Some important classes of multi-point bandwidth-intensive applications like video-conferencing with mixing and the distributed classroom can be characterized as consisting of a broadcast from a source node to several destinations nodes, and point-to-point flows from the destination nodes to the source node. Determining a tree in an arbitrary mesh network which satisfies the bandwidth constraints and minimizes the cost of reserved bandwidth is a NP-hard problem. In this paper, we look at some heuristics that can be used to solve the problem of routing these multi-point connections. The heuristics are based on finding the capacity-constrained minimum cost tree which minimizes the cost of bandwidth reserved for point-to-point communication from destinations to the source, and weights are assigned to minimize the number of extra nodes in the tree which increase the cost of bandwidth reserved from the source to the destination. A theoretical bound on the performance of some of the heuristics, as well as simulation results comparing their performance to that of the optimum solution are presented. The results are encouraging, the heuristics find a tree with a cost within 2% of the optimum on the average, and with a cost within 10% of the optimum in those cases when the heuristic fails to find the optimum tree.

A communication network management structure is considered which consists of regional management centers. These centers receive fault reports from individual nodes in their region and take appropriate action based on the information gathered. The regional centers may report their information to a central management center if required. The problem of partitioning a network into a given number of regions (or clusters) is considered such that there is one management center assigned to each region and the total distance all the nodes to their assigned center is minimized. An efficient algorithm to solve this problem is presented. It is shown that the problem becomes NP-complete when there are two management centers per region with the regions being disjoint. Some heuristic solutions to this problem are also presented.>

The problem of partitioning a large computer network into clusters in order to reduce the amount of network resources consumed by the routing algorithm is addressed. The clustering problem is formulated as a general graph partitioning problem. It is shown that the problem of partitioning a graph into a minimum number of clusters with unit weight vertices and a given weight bound on the cluster size is NP-complete if each cluster is required to be internally connected. It is also shown that if a diameter bound is imposed on the cluster instead of the weight bound, then the problem is NP-complete, even when cluster connectivity is not required. An optimum partitioning algorithm is presented for the latter problem when the graph is a tree. An optimum partitioning algorithm is presented for another problem in which each cluster is required to contain exactly one of a set of specified vertices called cluster heads.>

Three directory schemes are investigated: the local cache (LC) scheme in which there is a cache at the network nodes to store the results of a previous query for a remote resource so that a subsequent query for that resource can be resolved locally, and two enhancements of this scheme, namely the regional cache server (RCS) scheme and the cooperating cache servers (CCS) scheme, in which the queries not resolved locally are funneled through designated nodes or servers to reduce multiple network searchers for a given resource. The performance of these schemes in terms of the network search rate is dependent on the cache sizes at the nodes and servers, the probability distribution for queuing resources, and the cache replacement policy used to displace resources from the cache to accommodate newly discovered ones. Two policies are investigated: A/sub 0/, which is the optimal policy for the LC scheme, and the least recently used policy, which is of practical importance.>

A design is presented for rerouting existing sessions (virtual circuits) under certain conditions to improve the routing performance. The authors call this mechanism selective load redistribution (SLRD). SLRD is a fully distributed algorithm which redistributes sessions in parallel at different nodes by carefully selecting the amount of traffic to be switched. The performance of the algorithm is evaluated by a simulation model. The results for several sample networks show that the algorithm performs very well even though the information available to the nodes for route computation may not be completely accurate.>