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Selection of Metaheuristic Algorithm to Design Wireless Sensor Network

Rakhshan Zulfiqar1,2, Tariq Javed1, Zain Anwar Ali2,*, Eman H. Alkhammash3, Myriam Hadjouni4

1 Hamdard University, Karachi, 75270, Pakistan
2 Electronic Engineering Department, Sir Syed University of Engineering & Technology, Karachi, Pakistan
3 Department of Computer Science, College of Computers and Information Technology, Taif University, P.O. Box 11099, Taif, 21944, Saudi Arabia
4 Department of Computer Sciences, College of Computer and Information Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh, 11671, Saudi Arabia

* Corresponding Author: Zain Anwar Ali. Email: email

Intelligent Automation & Soft Computing 2023, 37(1), 985-1000. https://doi.org/10.32604/iasc.2023.037248

Abstract

The deployment of sensor nodes is an important aspect in mobile wireless sensor networks for increasing network performance. The longevity of the networks is mostly determined by the proportion of energy consumed and the sensor nodes’ access network. The optimal or ideal positioning of sensors improves the portable sensor networks effectiveness. Coverage and energy usage are mostly determined by successful sensor placement strategies. Nature-inspired algorithms are the most effective solution for short sensor lifetime. The primary objective of work is to conduct a comparative analysis of nature-inspired optimization for wireless sensor networks (WSNs’) maximum network coverage. Moreover, it identifies quantity of installed sensor nodes for the given area. Superiority of algorithm has been identified based on value of optimized energy. The first half of the paper’s literature on nature-inspired algorithms is discussed. Later six metaheuristics algorithms (Grey wolf, Ant lion, Dragonfly, Whale, Moth flame, Sine cosine optimizer) are compared for optimal coverage of WSNs. The simulation outcomes confirm that whale optimization algorithm (WOA) gives optimized Energy with improved network coverage with the least number of nodes. This comparison will be helpful for researchers who will use WSNs in their applications.

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Cite This Article

APA Style
Zulfiqar, R., Javed, T., Ali, Z.A., Alkhammash, E.H., Hadjouni, M. (2023). Selection of metaheuristic algorithm to design wireless sensor network. Intelligent Automation & Soft Computing, 37(1), 985-1000. https://doi.org/10.32604/iasc.2023.037248
Vancouver Style
Zulfiqar R, Javed T, Ali ZA, Alkhammash EH, Hadjouni M. Selection of metaheuristic algorithm to design wireless sensor network. Intell Automat Soft Comput . 2023;37(1):985-1000 https://doi.org/10.32604/iasc.2023.037248
IEEE Style
R. Zulfiqar, T. Javed, Z.A. Ali, E.H. Alkhammash, and M. Hadjouni "Selection of Metaheuristic Algorithm to Design Wireless Sensor Network," Intell. Automat. Soft Comput. , vol. 37, no. 1, pp. 985-1000. 2023. https://doi.org/10.32604/iasc.2023.037248



cc 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.
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