Connected k-hop clustering in ad hoc networks

In wireless ad hoc networks, clustering is one of the most important approaches for many applications. A connected k-hop clustering network is formed by electing clusterheads in k-hop neighborhoods and finding gateway nodes to connect clusterheads. Therefore, the number of nodes to be flooded in broadcast related applications could be reduced. In this paper, we study the localized solution for the connectivity issue of clusterheads with less gateway nodes. We develop the adjacency-based neighbor clusterhead selection rule (A-NCR) by extending the "2.5" hops coverage theorem and generalizing it to k-hop clustering. We then design the local minimum spanning tree based gateway algorithm (LMSTGA), which could be applied on the adjacent clusterheads selected by A-NCR to further reduce gateway nodes. In the simulation, we study the performance of the proposed approaches, using different values for parameter k. The results show that the proposed approaches generate a connected k-hop clustering network, and reduce the number of gateway nodes effectively.