Peer-to-Peer Streaming of Layered Video: Efficiency, Fairness and Incentive

Abstract

Recent advances in scalable video coding (SVC) make it possible for users to receive the same video with different qualities. To adopt SVC in P2P streaming, two key design questions need to be answered: 1) layer subscription: how many layers each peer should receive, and 2) layer scheduling: how to deliver to peers the layers they subscribed. From the system point of view, the most efficient solution is to maximize the aggregate video quality on all peers, i.e., the social welfare. From individual peer point of view, the solution should be fair. Fairness in P2P streaming should additionally take into account peer contributions to make the solution incentive-compatible. In this paper, we first develop utility maximization models to understand the interplay between efficiency, fairness and incentive in layered P2P streaming. We show that taxation mechanisms can be devised to strike the right balance between social welfare and individual peer welfare. We then develop practical taxation-based P2P layered streaming designs, including layer subscription strategy, chunk scheduling policy, and mesh topology adaptation. Extensive trace-driven simulations show that the proposed designs can effectively drive layered P2P streaming systems to converge to the desired operating points in a distributed fashion.