Stable Clustering Based on Motion Similarity Evaluation in Mobile Ad Hoc Networks

Clustering is an important technique in mobile ad hoc networks to provide a framework for management and reduce the overhead of route acquisition. In this paper, a motion similarity-based multi-hop clustering (MMC) algorithm is proposed, which is on the basis of a motion similarity evaluation (MSE). The proposed clustering scheme aims to form more stable multi-hop clusters by prolonging cluster lifetime and reducing the clustering iterations even in highly dynamic environment. Simulation results show that the performance of the proposed algorithm is superior to two widely referenced clustering algorithms, the least cluster change algorithm and the mobility based clustering algorithm, in terms of mean cluster lifetime, mean cluster member resident time, average number of cluster head changes.