A Novel Approach for Energy Optimization of Wireless Sensors Network by Adaptive Clustering

Energy optimization has a major role in modern researches. While, energy optimization of wireless sensors network is the most important, because of the limitations of the battery energy of the wireless sensor. This paper concentrate on energy optimization by introducing a novel and an adaptive clustering algorithm that is fuzzy logic based. The result of our work minimizes the interval between the first node (sensor) death and the last one. The dead node interval minimization to a value near to zero increases the efficiency of energy and saves 93% of traditional clustering of wireless sensors network. This paper compares the result of this novel approach to LEACH, LEACH-M, and LEACH-L algorithms.