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Abstract: In mesh-based peer-to-peer streaming systems data is distributed among the peers according to local scheduling decisions. The local decisions affect how packets get distributed in the mesh, the probability of duplicates and consequently, the probability of timely data delivery. In this talk we present an analytic framework that allows the evaluation of scheduling algorithms. We consider different solutions in which scheduling is performed at the forwarding peer, based on the knowledge of the playout buffer content at the neighbors. We evaluate the effectiveness of the solutions in terms of the probability that a peer can play out a packet versus the playback delay, the sensitivity of the solutions to the accuracy of the knowledge of the neighbors' playout buffer contents, and the scalability of the solutions with respect to the size of the overlay. Short bio: Ilias received his Diploma degree in Informatics and Telecommunications from the Department of Informatics and Telecommunications at the National and Kapodistrian University of Athens in 2003. In 2006 Ilias received his Masters degree in Economics and Management of Telecommunication Networks from the same university. As of October 2006, he is a phd student at the Laboratory for Communication Networks (LCN) at the Royal Institute of Technology (KTH) in Stockholm, Sweden. His research interests cover the area of p2p live video streaming.
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