Prediction-Based Prefetching to Support VCR-Like Operations in Gossip-Based P2P VoD Systems
Supporting free VCR-like operations in P2P VoD streaming systems is challenging. The uncertainty of frequent VCR operations makes it difficult to provide high quality real-time streaming services over distributed self-organized P2P overlay networks. Recently, prefetching has emerged as a promising approach to smooth the streaming quality. However, how to efficiently and effectively prefetch suitable segments is still an open issue. In this paper, the authors propose PREP, a PREdiction-based Prefetching scheme to support VCR-like operations over gossip-based P2P on-demand streaming systems. By employing the reinforcement learning technique, PREP transforms users' streaming service procedure into a set of abstract states and presents an online prediction model to predict a user's VCR behavior via analyzing the large volumes of user viewing logs collected on the tracker.