This paper studies the routing algorithms for multi-destination connections where each destination may require different amount of data streams. This asymmetric feature can arise mostly in a large and/or heterogeneous network environment. There are mainly two reasons for this. One is that terminal equipments may have different capabilities. The other is that users may have various interests in the same set of information. We first define the asymmetric multicast problem and describe an original routing method for this type of multicast. The method is then employed in the presented routing algorithms, which can be run in multi-cluster environment. The multi-cluster architecture is considered to be effective for running routing in the networks, where a variety of operating methods might be applied in different clusters but global network performance is required. Our algorithms are designed based on some classical Steiner tree heuristics. The basic goal of our algorithms is to make routing decisions for the asymmetric multicast connections with minimum-cost purpose. In addition, we also consider delay constraint requirements in the multicast connections and propose correspondent algorithms. We compare the performance between SPT (Shortest Path Tree)-based algorithms and the presented algorithms by simulations. We show that performance difference exists among the different types of the algorithms.

This paper addresses the optimum routing problem of multipoint connection in large-scale networks. A number of algorithms for routing of multipoint connection have been studied so far, most of them, however, assume the availability of complete network information. Herein, we study the problem under the condition that only partial information is available to routing nodes and that routing decision is carried out in a distributed cooperative manner. We consider the network being partitioned into clusters and propose a cluster-based routing approach for multipoint connection. Some basic principles for network clustering are discussed first. Next, the original multipoint routing problem is defined and is divided into two types of subproblems. The global optimum multicast tree then can be obtained asymptotically by solving the subproblems one after another iteratively. We propose an algorithm and evaluate it with computer simulations. By measuring the running time of the algorithm and the optimality of resultant multicast tree, we show analysis on the convergent property with varying network cluster sizes, multicast group sizes and network sizes. The presented approach has two main characteristics, 1) it can yield asymptotical optimum solutions for the routing of multipoint connection, and 2) the routing decisions can be made in the environment where only partial information is available to routing nodes.