Small-world Model Based Clustering Division Scheme in Wireless Sensor Network

Clustering is an effective approach to enhance performance in large-scale wireless sensor networks. SMCA (small-world model based clustering algorithm), a new clustering algorithm for wireless sensor networks is proposed in this paper, with high clustering coefficient and fault-tolerant properties. SMCA selectively remove some links in a virtual way by the analysis of the edges´ clustering coefficient and incorporate the limitations of the average hop counts and the number of nodes in each cluster. We analyze the gain in energy reduction in the form of average hop count reduction under the clustering algorithm, and conducted extensive simulations to validate our analysis. Simulation results show that our clustering mechanism not only balances the energy consumption, prolong the network lifetime, but also improve the network robustness, it clearly improve the network lifetime over LEACH and HEED for p=0.8, both the time until th.e first node dies and the time until the last node dies.