The Research Of Coverage Optimization Algorithm In Hybrid Wireless Sensor Network

In recent years,with the rapid development of electronic technology and wireless communication,the research on related issues of wireless sensor networks has become a frontier issue.In wireless network research,network coverage and effective deployment of nodes have become the core issues.They mainly address the network's perception and monitoring capabilities,which will directly reflect the service quality of wireless sensor networks.In some complex terrain environments that people cannot reach,if the sensor nodes randomly deploy,there will be some coverage blindness.Many scholars use hybrid wireless sensor networks to solve network coverage problems.In this paper,aiming at the shortcomings of the traditional artificial bee colony algorithm which is easy to fall into local optimum and too many iterations,an improved artificial bee colony algorithm is designed to deploy wireless network nodes so as to maximize the coverage rate.The work done in this article includes the following aspects.This paper studies the hybrid wireless sensor network.Firstly,it makes a detailed review and introduction of the traditional wireless network coverage problem.Then it lists several typical classifications of coverage problems and analyzes their respective characteristics.An improved bee colony algorithm(IVABC)is proposed.Two sets of test functions are used to simulate the improved algorithm.This illustrates the effectiveness of the algorithm.Apply the improved algorithm to solve the coverage problem of hybrid wireless sensor networks,aiming at the characteristics of coverage blindness caused by the random deployment of fixed nodes in hybrid wireless networks and combining the traditional artificial bee colony algorithm with slow search speed and easily falling into the local optimal solution.For the problem of defects,the algorithm first uses Voronoi polygons to determine the blind spot coverage position when the fixed node is deployed as the initial position of the mobile node,and then uses the bee colony algorithm based on the reverse learning strategy to optimize the deployment of the mobile node to obtain the optimal mobile node.Location,and finally reached the optimal network coverage and reduce the number of iterations.Comparison with other algorithms shows that this algorithm has the advantages of fast convergence and high network coverage.