On the application of K-center algorithms to hierarchical traffic grooming

In this paper, we study a clustering technique for the hierarchical traffic grooming approach in WDM mesh networks. The objective is to minimize the cost of electronic ports, as well as the wavelength requirement of the solution. In the hierarchical grooming approach we have presented in previous work, the first phase is to partition a large mesh network into clusters of nodes. The clustering phase is very important for the final grooming result. Various clustering approaches have been considered in literature; however, not all are suitable for traffic grooming application because they do not take grooming goals into account. In this work, we select a suitable existing clustering algorithm, developed for the K-center problem, and study its performance as a clustering algorithm for hierarchical grooming. We then improve the algorithm, adapting it specifically for the traffic grooming problem. Experimental results show that the improved version generally provides better solutions than the original algorithm, on various traffic patterns, for the general topology grooming problem instances