Dynamic on-line group-tree matching for large scale group communications: a performance study

Traditional IP multicast faces a serious state scalability problem when there are a large number of groups in the network. Recently, a novel approach called aggregated multicast was proposed [6], in which multiple groups share one delivery tree. A key problem in aggregated multicast is group-tree matching (i.e., assigning groups to trees). In this paper, we formally study the dynamic version of the group-tree matching problem. We propose a generic dynamic on-line algorithm (GDOA) and provide an approach to determine the upper bound on its performance. We quantitatively compare the performance of GDOA and other existing on-line heuristics. Extensive simulations demonstrate that GDOA is a very practical solution with promising performance and reasonable computation requirement.