A Content-Oriented Web Cache Policy under P2P Video Distribution Systems

Abstract

The increasing popularity of network-based multimedia applications poses many challenges for multimedia content providers to supply efficient and scalable multimedia services. Peer-to-Peer (P2P) networks have been shown to be a promising approach to provide large scale video services over Internet since they increase the scalability and robustness. In this paper, we propose and analyze an object management policy approach for video web cache in a P2P context, taking advantage of object's meta-data, e.g video popularity, and object's encoding techniques, e.g Scalable Video Coding (SVC). We exploit the peer-to-peer based approach to carry out the replication then eviction of videos in different web cache according to their popularity. Since videos are typically large and require high communication bandwidth for delivery, many peers may be unwilling to cache them in whole to serve others. Accordingly, we address this problem by proposing a new web caching approach for videos encoded in layers. Furthermore, in the proposed approach cooperation amongst the web caches may make it possible to replicate the video on several caches when this one is very popular. Afterward, we can gradually eliminate the replicas from the caches as the video popularity decrease. In addition, we structure our peer-to- peer network using interest-based communities. This network is made by ordinary nodes and super-nodes, and with peers clustered into communities. These communities are built around subjects (e.g., Science and Sports). The performance measurements we carried out allowed analyzing the traffic volume that flows from the community super-node to the first server into our content delivery network. The main goal is to measure how much our content-oriented management policy can help to decrease the demands put over the community output link. These measurements showed that the proposed approach (i) reduces the traffic volume, (ii) maximizes the overall bit rate of community demands, and (iii) optimizes the use of network resources.