Title: Investigation of multi-objective optimisation techniques to minimise the localisation error in wireless sensor networks

Authors: Harriet Puvitha; Saravanan Palani; V. Vijayakumar; Logesh Ravi; V. Subramaniyaswamy

Addresses: School of Computing, SASTRA Deemed University, Thanjavur, Tamil Nadu, India ' School of Computing, SASTRA Deemed University, Thanjavur, Tamil Nadu, India ' Briteyellow Ltd, Bedford MK43 0BT, UK ' Sri Ramachandra faculty of Engineering and Technology, Sri Ramachandra Institute of Higher Education and Research, Chennai, Tamil Nadu, India ' School of Computing, SASTRA Deemed University, Thanjavur, Tamil Nadu, India

Abstract: Wireless Sensor Networks (WSN) have a major role in remote sensing environments. In recent trends sensors are used in various wireless technologies due to their smaller size, cheaper rates and ability to communicate with each other to create a network. The sensor network is the convergent technology of micro-electronics and electro-mechanical technologies. The localisation process can determine the location of each node in the network. Mobility-assisted localisation is an effective technique for node localisation using mobility anchor. The mobile anchor is also used to optimise the path planning for the location-aware mobile nodes. In this proposed system, a multi-objective method has been proposed to minimise the distance between the source and the target node using the Dijkstra algorithm with obstacle avoidance. The Grasshopper Optimisation Algorithm (GOA), and Butterfly Optimisation Algorithm (BOA) based multi-objective models have been implemented along with obstacle avoidance and path planning. The proposed system maximises the localisation accuracy. Also it minimises the localisation error and the computation time when comparing with existing systems.

Keywords: localisation models; grasshopper optimisation; butterfly optimisation; Dijkstra; path planning.

DOI: 10.1504/IJGUC.2021.112459

International Journal of Grid and Utility Computing, 2021 Vol.12 No.1, pp.33 - 42

Received: 08 Apr 2019
Accepted: 28 Jun 2019
Published online: 19 Jan 2021 *

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