An efficient scalable weighted clustering algorithm for mobile Ad Hoc networks

We consider the problem of appropriate clusterhead selection in wireless ad-hoc networks where it is necessary to provide robustness in the face of topological changes caused by node motion, node failure and node insertion/removal. The main contribution of our work is a new strategy for clustering a wireless AD HOC network and improvements in WCA. We first derived a simple stability model and thereafter a load balancing clustering scheme. We showed that our algorithm outperforms the Weighted Clustering Algorithm (WCA) in terms of cluster formation and stability. One of the main ideas of our approach is to avoid clusterhead re-election and to reduce the computation and communication costs by implementing a non-periodic procedure for clusterhead election which is invoked on-demand. We strived to provide a trade-off between the uniformity of the load handled by the clusterheads and the connectivity of the network.