Optimizing patching performance

Patching has been shown to be cost efficient for video-on-demand systems. Unlike conventional multicast, patching is a dynamic multicast scheme which enables a new request to join an ongoing multicast. Since a multicast can now grow dynamically to serve new users, this approach is more efficient than traditional multicast. In addition, since a new request can be serviced immediately without having to wait for the next multicast, true video-on-demand can be achieved. In this paper, we introduce the notion of patching window, and present a generalized patching method. Re show that existing schemes are special cases with a specific patching window size. We derive a mathematical formula to help determine the optimal size for the patching window. This formula allows us to design the best patching scheme given a workload. The proposed technique is validated using simulations. They show that the analytical results are very accurate. We also provide performance results to demonstrate that the optimal technique outperforms the existing schemes by a significant margin. It is also up to two times better than the best Piggybacking method which provides data sharing by merging the services in progress into a single stream by altering their display rates.