Optimal Rate Allocation for ISP-friendly P2P VoD Systems
The rapid growth of Peer-to-Peer (P2P) Video-on-Demand (VoD) applications has posed significant pressure on both content providers and Internet Service Providers (ISPs). In this paper, we focus on rate allocation algorithms which not only improve the streaming performance of P2P VoD systems but also cut down on inter-ISP traffic. We first propose two centralized rate allocation algorithms which serve as the benchmarks: one is Server-First Optimal ( SFO ) algorithm that takes minimum server load as the first order objective, and the other is Locality-First Optimal ( LFO ) algorithm that takes minimum inter-ISP traffic as the first order objective. By introducing network flow theory, SFO and LFO can be solved as a series of maximum or min-cost flow problems. Then we propose a distributed rate allocation algorithm which utilizes a novel hybrid neighbor selection strategy and models the design goals as a multi-objective optimization problem. Through simulation studies, we show that our algorithms substantially outperform traditional and state-of-the-art approaches.