Design and analysis of server scheduling for video-on-demand systems

Recent advances in computing and networking technology make real time multimedia delivery such as video-on-demand (VoD) a reality. In such a system, multiple media servers can be integrated together to serve user requests. As compared to the large file size and the high bandwidth requirements of on-demand video, the storage capacity and the service capacity for each server appear to be very limited. It is therefore a great challenge to solve the media server scheduling problem that involves video file allocation and load balancing among media servers to improve aggregate resource utilization and the overall system performance.; This research mainly focuses on the development of server scheduling algorithms and performance study of request migration among media servers. We first present a greedy content allocation algorithm to assign video copies to servers given the potion of each video object in the total system storage capacity. Then, we consider the design and analysis of a random early migration (REM) scheme for user requests. When a new request is dispatched to a video server, the REM-based scheduler decides whether request migration is needed with a certain probability, which is a function of the service load. We develop two methods based on the state matrix to calculate performance metrics: the service failure rate and the system delay in service migration. Simulation results show that the REM scheme outperforms both the DASD dancing algorithm and the traditional migration scheme with less delay and lower failure rate. It is also confirmed that our theoretical results match well with experimental results. Finally, we extend the server scheduling algorithms to a distributed VoD system. We propose a cost-aware REM (CAREM) scheme to reduce the network bandwidth consumption due to the migration process. To accommodate the change in video popularity and/or client population, we present a concept called the server-video affinity and apply it to online video content reconfiguration. Simulation results show that CAREM together with the dynamic content update strategy can improve the system performance by reducing the request failure rate as well as the server bandwidth consumption.