On fair and optimal multi-source IP-multicast

We investigate the problem of maximizing multicast throughput under a fairness constraint. Multiple server nodes wish to communicate to their intended set of client nodes over a shared network infrastructure. Our goal is to devise distributed algorithms to construct multicast sessions, one for each server node, such that (a) the network infrastructure is optimally utilized and (b) the network resources are fairly distributed between multicast sessions, i.e., no individual session claims more than a prescribed share of the network bandwidth resources. We are particularly interested in multi-tree multicast strategies in which every multicast session may contain many multicast trees. We show how the use of multiple trees increases network throughput and the load distribution in the network. We propose a class of round-robin algorithms that are based on successive selection of multicast trees for each multicast session, in a loosely cooperative, yet distributed fashion. Our best algorithm, the Cooperative Shortest Path Tree Packing (CSPTP) algorithm, performs well in a variety of scenarios, ranging from very sparse to dense applications. Through extensive simulations on random networks, we compare the performance of our algorithms with those commonly used in IP-multicast as well as theoretical upper bounds derived from network coding formulations. We show that the CSPTP can improve the throughput, and often achieves about 90% of the theoretical upper bound.