Abstract-Most existing commercial video servers are designed for a single server. Consequently, the capacity of the system in terms of maximum sustainable concurrent sessions is limited by the performance of the video server hardware. This paper proposes and analyzes the performance of a novel parallel video server architecture where video data are striped across an array of autonomous servers. The architecture allows one to build incrementally scalable video servers without video data replication. The proposed concurrent-push scheduling algorithm allows the system to integrate with quality of service guarantees provided by today's switching networks. In this paper, the striping policy, the service model, and the concurrent-push scheduling algorithm are presented. A system model is constructed to quantify three performance metrics, namely, server buffer requirement, client buffer requirement, and system response time. Results show that a simple extension of the server-push service model does not perform well under the parallel video server architecture. To improve system performance, a novel extension of the grouped sweeping scheme called the asynchronous grouped sweeping scheme (AGSS) is introduced. To further increase the scalability of the architecture, a new subschedule striping scheme (SSS) is introduced. With the proposed AGSS and SSS, our parallel video server architecture can be scaled up to more than 10 000 concurrent users.Index Terms-Concurrent push, grouped sweeping scheme (GSS), parallel video server, performance analysis, scheduling algorithm, server push, server striping, video on demand.

Abstract-Current peer-to-peer (P2P) file-sharing systems are mostly optimized for file availability. This paper investigates P2P architecture for video streaming in general, and the performance impact of data redundancy schemes in particular. In particular, this work show that maximizing file availability is not the best strategy for video streaming as another constraint -peers' streaming bandwidth, comes into play. To address this limitation, a request-rate minimization policy is developed and evaluated using simulation. The resultant optimized replication strategy is then compared to data redundancy scheme based on erasure-correction coding. Simulation results show that with sufficient peer storage and a low erasure coding overhead, erasure-correction coding can achieve substantially better streaming performance than replication-based strategies.