A New Energy Efficient Clustering Method for Wireless Sensor Networks Based on Cuckoo Optimization Algorithms and Genetic Composition Operator

Recently, wireless sensor networks have been recognized as the next generation power systems due to their participatory nature as a promising technology for smart grids. Due to the anomalous environments of the smart grid spectrum, the main challenge of these networks is to establish secure, energy efficient and cost-effective communication in this paper, a clustering algorithm base on cuckoo optimization algorithms and genetic is presented that maximizes spectrum efficiency with minimal energy consumption. The proposed method for exchanging information is based on the basic method of LEACH and PEGASIS, the cuckoo algorithm is used to select the cluster head in clustering and from a genetic algorithm with a combination operator in the preprocessing of nodes to generate new nests. Two parameters of random numbers (Random values assigned to nodes) and two-stage energy of each node were used, these parameters play a key role in the objective function as the determinant of clusters against exploratory shear and eclipse detection. Method simulation was performed in MATLAB software. The evaluation was based on the number of live nodes in different cycles and the area covered along with some basic parameters of sensor networks. The result showed that the life expectancy of the proposed method was better than the mentioned methods, energy efficiency of the nodes was also proved in the "number of packets sent" parameter.