Vol.35, No.1, 2023, pp.705-725, doi:10.32604/iasc.2023.027545
OPEN ACCESS
ARTICLE
Efficient Hybrid Energy Optimization Method in Location Aware Unmanned WSN
  • M. Suresh Kumar1,*, G. A. Sathish Kumar2
1 Department of CSE, Sri Venkateswara College of Engineering, Sriperumbudur, 602117, India
2 Department of ECE, Sri Venkateswara College of Engineering, Sriperumbudur, 602117, India
* Corresponding Author: M. Suresh Kumar. Email:
Received 20 January 2022; Accepted 06 March 2022; Issue published 06 June 2022
Abstract
The growth of Wireless Sensor Networks (WSNs) has revolutionized the field of technology and it is used in different application frameworks. Unmanned edges and other critical locations can be monitored using the navigation sensor node. The WSN required low energy consumption to provide a high network and guarantee the ultimate goal. The main objective of this work is to propose hybrid energy optimization in local aware environments. The hybrid proposed work consists of clustering, optimization, direct and indirect communication and routing. The aim of this research work is to provide and framework for reduced energy and trusted communication with the shortest path to reach source to destination in WSN and an extending lifetime of wireless sensors. The proposed Artificial Fish Swarm Optimization algorithm is used for energy optimization in military applications which is simulated using Network Simulator(NS) tool. This work optimizes the energy level and the same is compared with various genetic algorithms (GA) and also the cluster selection process was compared with the fission-fusion (FF) selection method. The results of the proposed work show, improvement in energy optimization, throughput and time delay.
Keywords
Wireless sensor networks (WSNs); optimization algorithm; routing algorithm; military applications
Cite This Article
M. Suresh Kumar and G. A. Sathish Kumar, "Efficient hybrid energy optimization method in location aware unmanned wsn," Intelligent Automation & Soft Computing, vol. 35, no.1, pp. 705–725, 2023.
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