Research On Coverage Algorithm Of Video Sensor Network

With the development and application of video sensors,traditional network coverage control algorithms based on omnidirectional sensing models are no longer applicable,and it is urgent to redesign for the characteristics of video sensor networks.In this regard,based on the directed sensing model,this paper makes an in-depth discussion on the regional coverage enhancement of video sensor networks.Firstly,according to the area coverage problem of video sensor network under ideal conditions,a geometric method based on Delaunay triangulation is proposed.The Delaunay trigonometric center with the largest area around the target node is selected as the working direction of the node.On this basis,it is organically combined with a distributed greedy algorithm.The concept of “contribution rate” is introduced to set the node priority,and the proportion of overlapping area and coverage area is gradually reduced through greedy iteration,so as to achieve the purpose of optimizing network coverage.Secondly,considering the existence of multiple obstacles in the target area,a multi-obstacle-based sensor node perspective obstruction scheme is discussed and designed.Based on the analysis of multi-obstacle-based video sensor network coverage model,a dynamic optimization algorithm for sensor network coverage based on genetic algorithm is proposed.Experimental results show that the algorithm has strong practicality for improving network coverage.Finally,the spatial optimization problem for 3D perception model is discussed.Based on the original particle swarm algorithm and the characteristics of the video sensor network,this paper proposes a spatial network coverage control strategy based on three-dimensional sensing model.The particle swarm algorithm is used to optimize the perceptual perspective of the video sensor,gradually reducing the redundant coverage area between the sensor nodes in the space,thereby achieving the goal of enhancing network coverage.Experimental results show that the algorithm has obvious effect on improving spatial coverage.