A game theoretic framework for optimal resource allocation in P2P scalable video streaming

In this paper we describe a game theoretic framework for scalable video streaming over a peer-to-peer network. The proposed system integrates optimal resource allocation functionalities with an incentive provision mechanism for data sharing. First of all, we introduce an algorithm for packet scheduling that allows users to download a specific sub-set of the original scalable bit-stream, depending on the current network conditions. Furthermore, we present an algorithm that aims both at identifying free-riders and minimising transmission delay. Uncooperative peers are cut out of this system, while users upload more data to those which have less to share, in order to fully exploit the resources of all the peers. Experimental evaluation shows that this model can effectively cope with free-riders and minimise transmission delay for scalable video streaming.