Energy/Distance Estimation-based and Distributed Selection/Migration of Cluster Heads in Wireless Sensor Networks

In sensor networks, sensor nodes have limited computational capacity, power and memory. Thus energy efficiency is one of the most important requirements. How to extend the lifetime of wireless sensor networks has been widely discussed in recent years. However, one of the most effective approaches to cope with power conservation, network scalability, and load balancing is clustering technique. The function of a cluster head is to collect and route messages of all the nodes within its cluster. Cluster heads must be changed periodically for low energy consumption and load distribution. In this paper, we propose an energy-aware cluster head selection algorithm and Distance Estimation-based distributed Clustering Algorithm (DECA) in wireless sensor networks, which exchanges cluster heads for less energy consumption by distance estimation. Our simulation result shows that DECA can improve the system lifetime of sensor networks up to three times compared to the conventional scheme.