Improved sand cat swarm optimization algorithm for enhancing coverage of wireless sensor networks

The premise of wireless sensor networks (WSNs) working efficiently is to achieve effective coverage of the monitoring area. The initial random deployment leads to the sensor nodes deviating from the optimal position, resulting in coverage loopholes. Therefore, in order to improve the coverage of sensor nodes and reduce the coverage holes, based on the excellent performance of artificial intelligence algorithm, a virtual force-directed improved sand cat swarm optimization algorithm (VF-ISCSO) is proposed. Firstly, a nonlinear convergence strategy of sand cats sensitivity is designed, and the mechanism of sand cat searching for prey is improved. Secondly, the virtual resultant force applied to the nodes is considered as the perturbation factor for sand cats position update, enhancing the algorithm convergence speed and optimization capability. When deploying 30 sensor nodes in monitoring area of 60 m×80 m, the network coverage rate (CR) of VF-ISCSO algorithm is about 99.61%, which is 29.3% higher than the initial coverage. When the size of a monitoring area and the number of sensors change, the VF-ISCSO algorithm still has the best coverage performance.