A Trace-Driven Approach to Evaluate the Scalability of P2P-Based Video-on-Demand Service

Peer-to-Peer (P2P) networks have emerged as one of the most promising approaches to improve the scalability of Video-on-Demand (VoD) service over Internet. However, despite a number of architectures and streaming protocols have been proposed in past years, there is few work to study the practical performance of P2P-based VoD service especially in consideration of real user behavior which actually has significant impact on system scalability. Therefore, in this paper, we first characterize the user behavior by analyzing a large amount of real traces from a popular VoD system supported by the biggest television station in China, cctv.com. Then we ex-amine the practical scalability of P2P-based VoD service through extensive trace-driven simula-tion under a general system framework. The results show that P2P networks scale well in provid-ing VoD service under real user behavior by obtaining a considerable good cache hit ratio. Moreover, it is observed that adopting hard cache at client side help achieves better system scal-ability than that with soft cache. We also identify the impact of various aspects of user behavior upon system scalability through detailed simulation. We believe that our study will shine insight-ful light on the understanding of practical scalability of P2P-based VoD service and be helpful to future system design and optimization.