A Multi-parameter Weighted Clustering Algorithm for Mobile Ad Hoc Networks

Clustering is an efficient way of network topology management, and the hierarchical structure obtained by clustering algorithm can largely improve the performance of Mobile Ad Hoc Network (MANET). To better accommodate MANET, we propose a Multi-parameter Weighted Clustering (MWC) algorithm which takes into consideration three parameters: residual power, connectivity, and average mobility. We also designed different average mobility parameter for two typical MANET models, that is, Relative Stability (RS) for Random Walk Mobility (RWM) networks and Moving Correlation (MC) for Reference Point Group Mobility (RPGM) networks. Simulation results showed that the proposed algorithm has a better performance than HD and MOBIC in three aspects: topology simplicity, environment adaptability, and cluster stability.