Simulation of marine wireless sensor network coverage based on improved grey wolf optimization algorithm

Abstract A new improved algorithm (IGWO) is proposed based on the Grey Wolf Optimization (GWO) algorithm to solve the issue of low overall coverage easily caused by the random deployment of nodes in wireless sensor networks. The IGWO algorithm improves its searchability by adjusting the convergence factor a and changing the updating rules of individual gray wolf positions. IGWO improves the overall search capabilities of the algorithm by converging and adjusting the trend of convergence factors and dynamically adjusts the gray wolf position update strategy by taking the Euclidean distance ratio values of the omega wolf to the alpha wolf, beta wolf, and delta wolf as parameters, further expanding the search capability of the algorithm. Using MATLAB for simulation, we select 20, 30, and 40 sensor nodes respectively, and the coverage of IGWO compared to GWO’s WSN increases by 0.09%, 2.09%, and 1.17%, respectively, proving that the IGWO algorithm can effectively improve the coverage and performance of WSN.