Optimization of Wireless Sensor Networks Using Metaheuristic Algorithms

Wireless sensor networks (WSNs) are helpful in a wide range of application including defense, environmental, military, healthcare, office, and home-related applications. While sensing the environment and sending data collected to the center, they face many challenges and problems affecting their performance. The challenges are localization, coverage, and energy efficiency, and they all affect the performance of the WSNs. Metaheuristic algorithms are widely used for their adaptability and ability to find optimal solutions through global search. The metaheuristic algorithms inspired by the natural phenomena help solve complex global engineering problems. These algorithms facilitate the determination of optimal solutions for a wide range of optimization problems. This review critically examines research publications with particular emphasis on the advancements achieved as well as the limitations and gaps identified in each study. This article will review related works on using metaheuristic algorithms to optimize WSN challenges. The review paper aims to assess each work's objectives, strengths and weaknesses of each work.