Research Of Coverage On 3-D Wireless Sensor Networks

Wireless sensor network(WSN) is a kind of brand-new network model which is totally different from the existing networks. The good performances and characteristics of WSN have made it applied in the real life more and more widely and improved the quality of people’s lives constantly. The coverage and connectivity problems are the most basic research in the process of the wireless sensor network, which are also the most important contents. Network coverage problem means that realizing full coverage of the networks with a large number of sensor nodes which are deployed randomly or fixedly. According to the node’s perception model and the network quality of service requirements, changing the location distribution of the nodes which are deployed in networks to improve the quality of network service. Network connectivity refers to the normal communication between nodes and other nodes, nodes and the sink nodes in the network. Good network connectivity guarantees the fault tolerance of the wireless sensor networks.Firstly, a 3D perceptual model of sensor nodes is built to solve the coverage problem of 3D surface in wireless sensor network, which considers the irregularities of the 3D surface, the salient point on the surface can become obstacles in the process of perception of the node and lead to the problem of 3D monitoring blind area. Firstly calculating the required minimum number of nodes which can realize complete coverage of the limited surface through analyzing the simple 3D surface theoretically, then meshing on the surface and improving fitness function based on the 3D monitoring blind area, optimizing the position coordinates of the randomly deployed nodes by reference of differential evolution(DE) algorithm, and calculating the minimum number of nodes for realizing a complete coverage of target surface through a large number of simulation experiments, then introducing the error rate and test criterion to verify the effectiveness of DE algorithm in solving the simple 3D surface coverage problems. Finally the DE algorithm is adopted to solve the complex 3D surface coverage problems which achieve good results.Then, a deployment strategy of the target points is put forward to solve the target covering problems in 3D space, and adopting the DE algorithm to optimize the location coordinates of the sensor nodes to realize coverage of all the target points in 3D surface with minimal sensor nodes. Firstly, building the 3D perception model of sensor nodes, and proving the feasibility of solving the target coverage problems in 3D surface with DE algorithm theoretically, and reflecting the fault tolerance of the algorithm.Finally, a model based on Reuleaux tetrahedron is built to solve the problems of k-coverage and connectivity in 3D wireless sensor networks, which can achieve k-coverage of the wireless sensor networks. Then the minimum node density of the k-covered wireless sensor network is deduced based on the nature of the Reuleaux tetrahedron and Highline theorem. The proposed concept of average edge length achieves good results during the progress of calculating the minimum node density, meanwhile, calculates the connectivity of k-covered homogeneous wireless sensor networks and solves the problems of k-coverage and connectivity in 3D wireless sensor networks with minimum sensor nodes.