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On Layout Optimization of Wireless Sensor Network Using Meta-Heuristic Approach

Abeeda Akram1, Kashif Zafar1, Adnan Noor Mian2, Abdul Rauf Baig3, Riyad Almakki3, Lulwah AlSuwaidan3, Shakir Khan3,4,*

1 National University of Computer and Emerging Sciences, Islamabad (Lahore Campus), 44000, Pakistan
2 Information Technology University, Lahore, Pakistan
3 Department of Information Systems, College of Computer and Information Sciences, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia
4 University Centre for Research and Development, Department of Computer Science and Engineering, Chandigarh University, Mohali 140413, India

* Corresponding Author: Shakir Khan. Email: email

Computer Systems Science and Engineering 2023, 46(3), 3685-3701. https://doi.org/10.32604/csse.2023.032024

Abstract

One of the important research issues in wireless sensor networks (WSNs) is the optimal layout designing for the deployment of sensor nodes. It directly affects the quality of monitoring, cost, and detection capability of WSNs. Layout optimization is an NP-hard combinatorial problem, which requires optimization of multiple competing objectives like cost, coverage, connectivity, lifetime, load balancing, and energy consumption of sensor nodes. In the last decade, several meta-heuristic optimization techniques have been proposed to solve this problem, such as genetic algorithms (GA) and particle swarm optimization (PSO). However, these approaches either provided computationally expensive solutions or covered a limited number of objectives, which are combinations of area coverage, the number of sensor nodes, energy consumption, and lifetime. In this study, a meta-heuristic multi-objective firefly algorithm (MOFA) is presented to solve the layout optimization problem. Here, the main goal is to cover a number of objectives related to optimal layouts of homogeneous WSNs, which includes coverage, connectivity, lifetime, energy consumption and the number of sensor nodes. Simulation results showed that MOFA created optimal Pareto front of non-dominated solutions with better hyper-volumes and spread of solutions, in comparison to multi-objective genetic algorithms (IBEA, NSGA-II) and particle swarm optimizers (OMOPSO, SMOPSO). Therefore, MOFA can be used in real-time deployment applications of large-scale WSNs to enhance their detection capability and quality of monitoring.

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APA Style
Akram, A., Zafar, K., Mian, A.N., Baig, A.R., Almakki, R. et al. (2023). On layout optimization of wireless sensor network using meta-heuristic approach. Computer Systems Science and Engineering, 46(3), 3685-3701. https://doi.org/10.32604/csse.2023.032024
Vancouver Style
Akram A, Zafar K, Mian AN, Baig AR, Almakki R, AlSuwaidan L, et al. On layout optimization of wireless sensor network using meta-heuristic approach. Comput Syst Sci Eng. 2023;46(3):3685-3701 https://doi.org/10.32604/csse.2023.032024
IEEE Style
A. Akram et al., "On Layout Optimization of Wireless Sensor Network Using Meta-Heuristic Approach," Comput. Syst. Sci. Eng., vol. 46, no. 3, pp. 3685-3701. 2023. https://doi.org/10.32604/csse.2023.032024



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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