Weight based adaptive clustering in wireless ad hoc networks

This paper proposes a new weight based adaptive clustering algorithm (WBACA) for mobile ad-hoc networks (MANETs). MANETs are multi-hop wireless packet networks in which all the nodes cooperatively maintain network connectivity without the aid of any infrastructure networks. The proposed WBACA takes into account the transmission power, transmission rate, mobility, battery power and the degree of a node for forming clusters. Unlike the lowest-ID algorithm, which finds only the local minima of IDs and the weighted clustering algorithm (WCA), which finds the global minima of weights, the proposed WBACA finds the local minima of weights for the clustering process. Through simulations, we have compared the performance of our algorithm with that of the lowest-ID and WCA algorithms in terms of the number of clusters formed, number of reaffiliations, and the time delay in starting up the clustering process. The results demonstrate the superior performance of the proposed algorithm.