APEX: A personalization framework to improve quality of experience for DVD-like functions in P2P VoD applications

Abstract

The requirement for supporting DVD-like functions raises new challenges to the design of P2P VoD systems. The uncertainty of frequent user DVD-like interactivity makes it difficult to ensure user perceived Quality of Experience (QoE) for real-time streaming services over distributed self-organized P2P overlay networks. Most existing solutions are based on the unreasonable assumption that all the users in P2P VoD systems have the same preference. Few attention has been paid to personalization, which accommodates the differences between users. In this paper, we present a video model which characterizes the personalization information for users' contents and preferences. Based on this model, we develop APEX, a practical personalization framework for P2P VoD applications. APEX makes the personalization practical by using a hybrid architecture which leverages the offline pattern mining on the server side and online collaborative filtering on the peer side. Furthermore, APEX helps peers to personalize navigation, prefetching and membership management, aiming at improving QoE for DVD-like functions by reducing response latency and optimizing content sharing. Both theoretical analysis and comprehensive simulations show that APEX outperforms most existing schemes in terms of accumulated hit ratio, response latency, and searching efficiency.