Research On Range-Free Location Algorithms In Wireless Sensor Networks

Wireless Sensor Networks(WSN)is a hotspot in the field of computer networks in recent years,which is a communication network information system that can realize the functions of information collection,information processing and information transmission.WSN can collect various data and target information at any time,thereby promoting information interaction between the human and the physical world,and has a very broad application prospect in the field of defense military,industrial manufacturing and civil use.Positioning technology plays an important role in many key technologies of WSN.Because no accurate location information is obtained in time,more data collected by sensor nodes is of no use value.That is to say,when an event is sensed by the sensor,it must first know the specific place where it occurred.The division of positioning technology into Range-Based positioning technology and RangeFree positioning technology is currently the mainstream division.Range-Based positioning method requires additional technical tools to obtain the distance between the unknown node and the beacon node,thereby directly calculating the location of the unknown node;Range-Free positioning method rely on existing information in the network to estimate and locate unknown nodes.The former is more accurate,but the resources are expensive and the cost is high;the latter is relatively low in positioning accuracy,but it is much better than the former in terms of cost and energy consumption.At present,the Range-Free location algorithm is a research hotspot for scholars at home and abroad,so this paper will further study it,the specific work is as follows:This paper will briefly describe the research background,research significance,research status and related concepts of WSN,and introduces several node positioning calculation methods and Range-Free positioning algorithms.The error analysis of convex localization algorithm and DV-Hop localization algorithm in Range-Free methods is deeply explained.According to different application scenarios of the algorithm,three improved positioning algorithms are proposed:(1)Angle optimization convex location algorithm using multiple communication radius combined with RSSI(Received Signal Strength Indication).The algorithm first broadcasts multiple times using multiple communication radii to narrow the area where the unknown node is located;Secondly,the RSSI is used to sense the signal strength of the node,and the area where the unknown nodes is located is further refined;Finally,the position of the node is corrected by the value of each vertex of the polygon to determine the final positioning result.Because the convex positioning algorithm needs to deploy many beacon nodes,this improved algorithm is generally applicable to scenarios with small monitoring area and rapid deployment.(2)A DV-Hop improved positioning algorithm using multiple communication radius and angle value weighting.The algorithm first uses the multi-communication radius to correct the minimum hop count between nodes,and calculates the routing distance between nodes;Secondly,the angle value between the beacon nodes is obtained by the ratio of the routing distance to the actual distance,and the abnormal beacon node is eliminated by the angle value;Then,the angle value between the unknown node and the beacon node is obtained by the ratio of the routing distance to the communication radius;Finally,the average value of the jump between the nodes is corrected by using the angle value weighting,and the unknown node is obtained by the maximum likelihood method.The DV-Hop localization algorithm can complete the positioning when the beacon node ratio is not high,but the use of multiple communication radius requires a certain amount of node energy.Therefore,this improved algorithm is generally applicable to such a scenario that refers to the empty area of the monitoring area,the low cost input,and the reusable nodes.(3)DV-Hop algorithm combined with RSSI and bat optimization algorithm.The algorithm first uses the RSSI distance conversion model to calculate the distance between adjacent nodes,corrects the minimum hop count between nodes,and then calculates the routing distance between nodes.Second,use the angle value as the weight to correct the average hop distance between the nodes;finally,the positioning problem of the node is transformed into the minimum solution problem of the nonlinear equations,and the improved bat algorithm is used to obtain the coordinates of the unknown node.This improved algorithm is generally suitable for use in scenario that the monitoring area is empty,the cost is low,and the maintenance is unmanned.Simulation experiments were carried out on several algorithms proposed in the article,and compared with other classical algorithms in the same environment.The results show that the positioning algorithm of this paper has improved the positioning accuracy compared with other algorithms.