An Enhanced Black Widow Optimization Algorithm for the Deployment of Wireless Sensor Networks

Hicham Deghbouch and Fatima Debbat
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Hicham Deghbouch: University Mustapha Stambouli of Mascara, Algeria
Fatima Debbat: University Mustapha Stambouli of Mascara, Algeria

International Journal of Swarm Intelligence Research (IJSIR), 2022, vol. 13, issue 1, 1-19

Abstract: In order to solve the deployment problem, which is considered a major issue that faces the design of efficient Wireless Sensor Networks (WSNs), a novel deployment algorithm based on an Enhanced Black Widow Optimization algorithm (EBWO) is proposed. The EBWO algorithm aims to determine the optimal number of sensors and their locations for optimizing both the coverage and the deployment cost. The BWO algorithm is adapted to solve the deployment problem by introducing a set of enhancements, which improves the search capability and the run time of the algorithm. A chaotic initialization is employed in the EBWO algorithm to strengthen the exploration capability of the initial population. Moreover, a modified reproduction mechanism is designed to assist the algorithm in optimizing the number of deployed sensors. Comparisons with modern state-of-the-art deployment methods show that the EBWO algorithm can deliver excellent solutions, where it is ranked first during all the simulations with a coverage difference varying between 3.34% and 7.94% from the other competitors.

Date: 2022
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