Optimal partitioning of heterogeneous traffic sources in highway cellular systems

Given a linear array of n heterogeneous traffic sources which generate multiple types of traffic among themselves, we consider the problem of finding a set of disjoint clusters to cover n traffic sources such that it minimizes the total communication cost for the entire system where the cost of intra-cluster communication is usually lower than that of inter-cluster communication for each type of traffic. The optimization problem is transformed into the dual based on the relative cost which is the communication cost if a pair of nodes are in different clusters of a partition. Using the relative cost matrix, an efficient algorithm of O(mn/sup 2/), where m is the number of clusters in a partition, is designed by dynamic programming.