Research On Coverage Optimization Of Multi-dimensional Wireless Sensor Networks Based On Delaunay Triangulation Strategy

The primary problem in constructing a complete WSN is how to deploy sensor nodes.As the sensor node deployment process is affected by the complex environment and the spraying method,it will lead to the generation of coverage loopholes in the monitoring area.In response to this problem,this thesis takes the hybrid WSN composed of dynamic and static sensor nodes as the research object,and conducts research on the coverage optimization problem of two-dimensional plane and three-dimensional space.This thesis proposes a WSN coverage optimization scheme based on Delaunay triangulation strategy.The main work in this thesis is as follows:(1)Aiming at the problem that geometric methods are difficult to apply to probabilistic perception models in the study of two-dimensional coverage optimization,a coverage optimization scheme based on Delaunay triangulation combined with improved PSO optimization(DPSO)is proposed.First,according to the probabilistic perception model of the node,a concept of absolutely uncovered area in the monitoring area is proposed.Then the static nodes in the WSN are triangulated,and the Delaunay triangle centroid is obtained.By demonstrating the positional relationship between the triangle centroid and the coverage vulnerability,the improved PSO algorithm in this thesis is guided to complete the secondary deployment of mobile nodes to complete the repair of the coverage vulnerability caused by the initial deployment in the WSN.After simulation and comparison,it is proved that the scheme can effectively improve the coverage of two-dimensional WSN.(2)Aiming at the defects of PSO algorithm in the process of WSN coverage optimization,the algorithm is improved.This thesis uses the artificial bee colony algorithm to detect the characteristics of the random walk of bees and the greedy selection strategy.This thesis first selects the optimal set of particles to generate virtual particles and conducts tentative search in random directions according to the position formula of the detective bees in the artificial bee colony,and then reserves the particles with the best fitness value to replace the original particles according to the idea of greedy selection strategy.This thesis compares the improved PSO algorithm with the basic PSO algorithm through five classic test functions and proves that the improved PSO algorithm has higher individual particle optimization capabilities and better algorithm performance.(3)Aiming at the problem that the DPSO algorithm cannot be applied to three-dimensional scenes,this thesis builds a three-dimensional WSN model,adapts the previously proposed schemes to the three-dimensional coverage optimization problem,and further proposes a DPSO-3D algorithm suitable for three-dimensional space.The strategy of Delaunay triangulation of static nodes algorithm and obtaining the triangle centroid as the initial solution set in the DPSO algorithm is upgraded to three dimensions,and the centroid of the tetrahedron formed after the Delaunay triangulation is used as the initial solution set of the optimization algorithm to optimize the three-dimensional coverage problem.The simulation experiment proved that the DPSO-3D algorithm also has a good performance in improving the coverage of WSN in three-dimensional space under multiple experimental conditions with different sensing radius and different dynamic node numbers.Through the above research work,it is proved that the scheme proposed in this thesis can make good use of dynamic nodes to deploy the WSN twice to improve the coverage effect.The schemes in this thesis has good applicability in both two-dimensional and three-dimensional scenes.