A vEB-tree-based architecture for interactive video on demand services in peer-to-peer networks
Journal of Network and Computer Applications
Designing an effective P2P system for a VoD system to exploit the multicast communication
Journal of Parallel and Distributed Computing
Efficient Support of Streaming Videos through Patching Proxies in the Cloud
International Journal of Grid and High Performance Computing
Efficient Support of Streaming Videos through Patching Proxies in the Cloud
International Journal of Grid and High Performance Computing
Enhancing scalability in on-demand video streaming services for P2P systems
Advances in Multimedia
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Recent advances in multicast video streaming algorithms have opened up new ways to provision video-on-demand services to potentially millions of users. However, the spectacular efficiency of multicast streaming algorithms can only be realized by restricting or even prohibiting interactive playback control. Experiments reveal that the performance of current state-of-the-art multicast streaming algorithms will degrade significantly even at very low levels of interactivity (e.g., one control per five users). This study tackles this challenge by investigating the fundamental limitations of multicast streaming algorithms in supporting interactive playback control and presents a general solution-static full stream scheduling (SFSS)-which can be applied to many of the existing multicast streaming algorithms to substantially improve their performance when interactive playback control is to be supported. Moreover, to solve the problem of optimizing the algorithm for the often unknown client access patterns (e.g., arrival rates and interactivity rates), we present a novel just-in-time simulation (JTS) scheme to dynamically and automatically tune operating parameters of the SFSS algorithm while the system is online. This JTS scheme not only eliminates the need for a priori knowledge of the often unknown system parameters, but also can adapt to changes in the client access pattern over time. Extensive simulation results show that the proposed adaptive algorithm can reduce the admission and interactive control latencies by as much as 90%