(untitled) (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 this type of network due to its high-powered consumption, limited energy and network lifetime.In this paper, the sensors of a wireless sensor network is clustered by using the LEACH-C clustering algorithm and its performance is improved by using the Cuckoo optimization algorithm (COA) and Levy flight. Then, with the help of the Radial Basis Functions network (RBF), the data received from a moving target is transmitted to the central base station (BS) in a multi-step connection through the best path from the Cluster Heads (CH), which reduces the energy consumption of the Cluster Heads (CH) compared to using the LEACH - R algorithm. Using MATLAB simulator, a wireless sensor network is simulated with specifications of 100 *100 meters, 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 an appropriate accuracy and quality. Therefore, by comparison to the LEACH - R algorithm method a significant reduction in the energy consumption of sensors is observed. As a result, the use of Cuckoo optimization algorithm (COA) and Levy Flight algorithm in improving the LEACH-C clustering algorithm and the use of Radial Basis Functions network (RBF) in selecting the best path in tracking reduces the energy consumption of sensors and increases the network lifetime.