Coverage Optimization Strategy for 3-D Wireless Sensor Networks Based on Improved Sparrow Search Algorithm

Compared with 2-D wireless sensor networks (WSNs), 3-D WSNs need more node deployment costs under the same coverage performance. Therefore, how to use fewer nodes to maximize coverage quality and ensure connectivity at the same time is the key issue to improve coverage performance. To solve these problems, a coverage optimization strategy for 3-D WSNs based on improved sparrow search algorithm (ISSA) is proposed in this article. First, aiming at the shortcomings of sparrow search algorithm (SSA), such as easy to fall into local optimum and slow convergence speed, the safety threshold attenuation function and stagnation update mechanism are designed. At the same time, aiming at minimizing the network energy consumption and ensuring the applicability of the ISSA algorithm in 3-D WSNs, the optimal threshold of 3-D virtual force is deduced. According to the density of network nodes, the appropriate virtual threshold is selected to optimize the moving distance of nodes. At the same time, the optimization assignment strategy is adopted for the optimal particles of ISSA to reduce the total moving energy consumption. The simulation results show that compared with the SSA, the 3-D virtual force algorithm (3DVFA), and virtual force-directed particle swarm optimization (VFPSO) algorithms, ISSA algorithm improves the coverage rate by 29.26%, 8.5%, and 4.6%, respectively. In addition, ISSA algorithm has obvious advantages in connectivity and moving distance.