Efficient server replication and client re-direction for multicast services

Server replication and multicasting are well-established techniques for increasing the capacity of a networked service and improving client performance. In this paper, we consider the combination of these two techniques. Specifically, we investigate the problem of selecting amongst rate-adaptive multicast servers, which adjust their sending rate based on network conditions and/or feedback from clients. Effective server rate adaptation can lead to efficient utilization of network resources and performance improvement perceived by clients. In this study of adaptive multicast server selection, we explore some fundamental issues and investigate the implications of different selection strategies on the performance perceived by clients. We first formulate several optimization problems based on different performance measures, We prove that the general problem is NP-hard and then present a special case with an optimal polynomial-time solution. We then design several heuristics for the general problem. We investigate the performance of the heuristics through simulation and show that our heuristics can improve the performance perceived by clients over other strategies.