Title: Wireless sensor deployment optimisation based on cost, coverage, connectivity, and load balancing

Authors: Jun Wang; Dongxu Luo; Funan Peng; Weiru Chen; Jun Liu; Hualiang Zhang

Addresses: College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang 110142, China; Key Laboratory of Industrial Intelligence Technology on Chemical Process, Shenyang University of Chemical Technology, Shenyang 110142, China ' College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang 110142, China; Key Laboratory of Industrial Intelligence Technology on Chemical Process, Shenyang University of Chemical Technology, Shenyang 110142, China ' College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang 110142, China; Key Laboratory of Industrial Intelligence Technology on Chemical Process, Shenyang University of Chemical Technology, Shenyang 110142, China ' College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang 110142, China; Key Laboratory of Industrial Intelligence Technology on Chemical Process, Shenyang University of Chemical Technology, Shenyang 110142, China ' College of Computer Science and Technology, Shenyang University of Chemical Technology, Shenyang 110142, China; Key Laboratory of Industrial Intelligence Technology on Chemical Process, Shenyang University of Chemical Technology, Shenyang 110142, China ' Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China; Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China; Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China

Abstract: Wireless sensor networks have been developed in many areas but face many challenges. For example, a suite of indicators should be considered when deploying sensors. Deciding how to minimise the cost of deploying sensors, increase coverage, maintain a certain degree of connectivity, and maintain a long network life cycle is of great significance when deploying nodes. This paper proposes a many-objective deployment strategy based on cost, coverage, connectivity, and load balancing to solve the sensor deployment problem. The objectives include cost, coverage, connectivity, and load balancing. It uses a multi-objective evolutionary algorithm based on the projection plane to study the deployment of wireless sensor networks. Experimental results show that this deployment strategy has excellent performance compared with other multi-objective algorithms. It can balance the number of nodes, provide node energy utilisation, prolong the network cycle in a certain environment, and help decision-makers to choose an optimal or near-optimal deployment strategy for the deployment problem.

Keywords: multi-objective optimisation; wireless sensor network; WSN; indoor deployment; load balancing.

DOI: 10.1504/IJSNET.2023.129641

International Journal of Sensor Networks, 2023 Vol.41 No.2, pp.126 - 135

Received: 13 Sep 2022
Accepted: 17 Sep 2022
Published online: 17 Mar 2023 *

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