Energy Management using Optimal Fuzzy Logic Control in Wireless Sensor Network

Energy is a key factor that affects the lifetime of wireless sensor network (WSN). This paper proposes an adaptive energy management model to improve the energy efficiency in WSN. Unlike existing clustering routing protocols, the overall performance indicators of the network are introduced into fuzzy logic control (FLC). And the output of FLC, i.e., the adjustment value of cluster head scale, is fed back and used to generate a new cluster. Considering the design of membership functions (MFs) of FLC has a significant impact on system performance, particle swarm optimization (PSO) is used. The optimization goal of MFs is to reduce the number of dead nodes and increase the remaining energy level. Simulation experiments were conducted for the low energy adaptive clustering hierarchy protocol (LEACH), the conventional FLC, the FLC using genetic algorithm (GA), and the FLC using PSO. The results show that the proposed FLC-PSO has the best performance among the four protocols. Therefore, it can be used efficiently in energy management of WSN.