Destination-driven routing for low-cost multicast

We present a destination-driven algorithm that optimizes for applications, such as group video or teleconferencing, that require multicast trees with low total cost. The destination-driven algorithm uses a greedy strategy based on shortest-path trees and minimal spanning trees but biases routes through destinations. The performance of the algorithm is analyzed through extensive simulation and compared with several Steiner tree heuristics and the popular shortest-path tree (SPT) method. The algorithm is found to produce trees with significantly lower overall cost than the SPT while maintaining reasonable per-destination performance. Its performance also compares well with other known Steiner heuristics. Moreover, the algorithm does not suffer from high complexity common to most Steiner tree heuristics and builds a route by querying only incident links for cost information.