Density, distance and energy based clustering algorithm for data aggregation in wireless sensor networks

Wireless sensor networks (WSNs) are wireless networks which consist of distributed sensor nodes monitoring physical and environmental conditions. Due to the energy limit of sensor nodes, prolonging lifetime of wireless sensor networks (WSNs) is a big challenge. In this paper, we propose a new clustering method called Density, Distance and Energy based Clustering (DDEC) to improve network performance. DDEC partitions the network into clusters with similar member number, so as to achieve load balancing. Then a cluster head is selected for each cluster based on three criteria: residual energy, distance and density, which achieves to minimize intra-communication cost and prolong cluster lifetime. In our performance analysis, we compare DDEC with another clustering method called DDCHS. The results show that DDEC outperforms DDCHS in terms of alive node number and energy consumption.