Optimization Algorithm For Wireless Sensor Network Coverage And Node Location

Intelligent optimization algorithm is applied in various fields of people's life,among which in the wireless sensor network,node positioning technology and network coverage technology are important research directions.In this paper,the social spider optimization algorithm is improved and applied to the network coverage and node location of wireless sensor networks.Aiming at the imbalance of local and overall search ability in the optimization algorithm of colony spiders,the position of the spider gradually moves to the current optimal position during the running process,which leads to the reduction of position diversity and low convergence accuracy,,and proposes a social spider optimization algorithm with a hybrid improved strategy.The improved strategy is as follows: In the initialization process of the algorithm,a combination of reverse learning strategy and chaotic mapping is introduced to make the spider individuals evenly distributed during the initial operation;spiders of different sexes move independently under the,adding an adaptive weight value,and at the same time,a dynamic nonlinear decreasing operation is performed for the probability factor that controls the attraction or repulsion operation in the female spider,so as to ensure the balance of the search ability between the local and the whole as much as possible;finally,the female and male spiders are completed After the mating operation,the optimal spider under the current iteration is selected for Gaussian mutation perturbation.Aiming at the coverage optimization problem of wireless sensor network,the probability perception model is selected,and the network coverage rate is used as the fitness function of the algorithm.The simulation results show that the average coverage rate of the GSSO algorithm is 96.36%,and the optimal coverage rate can reach 98.49%.,compared with the SSO algorithm,the average coverage rate is increased by 7.91%,and the optimal coverage rate is increased by 7.81%.It can be seen that the improved algorithm has very good practicability in wireless sensor network coverage optimization.In the wireless sensor network node location,DV-Hop algorithm is selected as object.In the node positioning process,the traditional DV-Hop algorithm generally estimates the coordinate position of the unknown node by the least square method,and a large error will occur in the estimation process.The GSSO algorithm proposed in this paper is applied to the node location,the average location error of the node is taken as the fitness function of the algorithm,and the accuracy of the node location is improved by optimizing the average location error.Experiments show that the DV-Hop algorithm based on the GSSO algorithm can more accurately locate the unknown nodes.