Research On Technologies Of Localization And Coverage For Wireless Sensor Networks

The wireless sensor network was generated with the development of semiconductor,microsystem and communication technologies and has been developing rapidly.The wireless sensor network uses various integrated micro-sensor nodes for the collaborative sensing,collection and processing of data of sensed objects in the geographic area covered by the network,processes the data with an embedded system,and then transfers the data to the base station through a random self-organizing wireless communication network from which the data finally reach management nodes through internet or satellite network.Currently,the wireless sensor network has been widely applied to various fields,such as national defense and military,national security,environment monitoring and medial treatment&public health.In the wireless sensor network application research,node location and network coverage are two focuses.The location information of node plays a role of great importance in various applications of wireless sensor network;network coverage decides the scope of services offered by the wireless sensor network,and largely affects the cost of network and the performance of specific application.The paper makes an in-depth study and exploration on the node location and network coverage technology of wireless sensor network.With regard to node location,the paper first analyzes and improves traditional DV-Hop location algorithm,and then proposes two new location algorithms combined with the mainstream learning algorithm using the research approach of kernel method.With regard to network coverage,the research mainly focuses on the virtual-potential-field-based coverage algorithm in static coverage and proposes an adaptive and extensible deployment algorithm.Specific research procedures are as follows:1.Define the error causes of DV-Hop algorithm,and,on this basis,propose an incremental algorithm from rough location to accurate location,and then introduce the concept of collinearity degree at the stage of trilateration calculation stage and choose the units of good location quality for the calculation so that the location algorithm can get a high location accuracy.2.Generate some virtual beacon nodes with the help of mobile beacon nodes by making them move in given paths,to reduce the number of real beacon nodes effectively;meanwhile,consider the signal vectors obtained from the communication of the virtual beacon nodes and the unknown nodes in monitored area as the training labeled data samples of TSVM.According to the characteristics of training samples,propose a multiclass-vs.-multiclass classification method,on which basis to infer the position of unknown node.Experiment and simulation results show that the method has the high location accuracy.3.Propose a wireless sensor network location algorithm based on hop count and kernel method.The algorithm's basic idea is to measure the similarity of nodes using the Gaussian kernel function.Collect and use the information of real distance and hop count between nodes and use the data of hop count and distance between beacon nodes as training data,and then study with PLS and build the optimal model to predict the distance from the unknown node to the known node.Experiment results show that the location algorithm has features of the high location accuracy,little influence from the number of beacon nodes,the strong environmental adaption and the suitability for different deployment environments.4.Propose a virtual-potential-field-based distributed,adaptive and extensible mobile sensor network deployment algorithm.The algorithm considers the obstacles and nodes in deployment area as charged particles.The particles move under the Coulombic force of other obstacles and particles,and finally all nodes spread to the entire network automatically due to the interaction of force,in which case the deployment is completed.According to simulation results,the algorithm's performance indexes show good performance in various scenes.