Energy-Efficient Cluster-Head Selection Based on a Fuzzy Expert System in Wireless Sensor Networks

Abstract

Energy efficiency is a key issue in the design of wireless sensor networking systems because each sensor node carries power source of limited capacity and cannot be easily replaced. To achieve high energy efficiency, a typical approach is to cluster the sensor nodes in some way so that energy is conserved. In practice, it is critical to select some nodes as cluster-heads to form clusters so that the lifetime of the networking system can be maximized due to the energy saving. This paper aims to develop a fuzzy expert system which intelligently assigns the cluster-heads in wireless sensor networks for optimal energy efficiency. Three linguistic variables are employed in the design of our fuzzy expert system, which include selection probability, distance from the base station and the sum of distances between the selected node and the other nodes with lower than the average energy. Simulation results show that the proposed fuzzy expert system in this paper prolonged the lifetime of the network, reduced energy consumption, and outperformed other existing methods such as LEACH, CHEF and DEEC.