A scalable and adaptive video streaming framework over multiple paths

In this paper, we examine the frame loss probabilities for multiple-description coded video transmitted over independent paths. We apply an efficient multiple description coding technique for the analysis, and we investigate the impact of drifting error in terms of the probability of receiving freeze frames for reconstructed video. In order to improve the video delivery, an adaptive video coding scheme by adjusting the length of group-of-pictures is investigated in this paper. In addition, a scalable video streaming framework from client-server, centralized peer-to-peer, and decentralized peer-to-peer network topologies are examined. Analytical and experimental results based on Gilbert model are used to evaluate the performance of the proposed adaptive and scalable video streaming framework.