Research Publications

This paper considers the problem of adapting the BitTorrent protocol for on-demand streaming. BitTorrent is a popular peer-to-peer file sharing protocol that efficiently accommodates a large number of requests for file downloads. Two components of the protocol, namely the Rarest-First piece selection policy and the Tit-for-Tat algorithm for peer selection, are acknowledged to contribute toward the protocol's efficiency with respect to time to download files and its resilience to freeriders. Rarest-First piece selection, however, does not augur well for on-demand streaming. In this paper, we present a new adaptive Window-based piece selection policy that achieves a balance between the system scalability provided by the Rarest-First algorithm and the necessity of In-Order pieces for seamless media playback. We also show that this simple modification to the piece selection policy allows the system to be efficient with respect to utilization of available upload capacity of participating peers, and does not break the Tit-for-Tat incentive scheme which provides resilience to freeriders.