Genetic Algorithm Energy Optimization in 3D WSNs with Different Node Distributions Yousef Jaradat * , Mohammad Masoud, Ismael Jannoud and Dema Zeidan Department of Electrical Engineering, Al-Zaytoonah University of Jordan, Amman, 11733, Jordan *Corresponding Author: Yousef Jaradat. Email: y.jaradat@zuj.edu.jo Received: 09 October 2021; Accepted: 24 November 2021 Abstract: Optimal node clustering in wireless sensor networks (WSNs) is a major issue in reducing energy consumption and extending network node life time and reliability measures. Many techniques for optimizing the node clustering process in WSN have been proposed in the literature. The metaheuristic algorithms are a subset of these techniques. Genetic algorithm (GA) is an evolutionary metaheur- istic technique utilized to improve the network reliability and extending the net- work life time by optimizing the clustering process in the network. The GA dynamic clustering (GA-DC) algorithm is proposed in this paper to extend the network reliability and node life time of three dimensional (3D) WSN. The GA-DC algorithm made use of an improved fitness function that takes into account a variety of metrics such as energy expenditure per protocol round, clus- tering distance, and the number of long-distance wireless connections. There have been two types of simulation scenarios run. First, simulation results show that the GA-DC algorithm increases network life time by 80% and network throughput by 55% when compared to the well-known LEACH protocol. Second, simulation results show that the uniform node distribution outperforms the normal and expo- nential distributions in terms of network life time by 5.7% and 7%, network relia- bility by 4.2% and 76%, and data throughput by 10.85% and 19.54%, respectively Keywords: Dynamic GA; selection; mutation; crossover; clustering; energy efficient 1 Introduction Rapid technological advances in the field of micro electro mechanical systems (MEMS) have led to the development of cheap and autonomous miniature sensor nodes [1]. These sensor nodes have the capabilities of sensing and monitoring the environment, processing and aggregating data, and communicating data reports to each other or to a central location, usually referred to as the sink or the base station (BS). Wireless sensor network (WSN) is the interconnection of large number of these sensor nodes to serve an application-specific purpose [2]. Sensor nodes have limited battery energy sources and these batteries are mostly not rechargeable. The communication function of a sensor node usually consume energy the most [3]. If the energy source of a particular node gets drained, the node is considered dead and it becomes This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Intelligent Automation & Soft Computing DOI:10.32604/iasc.2022.024218 Article ech T Press Science