Optimization of energy consumption of wireless sensor networks in pursuit of moving targets using LEACH-C algorithm optimized by Cuckoo algorithm and Radial Basis Functions networks (Turkish Journal of Computer and Mathematics Education (TURCOMAT), 2021)
The problem of tracking moving targets in wireless sensor networks is one of the most challenging issues of thistype of network due to its high-powered consumption, limited energy and network lifetime.In this paper, the sensors of awireless sensor network is clustered by using the LEACH-C clustering algorithm and its performance is improved by using theCuckoo optimization algorithm (COA) and Levy flight. Then, with the help of the Radial Basis Functions network (RBF), thedata received from a moving target is transmitted to the central base station (BS) in a multi-step connection through the bestpath from the Cluster Heads (CH), which reduces the energy consumption of the Cluster Heads (CH) compared to using theLEACH - R algorithm. Using MATLAB simulator, a wireless sensor network is simulated with specifications of 100 *100meters, 100 wireless sensors with an initial energy of 0.5 volts, a fixed central base station (BS) and 1000 rounds of testing.The results shows that the location of the target is determined with the least time and energy, and the tracking is done with anappropriate accuracy and quality. Therefore, by comparison to the LEACH - R algorithm method a significant reduction in theenergy consumption of sensors is observed. As a result, the use of Cuckoo optimization algorithm (COA) and Levy Flightalgorithm in improving the LEACH-C clustering algorithm and the use of Radial Basis Functions network (RBF) in selectingthe best path in tracking reduces the energy consumption of sensors and increases the network lifetime.