Wireless sensor deployment optimisation based on cost, coverage, connectivity, and load balancing. (10th March 2023) - Wang, Jun; Luo, Dongxu; Peng, Funan; Chen, Weiru; Liu, Jun; Zhang, Hualiang
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.