Modeling and performance analysis of BitTorrent-like peer-to-peer networks
Proceedings of the 2004 conference on Applications, technologies, architectures, and protocols for computer communications
2Fast: Collaborative Downloads in P2P Networks
P2P '06 Proceedings of the Sixth IEEE International Conference on Peer-to-Peer Computing
The Orchard Algorithm: P2P Multicasting without Free-Riding
P2P '06 Proceedings of the Sixth IEEE International Conference on Peer-to-Peer Computing
Can internet video-on-demand be profitable?
Proceedings of the 2007 conference on Applications, technologies, architectures, and protocols for computer communications
Peer-assisted On-demand Video Streaming with Selfish Peers
NETWORKING '09 Proceedings of the 8th International IFIP-TC 6 Networking Conference
Accelerating YouTube with video correlation
WSM '09 Proceedings of the first SIGMM workshop on Social media
Improving the streaming capacity in P2P VOD systems with helpers
ICME'09 Proceedings of the 2009 IEEE international conference on Multimedia and Expo
Provide VoD service in peer-to-peer network using offset ranking and epidemic diffusion
CCNC'09 Proceedings of the 6th IEEE Conference on Consumer Communications and Networking Conference
Advanced prefetching and upload strategies for P2P video-on-demand
Proceedings of the 2010 ACM workshop on Advanced video streaming techniques for peer-to-peer networks and social networking
Toward efficient on-demand streaming with bittorrent
NETWORKING'10 Proceedings of the 9th IFIP TC 6 international conference on Networking
BitTorrent-like P2P approaches for VoD: A comparative study
Computer Networks: The International Journal of Computer and Telecommunications Networking
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The peer-to-peer (P2P) paradigm provides a data distribution model that may be attractive for Video on Demand (VoD) as it allows to decrease the costs and to increase the scalability of video distribution. However, VoD is more challenging for P2P technology than file sharing or live streaming, and so, practically feasible VoD systems proposed to date rely on a backend server infrastructure as a fail-over solution. In this paper we investigate how the dependency on servers can be decreased by optimizing the video piece-selection strategy and by allowing multiple peers to form a collaboration for obtaining a single video. In a set of simulations of a trace-based system model we show that for systems such as YouTube the proposed optimizations would result in savings of as much as 70% of the server bandwidth. These simulation results confirm the conclusions of an analytical study of our optimizations, the essential part of which is also included in this paper.