Bat Inspired Technique for Effective Clustering in Wireless Sensor Networks

Wireless sensor networks are functioned by using battery sources. A lot of sensors in the network is collaboratively utilized for performing, sensing, processing, and communication. These tasks use additional energy and have an effect on lifetime. Clustering methodology provides a better solution for performing the data communication process which extends the lifetime. In this paper, a bat-inspired technique is presented in LEACH-C to select the suitable cluster head. The proposed methodology utilizes the echolocation performance of bats for balancing exploration and exploitation phases in the optimization process. The fitness function is computed by using residual energy and node distance. The proposed method is estimated with the performance metrics of a lifetime, energy consumption, and the alive nodes. The proposed methodology prolongs the lifetime and reduces energy utilization.