Dynamic Clustering based on Evolutionary Algorithms Asexual Reproduction Optimization (ARO)

Abstract

Wireless sensor networks (WSNs) in the dynamic system have various limitations, of which the limitation of using and supplying of energy, bandwidth limitation of wireless communication links among the nodes can be cited. In spite of the various applications of these networks and the efforts made to eliminate the raised constraints, the challenges still survive, The ARO optimization method which is responsible for the dynamic clustering of the system is used in this study. Then, according to fuzzy algorithm, it performs optimal routing between the clusters. In the new proposed method here, F_WU_ARO wireless sensor network is defined as 200 sensors, distributed uniformly and randomly in a square-shaped area with an area of 100 square meters. Moreover, each cluster-head (CH) has the address or the location of its neighboring clusters and can send the relevant data if needed. In the proposed hybrid method of F_WU_ARO, with its used parameters, the residual energy based on the death of the first, middle, and last network sensors showed an improvement in the level of system sustainability in comparison to F_WU_PSO algorithm at the values of 1.5, 3, and 5 percent, respectively. In addition, it showed a reduction in the time spent with the amount of 0.14 (based on the minute).