Maximizing Nano-Sensor Node Coverage using BWO in WNSNs

Due to the energy constraints of nano-sensors, all network operations should be optimized in Wireless Nano-Sensor Networks (WNSNs). Nature-inspired metaheuristics have been widely used for solving the network problems such as routing, clustering, security and such areas in the literature. Therefore, in this paper, Black Widow optimization (BWO) based nano-node clustering algorithm is proposed in order to achieve maximum node coverage on WNSNs. The proposed algorithm is compared with 2 different Genetic Algorithm (GA) setups. According to the results, the proposed method successfully covers the nano-nodes by the chosen head nodes on the network up to 99.876% on average.