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Title	Optimizing Coverage In Wireless Sensor Networks Using The Cheetah Meta-Heuristic Algorithm
ID_Doc	40777
Authors	Basirnezhad M.; Houshmand M.; Hosseini S.A.; Jalali M.
Year	2023
Published	7th International Conference on Internet of Things and Applications, IoT 2023
DOI	http://dx.doi.org/10.1109/IoT60973.2023.10365363
Abstract	A wireless sensor network (WSN) consists of many sensor nodes that self-organize to form a distributed network system. These networks are mostly installed randomly in cities. To ensure data transmission, reception, and processing in smart city development, many sensor nodes need to be installed throughout the city due to factors causing inadequate coverage of monitoring areas. However, heterogeneous distribution may lead to large losses of resources. To solve this problem, in this research, an optimization model for WSN coverage is proposed based on the Cheetah Optimizer (CO) algorithm. CO is a nature-inspired algorithm inspired by cheetah hunting tactics. Three main strategies used by cheetahs for hunting, searching, sitting and waiting, and attacking are included in the algorithm. In addition, a fourth strategy, leaving prey and returning home, is also added to increase population diversity, convergence performance, and robustness. Different test functions demonstrate that CO outperforms other algorithms significantly in the literature. Moreover, for optimizing WSN coverage, CO produces a higher coverage rate compared to other meta-heuristic algorithms and improved algorithms mentioned in the literature for addressing the WSN coverage optimization problem. © 2023 IEEE.
Author Keywords	cheetah optimizer; coverage optimization; metaheuristic algorithm; wireless sensor network

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