Intuitive cluster head selection in wireless sensor networks evaluation of the performance of algorithms

ABSTRACT INTUITIVE CLUSTER SELECTION IN WIRELESS SENSOR NETWORKS EVALUATION OF THE PERFORMANCES OF ALGORITHMS Abdülbaki DEMİREL Master Thesis Institute of Science and Technology Information System Engineering Supervisor: Assistant Professor Gürcan ÇETİN September 2022, 66 pages This thesis presents a strategy based on heuristic algorithms for reducing energy losses of sensor nodes in Wireless Sensor Networks (WSN) utilizing the LEACH routing protocol and increasing network active time. The issue was solved using the Genetic Algorithm (GA), Ant Colony Optimization (ACO), and Artificial Bee Colony (ABC) techniques, which are the most often used swarm-based optimization algorithms in the literature. In MATLAB R2017b software, a model based on Multi-Hop Routing was created to compare the performance results of the proposed techniques with the LEACH protocol. In situations where the gateway is positioned in different locations, the selected optimization methods are implemented in networks with 50 and 100 sensors, comparing energy consumption, data transmission, number of active / dead nodes, and average energy per sensor in each cycle. The comparisons revealed that all of the optimization techniques tested achieved much better outcomes than the LEACH process. When the algorithms were compared among themselves, the Genetic Algorithm-based LEACH model (LEACH-GA) produced the best results. According to the LEACH protocol, the LEACH-GA approach increased the number of rounds by around 50% and the amount of data packets by about 60% in 50-node network structures. When compared to the LEACH protocol, the LEACH-GA protocol increased the number of rounds by around 130% and the amount of data packets by about 150% in 100-node network structures. Keywords: Wireless Sensor Networks, Energy Efficiency, LEACH Protocol, Multi-Hop, Ant Colony Algorithm, Artificial Bee Colony Algorithm, Genetic Algorithm, Optimization