With the arrival of B-ISDN, point-to-point routing alone is no longer adequate. A new class of computer and video related services, such as mass mailing, TV broadcasting, teleconferencing, and video 900 service, requires the network to handle multiple destination routing (MDR). Multiple destination routing enables widespread usage of multipoint services at a lower cost than networks using point-to-point routing. With this in mind, network providers are researching more into MDR algorithms. However, the MDR problem itself is very complex. Furthermore, its optimal solution, the Steiner tree problem, is NP-complete and thus not suitable for real-time applications. Recently, various algorithms which approximate the Steiner tree problem have been proposed and, in this invited paper, we will summarize the simulation results of these algorithms. But first, we will define the MDR problem, the issues involved, and the benchmark used to compare MDR algorithms. Then, we will categorize the existing MDR algorithms into a five-level classification tree. Lastly, we will present various published results of static algorithms and our own simulation results of quasi-static algorithms.

With the arrival of B-ISDN, widespread usage of multicast services such as TV broadcasting and video 900 services will increase the possibility of network congestion unless efficient multiple destination routing (MDR) algorithms are used. Current MDR algorithms using link cost based on bandwidth usage or distance to compute the minimum cost routing tree do not take into account the vast amount of information collected by intelligent network (IN) databases. In this paper, we propose a multicast routing algorithm which modifies the way the cost is calculated by using the predicted traffic statistics collected by IN databases. We also show that the traffic handling characteristics vastly improved over conventional MDR algorithms.