A Novel Fuzzy Inference System Based on Hedge Algebras to Enhance Energy Efficiency in Wireless Sensor Networks

Improving the network lifetime of wireless sensor networks is one of the most research issues in recent years. Clustering strategy based on Low-Energy Adaptive Clustering Hierarchy (LEACH) can provide a good performance on the energy efficiency aspects. In which, fuzzy logic based on LEACH is suitable to adapt uncertain conditions in decision actions such as cluster formation and cluster head election. In this paper, a novel fuzzy Inference system based on hedge algebras is proposed to enhance energy efficiency in wireless sensor networks. The proposed model can bring a good decision support while utilizing special features of the hedge algebra as optimization of both input and output values at the same time. The performance of the proposed model is evaluated by comparing with the Mamdani type fuzzy inference system and the LEACH protocol. Simulation results show that the model has enhanced the energy efficiency aspect in wireless sensor networks.