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Intelligent Aquila Optimization Algorithm-Based Node Localization Scheme for Wireless Sensor Networks

by Nidhi Agarwal1,2, M. Gokilavani3, S. Nagarajan4, S. Saranya5, Hadeel Alsolai6, Sami Dhahbi7,*, Amira Sayed Abdelaziz8

1 Department of Information Technology, KIET Group of Institutions, Delhi, 201206, India
2 Department of Computer Science and Engineering, Indira Gandhi Delhi Technical University for Women, New Delhi, Delhi, 110006, India
3 Department of Computer Science and Engineering, KL University, Vaddeswaram, Andhra Pradesh, 522502, India
4 Department of Electronics & Communication Engineering, Saveetha Engineering College, Chennai, 602105, India
5 Department of Computer Science and Engineering, K. Ramakrishnan College of Engineering, Tiruchirapalli, 621112, India
6 Department of Information Systems, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, P. O. Box 84428, Riyadh, 11671, Saudi Arabia
7 Department of Computer Science, College of Science & Art at Mahayil, King Khalid University, Muhayel Aseer, 62529, Saudi Arabia
8 Department of Digital Media, Faculty of Computers and Information Technology, Future University in Egypt, New Cairo, 11835, Egypt

* Corresponding Author: Sami Dhahbi. Email: email

Computers, Materials & Continua 2023, 74(1), 141-152. https://doi.org/10.32604/cmc.2023.030074

Abstract

In recent times, wireless sensor network (WSN) finds their suitability in several application areas, ranging from military to commercial ones. Since nodes in WSN are placed arbitrarily in the target field, node localization (NL) becomes essential where the positioning of the nodes can be determined by the aid of anchor nodes. The goal of any NL scheme is to improve the localization accuracy and reduce the localization error rate. With this motivation, this study focuses on the design of Intelligent Aquila Optimization Algorithm Based Node Localization Scheme (IAOAB-NLS) for WSN. The presented IAOAB-NLS model makes use of anchor nodes to determine proper positioning of the nodes. In addition, the IAOAB-NLS model is stimulated by the behaviour of Aquila. The IAOAB-NLS model has the ability to accomplish proper coordinate points of the nodes in the network. For guaranteeing the proficient NL process of the IAOAB-NLS model, widespread experimentation takes place to assure the betterment of the IAOAB-NLS model. The resultant values reported the effectual outcome of the IAOAB-NLS model irrespective of changing parameters in the network.

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APA Style
Agarwal, N., Gokilavani, M., Nagarajan, S., Saranya, S., Alsolai, H. et al. (2023). Intelligent aquila optimization algorithm-based node localization scheme for wireless sensor networks. Computers, Materials & Continua, 74(1), 141-152. https://doi.org/10.32604/cmc.2023.030074
Vancouver Style
Agarwal N, Gokilavani M, Nagarajan S, Saranya S, Alsolai H, Dhahbi S, et al. Intelligent aquila optimization algorithm-based node localization scheme for wireless sensor networks. Comput Mater Contin. 2023;74(1):141-152 https://doi.org/10.32604/cmc.2023.030074
IEEE Style
N. Agarwal et al., “Intelligent Aquila Optimization Algorithm-Based Node Localization Scheme for Wireless Sensor Networks,” Comput. Mater. Contin., vol. 74, no. 1, pp. 141-152, 2023. https://doi.org/10.32604/cmc.2023.030074



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
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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