An energy-efficient clustering algorithm for large scale wireless sensor networks

Abstract

Wireless sensor networks (WSNs) consist of a large number of sensor nodes with limited energy resources. Collecting and transmitting sensed information in an efficient way is one of the challenges in these networks. The clustering algorithm is a solution to reduce energy consumption. It can be helpful to the scalability and network life time. However, the problem of unbalanced energy dissipation is an important issue in cluster based WSNs. In this paper, a new clustering algorithm, named PDKC, is proposed for wireless sensor networks based on node deployment knowledge. However, in PDKC, sensor node location is modelled by Gaussian probability distribution function instead of using GPSs or any other location-aware devices. In the proposed method, cluster heads are selected based on node deployment information, residual energy, node degree and their distance from the base station. The Simulation results indicate that PDKC algorithm prolongs network lifetime, improves the network coverage and balance energy dissipation in comparison to other works.