Connectivity Based k-Hop Clustering in Wireless Networks

In this paper we describe several new clustering algorithms for nodes in a mobile ad hoc network. The main contribution is to generalize the cluster definition and formation algorithm so that a cluster contains all nodes that are at distance at most k hops from the clusterhead. We also describe algorithms for modifying cluster structure in the presence of topological changes. We also proposed an unified framework for most existing and new clustering algorithm where a properly defined weight at each node is the only difference in otherwise the same algorithm. This paper studied node connectivity and node ID as two particular weights, for k=1 and k=2. Finally, we propose a framework for generating random unit graphs with obstacles.