Parallel video servers provide highly scalable video-on-demand service for a huge number of clients. The conventional stream-scheduling scheme does not use I/O and network bandwidth efficiently. Some other schemes, such as batching and stream merging, can effectively improve server I/O and network bandwidth efficiency. However, the batching scheme results in long start-up latency and high reneging probability. The traditional stream-merging scheme does not work well at high client-request rates due to mass retransmission of the same video data. In this paper, a novel stream-scheduling scheme, called Medusa, is developed for minimizing server bandwidth requirements over a wide range of client-request rates. Furthermore, the start-up latency raised by Medusa scheme is far less than that of the batching scheme.