Abstract
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 are introduced as the inputs of fuzzy logic control (FLC). Meanwhile, the probability adjustment value, as the out of FLC, is fed back to the network for the generation of new clusters. Since the design of membership functions (MFs) of FLC has a significant impact on system performance, a particle swarm optimization (PSO) algorithm is used to optimize MFs and its optimization goal is to reduce the number of dead nodes and increase the remaining energy level in WSN. Simulation experiments were conducted for the low energy adaptive clustering hierarchy protocol (LEACH), the conventional FLC, FLC using genetic algorithm (GA), and FLC using PSO. The results show that the proposed FLC-PSO has the best performance among the four protocols and it can be used efficiently in energy management of WSN.
Highlights
Wireless sensor network (WSN) has been widely used in military facilities, environmental monitoring, intelligent transportation, smart home and medical care due to the advantages of cheapness, easy implementation and reliability [1][2]
particle swarm optimization (PSO) is a valuable approach for energy management in WSN, and we use it to optimize the parameters of fuzzy logic control (FLC) system
We presented an energy management model based on the clustering hierarchy method
Summary
Wireless sensor network (WSN) has been widely used in military facilities, environmental monitoring, intelligent transportation, smart home and medical care due to the advantages of cheapness, easy implementation and reliability [1][2]. Unlike [13,14,15,16], we use FLC to control the selection of CHs in WSN according to the overall remaining energy level and the number of dead nodes. The main contributions are: 1) unlike existing clustering routing protocols, we integrate the overall performance indicators (the overall remaining energy and the number of dead nodes) into WSN fuzzy control. 4) Simulation results show that in terms of the number of dead nodes, the remaining energy level, the number of cluster heads and the number of surviving nodes, the proposed FLC method using PSO has the best performance among the four protocols, i.e., the LEACH, the conventional FLC, the FLC using GA and the FLC using PSO.
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