A Data- driven Overlay Network for Peer- to-Peer Live Media Streaming INFOCOM 2005 Xinyan Zhang, Jiangchuan Liu, Bo Li, and Tak- Shing.

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Presentation transcript:

CoolStreaming/DONet: A Data- driven Overlay Network for Peer- to-Peer Live Media Streaming INFOCOM 2005 Xinyan Zhang, Jiangchuan Liu, Bo Li, and Tak- Shing Peter Yum Department of Information Engineering, The Chinese University of Hong Kong School of CS Simon Fraser University, BC, Canda Department of CS, Hong Kong University of Science and Technology

Motivation Provide peer-to-peer live streaming broadcasting  Network heterogeneity  No QoS guarantee Data-driven design  Don’t use any tree, mesh, or any other structures  Data flows are guided by the availability of data

Related work Overlay multicast system  Proxy-assisted Servers or application-level proxies are strategically placed  Peer-to-peer based Self-organized overlay networks Peer-to-Peer based multimedia distribution service (*)  May not suitable for live streaming *IEEE Transactions on Multimedia, April,

Related work * Peer-to-peer based overlay multicast system  Tree-based protocols Not suitable for highly dynamic environment Load balancing problem  Gossip-based protocols (*) Iteration  Send messages to a random set of nodes  Message receiving nodes do similar things in the next round Simple and robust Redundancy and delay problem

Core operations of DONet / CoolStreaming DONet: Data-driven Overlay Network CoolStream: Cooperative Overlay Streaming  A practical DONet implementation Every node periodically exchanges data availability information with a set of partners Retrieve unavailable data from one or more partners, or supply available data to partners The more people watching the streaming data, the better the watching quality will be  The idea is similar to BitTorrent (BT)

A generic system diagram for a DONet node Membership manager  mCache: record partial list of other active nodes  Update by gossiping Partnership manager  Random select Transmission scheduler  Schedules transmission of video data Buffer Map  Record availability

Node join and membership management Each node has a unique ID (eg, IP) and a membership cache (mCache) A new node contacts the original node (server), gets a randomly selected deputy node, then gets partner candidates from the deputy node’s mCache Use SCAM (Scalable Gossiping Membership Protocol) to distribute membership messages among nodes

Buffer map representation and exchange A video length is divided into segments of uniform size Availability of the segments in a node is represented by a Buffer Map (BM)  In practical, a BM is recorded by 120 bits for 120 segments Each node continuously exchanges its BM with its partners and schedules which segments to fetch from which partner

Scheduling algorithm Adapt to dynamic and heterogeneous networks  Playback deadline of each segment Number of segments missing deadlines should be kept minimum  Heterogeneous streaming bandwidth from partners This problem is a variation of the Parallel machine scheduling  NP-hard problem  The situation will become worse in a highly dynamic environment  Resort a simple heuristic of fast response time

Heuristic scheduling algorithm Calculate the number of potential suppliers for each segment  Message exchange Window-based buffer map (BM): data availability Segment request (similar to BM)  Less supplier first  Multi-supplier: highest bandwidth within deadline first

Failure recovery and partnership refinement Graceful departure  Issue a departure message when departing Node failure  A partner that detects the failure will issue the departure message Departure messages are propagated by gossip protocol A node periodically establishes new partnership with a randomly selected node in its mCache  In practical, establish with the nodes that have high segment send/receive throughput

Analysis on DONet (*) Coverage ratio for distance k (# of neighbors: M, total nodes: N)  E.g. 95% nodes are covered in 6 hops when M=4, N=500 Average distance from source to destination is bounded by O(logN) *DONet/CoolStreaming: A data-driven overlay network for live media streaming, Technical report, 2004

PlanetLab-based experiment PlanetLab  An open platform for developing, deploying, and accessing planetary-scale services Involved 200~300 nodes during experiment period (May to June, 2004) Streaming rate: 500 Kbps

Result: data continuity Continuity index: number of segments that arrive before or on playback deadlines over the total number segments

Result: control overhead vs. number of partners for different overlay sizes

Result: continuity index as a function of the number of partners

Result: Continuity index as a function of streaming rate (size = 200 nodes)

Result: average hop-count of DONet and tree-based overlay

CoolStream A practical DONet implementation First version release: May, 2004 Support Real Video and Windows Media format Broadcast live sport programs at 450~755 Kbps Attached users

CoolStream snapshot (*) *

User distribution Heterogeneous network environment  LAN, CABLE, DSL, …

Online statistics (June 21, 2004)

Observations Current Internet has enough available band to support TV-quality streaming (>450Kbps)  Bottleneck: server, end-to-end bandwidth Larger data-driven overlay  better streaming quality  Capacity amplification

Conclusion Present the design of DONet for live media streaming  Data-driven design  Scalable membership and partnership management algorithm  Heuristic scheduling algorithm The experiment results on PlantLab demonstrate DONet delivers quite good playback quality in a highly dynamic networks A practical implementation was also released for broadcasting live programs

PlanetLab distribution (*) *

A snapshot of a tree-based overlay with 231 nodes