Receiver-driven layered multicast
Conference proceedings on Applications, technologies, architectures, and protocols for computer communications
A comparison of layering and stream replication video multicast schemes
NOSSDAV '01 Proceedings of the 11th international workshop on Network and operating systems support for digital audio and video
Scalable application layer multicast
Proceedings of the 2002 conference on Applications, technologies, architectures, and protocols for computer communications
Peer-to-Peer Membership Management for Gossip-Based Protocols
IEEE Transactions on Computers
PALS: peer-to-peer adaptive layered streaming
NOSSDAV '03 Proceedings of the 13th international workshop on Network and operating systems support for digital audio and video
Layered peer-to-peer streaming
NOSSDAV '03 Proceedings of the 13th international workshop on Network and operating systems support for digital audio and video
On Peer-to-Peer Media Streaming
ICDCS '02 Proceedings of the 22 nd International Conference on Distributed Computing Systems (ICDCS'02)
SplitStream: high-bandwidth multicast in cooperative environments
SOSP '03 Proceedings of the nineteenth ACM symposium on Operating systems principles
PROMISE: peer-to-peer media streaming using CollectCast
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Large-scale live media streaming over peer-to-peer networks through global internet
Proceedings of the ACM workshop on Advances in peer-to-peer multimedia streaming
Distributed prefetching scheme for random seek support in peer-to-peer streaming applications
Proceedings of the ACM workshop on Advances in peer-to-peer multimedia streaming
Optimal peer selection for minimum-delay peer-to-peer streaming with rateless codes
Proceedings of the ACM workshop on Advances in peer-to-peer multimedia streaming
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A fundamental problem in peer-to-peer streaming is how to select peers from a large network to request their media data. Due to the heterogeneity and the time-varying features of shared resources between peers, an adaptive method is required to select suitable peers. In this paper, we use Hidden Markov Models (HMMs) to model each peer to reflect the variation of resources. Among peers with different HMMs, the one which produces the maximum observation probability is selected as the serving peer. Through simulation results, we show that the proposed algorithm can achieve a good streaming quality and low communication overhead. In addition to these characteristics, the proposed model also comes with the fairness property.