Research On Sensor Node Redeployment Based On Voronoi Polygon For Confident Information In WSN

Wireless sensor network(WSN)is composed of many small sensor nodes with sensing,computing,and wireless communication capabilities.It is mainly used to collect and process target object information in the network coverage area.With the rapid development of the current Internet of Things technology,WSN has been widely used in various fields such as military,environmental monitoring,medical monitoring,and agricultural data observation.In the coverage control for wireless sensor networks,sensor nodes are generally randomly deployed on a large scale in the target area.However,random deployment usually results in uneven distribution of nodes,resulting in coverage holes or redundant coverage,which significantly reduces the quality of network coverage.Aiming at the problem of random deployment leading to uneven distribution of sensor nodes,this paper focuses on the research of mobile sensor node redeployment theory and methods to improve network coverage performance.The main tasks include:(1)Aiming at the problem of area division of wireless sensor networks,this paper combines the advantages of Confident Information Coverage(short as CIC)and the Voronoi,studies the technical difficulties of integrating them,and designs a new Voronoi area division algorithm for CIC.Simulation experiment results show that compared with the Voronoi method under the traditional disc model,the algorithm has fewer Voronoi regions divided by the same number of nodes and has a higher initial coverage.(2)Aiming at the coverage control problem of wireless sensor networks,this paper designs two node redeployment algorithms based on the proposed CIC-Voronoi model,CIC-Minmax-vertex algorithm and CIC-Maxmin-vertex algorithm,to solve the field area coverage problem.The basic idea of these two algorithms is based on the polygonal geometric centroid sensor,which iteratively calculates and moves the sensor position to achieve a more favorable position.Simulation results demonstrate the advantages of the algorithm,which can achieve greater coverage with fewer nodes.Moreover,simulations were performed in multiple dimensions such as time and energy consumption,and the results fully proved the effectiveness of the proposed algorithm.