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Accelerated Particle Swarm Optimization Algorithm for Efficient Cluster Head Selection in WSN

Imtiaz Ahmad1, Tariq Hussain2, Babar Shah3, Altaf Hussain4, Iqtidar Ali1, Farman Ali5,*

1 Institute of Computer Sciences and Information Technology, The University of Agriculture, Peshawar, Pakistan
2 School of Computer Science and Technology, Zhejiang Gongshang University, Hangzhou, China
3 College of Technological Innovation, Zayed University, Dubai, United Arab Emirates
4 School of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China
5 Department of Applied AI, School of Convergence, College of Computing and Informatics, Sungkyunkwan University, Seoul, 03063, South Korea

* Corresponding Author: Farman Ali. Email: email

Computers, Materials & Continua 2024, 79(3), 3585-3629. https://doi.org/10.32604/cmc.2024.050596

Abstract

Numerous wireless networks have emerged that can be used for short communication ranges where the infrastructure-based networks may fail because of their installation and cost. One of them is a sensor network with embedded sensors working as the primary nodes, termed Wireless Sensor Networks (WSNs), in which numerous sensors are connected to at least one Base Station (BS). These sensors gather information from the environment and transmit it to a BS or gathering location. WSNs have several challenges, including throughput, energy usage, and network lifetime concerns. Different strategies have been applied to get over these restrictions. Clustering may, therefore, be thought of as the best way to solve such issues. Consequently, it is crucial to analyze effective Cluster Head (CH) selection to maximize efficiency throughput, extend the network lifetime, and minimize energy consumption. This paper proposed an Accelerated Particle Swarm Optimization (APSO) algorithm based on the Low Energy Adaptive Clustering Hierarchy (LEACH), Neighboring Based Energy Efficient Routing (NBEER), Cooperative Energy Efficient Routing (CEER), and Cooperative Relay Neighboring Based Energy Efficient Routing (CR-NBEER) techniques. With the help of APSO in the implementation of the WSN, the main methodology of this article has taken place. The simulation findings in this study demonstrated that the suggested approach uses less energy, with respective energy consumption ranges of 0.1441 to 0.013 for 5 CH, 1.003 to 0.0521 for 10 CH, and 0.1734 to 0.0911 for 15 CH. The sending packets ratio was also raised for all three CH selection scenarios, increasing from 659 to 1730. The number of dead nodes likewise dropped for the given combination, falling between 71 and 66. The network lifetime was deemed to have risen based on the results found. A hybrid with a few valuable parameters can further improve the suggested APSO-based protocol. Similar to underwater, WSN can make use of the proposed protocol. The overall results have been evaluated and compared with the existing approaches of sensor networks.

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APA Style
Ahmad, I., Hussain, T., Shah, B., Hussain, A., Ali, I. et al. (2024). Accelerated particle swarm optimization algorithm for efficient cluster head selection in WSN. Computers, Materials & Continua, 79(3), 3585-3629. https://doi.org/10.32604/cmc.2024.050596
Vancouver Style
Ahmad I, Hussain T, Shah B, Hussain A, Ali I, Ali F. Accelerated particle swarm optimization algorithm for efficient cluster head selection in WSN. Comput Mater Contin. 2024;79(3):3585-3629 https://doi.org/10.32604/cmc.2024.050596
IEEE Style
I. Ahmad, T. Hussain, B. Shah, A. Hussain, I. Ali, and F. Ali "Accelerated Particle Swarm Optimization Algorithm for Efficient Cluster Head Selection in WSN," Comput. Mater. Contin., vol. 79, no. 3, pp. 3585-3629. 2024. https://doi.org/10.32604/cmc.2024.050596



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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