Performance study on media server scheduling in video-on-demand systems

Media server scheduling in video-on-demand systems includes video content allocation and request migration among servers. In this paper, we present a greedy algorithm to allocate video copies to media servers. It uses a graph model and minimizes the average shortest distance among media servers at each step. In order to study the request migration process, we introduce a state matrix representation that stores the service load information of each media server and plays an important role in the determination of migration paths. Based on this representation, we develop a state transition method to simulate the request migration process and calculate the performance metrics such as failure rates and service delay. The derived results match very well with numerical experiments. It is further demonstrated that the random early migration (REM) algorithm proposed in our previous work outperforms the normal migration scheme with lower failure rates and shorter service delay.