Research On 3D Wireless Sensor Network Node Deployment Algorithm

Deployment is one of the most important research directions of wireless sensor networks.A reasonable node deployment strategy can optimize the topology of the network,improve the overall energy efficiency of the network,and improve the quality of service of the network.Therefore,the research on sensor network node deployment technology has extremely important theoretical significance and practical value.The traditional wireless sensor network node deployment research mainly stays in the two-dimensional plane model.With the deepening of research and the complexity of monitoring tasks,the deployment of three-dimensional(3D)space model wireless sensor networks has become the focus of research.This article mainly focuses on the two aspects of 3D surface sensor node deployment and underwater sensor node deployment in 3D space,combined with the actual application environment requirements,proposed node deployment optimization algorithm.Therefore,the main work and innovations of this article are as follows:(1)To solve the problem of node deployment in 3D surface wireless sensor network nodes,a deterministic deployment algorithm for 3D surface full coverage sensor network is proposed(Full Coverage Deterministic Deployment Algorithm in 3D Surfaces,FCDDA).Using the Delaunay triangulation algorithm to discretize the continuous surface,select the vertices in the triangulation as the sensor node deployment candidate position,and then iteratively select the node with the largest weight as the sensor node deployment position from the sensor node deployment candidate position based on the greedy strategy.Use the minimum number of nodes to complete the full coverage of the entire surface,where the node weight is defined as the increment of the sensor network to cover the partition set.The simulation results show that the proposed FCDDA algorithm has achieved good results in solving the problem of 3D surface deployment,and compared with similar algorithms,the algorithm is more feasible and suitable for any complex surface.(2)For the 3D surface with unknown geographic information,such as primary forest fire monitoring,seabed exploration and earthquake disaster area monitoring,the topology of the network cannot be preset,which leads to the implementation of the deterministic network deployment scheme.A 3D surface multi-mobile node sensor network deployment algorithm is proposed(Multiple Mobile-node Deployment Algorithm in 3D Surface,MMDA).Randomly distributed static nodes and mobile nodes cooperate with each other to complete the coverage of the monitoring area.First,the static nodes are used to construct a Delaunay triangulation network to determine the size and location of the coverage holes,and then the coverage hole repair strategy is designed based on the mobile nodes.The algorithm also considers the mobile energy consumption of nodes in practical applications,and sets a maximum mobile distance threshold for a single mobile node.Simulation results show that the proposed MMDA algorithm improves overall network coverage and reduces network energy consumption compared with similar algorithms.(3)Aiming at the problem of underwater wireless sensor network node deployment,an algorithm for underwater sensor network node deployment based on depth adjustment and layering is proposed(Depth-adjustment and Layering Deployment Algorithm,DLDA).First,the nodes are randomly scattered on the surface of the monitoring water area.All the nodes construct a Tyson polygon graph(Voronoi diagram),and use the Voronoi diagram to calculate the node redundancy,and adjust the redundant nodes to the next layer in the vertical direction,according to each The number of nodes in the layer and the average Euclidean distance between the nodes in the layer determine the depth of node adjustment,and repeat the algorithm to achieve network coverage of each layer in the entire network.Simulation experiments show that the proposed DLDA algorithm has advantages over the previous underwater sensor node deployment algorithms in terms of network coverage,connectivity,and network life cycle.