A Collaborative Localization Scheme For Wireless Sensor Networks

As the development and research of wireless sensor networks (WSN) technology, people propose to establish large-scale "The Internet of Things" with WSN technology as the core. The expansion of WSN applications, Standard communication protocol, clock information synchronization, collaborative information processing and network topology control is an important part of "The Internet of Things". Research in the network, the node (to be monitored objects) location information is based on used network studies need to focus on key issues. Designing of positioning technology to consider positioning accuracy, the energy consumed, application of the physical environment, position calculation speed, and information transmission delay and so on.This paper briefly describes the WSN technology, on the recent status briefly a typical localization algorithm on WSN, the mass center algorithm based on improved multi-level to form a multiple energy level centroid algorithm, the experiment of algorithm positioning error factor, understanding the advantages and disadvantages of range-free for later use in the positioning method based on range-based.Collaborative localization scheme is a range-based, according to random graph theory to know the definition of rigid body, rigid body in ideal conditions, two points of the Euclidean distance remain the same node location nature of compliance requirements. In accordance with this theory, the definition of localizable collaborative set, and build self-organization collaboration simple set positioning, and localizable collaborative set are given by the geometric expansion of proven methods to locate the expanding scope of the final completion of the entire network node localization. Genetic optimization method used WSN node position calculation process, the optimization algorithm combined with the positioning mode design collaborative model based on genetic optimization of the orientation program. The method to rigid graph theory-based network topology according to the formation of self-adaptive location unknown node can be estimated to achieve coordination body positioning. Then it used to achieve unknown node location estimation algorithm. In order to reduce the amount of computation, the value of life is written in the genetic optimization, the formation of local collaborative body positioning to reduce the number of loop calculations.Collaborative model based on genetic optimization method can take full advantage of the positioning device connected network sensor characteristics and locations of beacons, beacons to achieve lower rates under conditions of high positioning accuracy and high localization rate. Simulation results show that the algorithm optimization of multi-hop localization rate than the rate of single-hop positioning double standard, when the range error Re= 0.05R, the mean absolute positioning error is 0.073R, when the ranging error when Re= 0.1R the average absolute positioning error of 0.14R, showing good positioning performance.In the location method, the paper analyzes the WSN technology based container monitoring system as an example about the localizable technology applications in the field of container monitoring methods, and integration " The Internet of Things "of ideas for simple explanation for the further study to prepare.