A Voronoi Diagram-Based Grouping Test Localization Scheme In Wireless Sensor Networks

With the rapid development and wide application of wireless sensor networks,location technology,as one of the basic and key technologies,has a direct impact on the efficiency of location-aware routing and the effectiveness of related applications.It is of great significance to promote the development of wireless sensor networks.However,due to the complexity of the application environment and the diversity of node distribution,node localization is still a major challenge for most wireless sensor network applicationsRange-based localization algorithms have high accuracy,but they have been equipped with special equipment,high cost and poor scalability Range-free localization algorithms estimate the location of nodes by network connectivity or other useful information,and the accuracy can meet the requirements of specific applications.They have been paid more attention because of its simple and efficient implementation and rich application scenarios.Range-free localization algorithms are studied in this thesis.Major tasks of the thesis are as followsFirstly,wireless sensor networks are summarized.The classical range-based and range-free algorithms are described in detail.The key problems in localization algorithm are found,and the design target of localization algorithms is determined in this thesisThen,aiming at the problem that the current range-free algorithms usually assume that the algorithms are carried out in a regular ideal environment,but it is not feasible in reality.Considering the propagation loss and complex environment,we propose a range-free localization algorithm suitable for outdoor open area and irregular signal propagation using the most appropriate logarithmic attenuation model.Moreover,the properties of Voronoi Diagram are used to reduce error accumulation.Secondly,a new geometric region constraint method is proposed to determine the estimation region of unknown nodes.not completely dependent on the connectivity of network nodes.The grid scan algorithm is used to optimize the algorithm to solve the centroid of the estimated area,and the weight coefficient is introduced to obtain the centroid of the area with the largest weight as the node estimation location,which reduces the calculation complexity of the algorithmFinally,on the platform of MATLAB,the algorithm is simulated and compared with the other two classical algorithms,aiming at the factors that may affect the performance of the algorithm,the effectiveness of the algorithm is verified in the case of square random distribution and C-type non-uniform distribution of network nodesIn summary,the proposed algorithm takes into account the irregular application environment.Experiments show that the algorithm significantly improves the positioning accuracy and the coverage in the case of uniform and uneven distribution of nodes.