Selecting among replicated batching video-on-demand servers

A Video-on-Demand (VoD) service offers a large selection of videos from which customers can choose. Designers of VoD systems strive to achieve low access latency for customers. One approach that has been investigated by several researchers allows the server to batch clients requesting the same video and to serve clients in the same batch with one multicast video stream. This approach has the advantage that it can save server resources as well as server access and network bandwidth, thus allowing the server to handle a large number of customers without sacrificing access latency. VoD server replication is another approach that can allow a VoD service to handle a large number of clients, albeit at the additional cost of providing more servers. While replication is an effective way to increase the service capacity, it needs to be coupled with appropriate selection techniques in order to make efficient use of the increased capacity. In this paper, we investigate the design of server selection techniques for a system of replicated batching VoD servers. We design and evaluate a range of selection algorithms as they would be applied to three batching approaches: Batching with Persistent Channel Allocation, Patching, and Hierarchical Multicast Stream Merging (HMSM). We demonstrate that server replication combined with appropriate server selection scheme can indeed be used to increase the capacity of the service leading to improved performance.