Open Access

ARTICLE

Metaheuristics Based Node Localization Approach for Real-Time Clustered Wireless Networks

by R. Bhaskaran¹, P. S. Sujith Kumar², G. Shanthi³, L. Raja⁴, Gyanendra Prasad Joshi⁵, Woong Cho^6,*

1 Department of Information Technology, PSNA College of Engineering and Technology, Dindigul, 624622, India
2 Department of Computer Science and Engineering, MEA Engineering College, Mallapuram, 679325, Kerala, India
3 Department of Electronics and Communication Engineering, Rajalakshmi Institute of Technology, Kuthambakkam, Chennai, 600124, India
4 Department of Electronics and Communication Engineering, Sri Eshwar College of Engineering, Coimbatore, 641202, India
5 Department of Computer Science and Engineering, Sejong University, Seoul, 05006, Korea
6 Department of Software Convergence, Daegu Catholic University, Gyeongsan, 38430, Korea

* Corresponding Author: Woong Cho. Email:

Computer Systems Science and Engineering 2023, 44(1), 1-17. https://doi.org/10.32604/csse.2023.024973

Received 06 November 2021; Accepted 22 December 2021; Issue published 01 June 2022

Abstract

In recent times, real time wireless networks have found their applicability in several practical applications such as smart city, healthcare, surveillance, environmental monitoring, etc. At the same time, proper localization of nodes in real time wireless networks helps to improve the overall functioning of networks. This study presents an Improved Metaheuristics based Energy Efficient Clustering with Node Localization (IM-EECNL) approach for real-time wireless networks. The proposed IM-EECNL technique involves two major processes namely node localization and clustering. Firstly, Chaotic Water Strider Algorithm based Node Localization (CWSANL) technique to determine the unknown position of the nodes. Secondly, an Oppositional Archimedes Optimization Algorithm based Clustering (OAOAC) technique is applied to accomplish energy efficiency in the network. Besides, the OAOAC technique derives a fitness function comprising residual energy, distance to cluster heads (CHs), distance to base station (BS), and load. The performance validation of the IM-EECNL technique is carried out under several aspects such as localization and energy efficiency. A wide ranging comparative outcomes analysis highlighted the improved performance of the IM-EECNL approach on the recent approaches with the maximum packet delivery ratio (PDR) of 0.985.

---

Keywords

---