Research On Coverage Control Of Directional Sensor Networks Based On Virtual Potential Field

With the development of image/video sensors and hyperspectral cameras,environmental data information becomes diverse and complex.Therefore,Directional Sensor Networks(DSNs)which can collect and transmit data information more comprehensively and accurately have emerged.For places where the environment is harsh and people can’t reach,DSNs usually uses large-scale random scattering to deploy directional nodes to form,which often produces a large number of holes and overlapping coverage areas,and it is impossible to analyze the data of the monitoring area accurately and comprehensively.In addition,due to the limited energy of nodes and the difficulty of battery replacement,when a large number of nodes run out of energy,the network will be disconnected or even paralyzed.Therefore,in order to effectively control energy consumption,the nodes are fixed once deployed.At present,the existing coverage control algorithms mainly carry out coverage enhancement operations without considering the sleep problem of redundant nodes.Therefore,this paper focuses on the low coverage caused by the random deployment of DSNs in two-dimensional and three-dimensional monitoring areas and the high energy consumption caused by a large number of redundant nodes working at the same time,and proposes two coverage control algorithms based on virtual potential field to adjust the sensing direction of nodes in order to achieve efficient coverage of the network.The main work of this study are as follows:(1)Aiming at the shortcomings of Gravitational Search Algorithm in coverage problems,such as easy to fall into local optimum and slow convergence,this paper puts forward improved attenuation function and virtual force strategy of grid points to enhance network coverage.(2)Aiming at the problem of reducing network energy consumption,a DSNs node dormancy strategy based on safe set is constructed,and a Coverage Control Algorithm of DSNs Based on Improved Gravitational Search(IGSCCA)is proposed by combining the coverage enhancement strategy,which enhances the coverage effect and reduces the network redundancy rate and energy consumption.(3)Facing the three-dimensional monitoring area,the monitoring area model is constructed in combination with the actual scene,and targets such as obstacles and hot spots are introduced,and an Efficient Coverage Control Algorithm for 3D DSNs in Complex Scenes(ECCACS)is proposed.Based on the sensing characteristics of nodes,the marching ant optimizer is used to optimize the pitch angle to maximize the sensing area.Aiming at the deflection angle,the deflection angle is optimized by constructing corresponding virtual forces such as obstacles and hot spots,spots so as to maximize the coverage without blind areas,thus improving the weighted effective coverage of the network.In the two-dimensional monitoring area of 500 m×500 m,compared with the coverage enhancement algorithms based on virtual potential field,Voronoi and virtual force-oriented particle swarm optimization,the coverage rate of IGSCCA is increased by28.35%,21.20% and 13.90% respectively.In the same size of three-dimensional monitoring area,the ECCACS algorithm can greatly improve the effective coverage rate and sensing area of the network.Compared with the coverage enhancement algorithms based on virtual force,differential evolution and the combination of virtual force based on differential evolution,the weighted effective coverage of ECCACS is increased by 8.51%,10.26% and 4.69% respectively,and it also has significant advantages in the improvement rate of sensing area,energy utilization rate and the minimum number of nodes.