Research And Improvement Of DV-Hop Localization Algorithm In Wireless Sensor Networks

Wireless Sensor Networks(WSN)is a new type of distributed network with functions of information collection,data processing and Wireless communication.Because of its advantages of low cost and high expansion,it is widely used in national defense,industrial manufacturing,daily life and other aspects.As the core component of node location technology,network node location information has always been the focus of WSN research.Node positioning technology in WSN can be divided into range-based and range-free positioning algorithms according to the measurement methods of the distance between nodes.The former has high positioning accuracy but also brings high cost,while the latter has been widely studied and applied due to its advantages of low cost and low energy consumption.DV-Hop location algorithm,as a classic range-free location algorithm,has the advantages of wide coverage and easy implementation.However,there are also shortcomings such as fuzzy positioning and low precision,so the algorithm has been studied and improved by many experts and scholars since it was proposed.In this paper,the causes of location errors in each step of the algorithm are analyzed,and two different improvement methods are proposed on the basis of the existing research.The main contents are as follows:1.An improved DV-Hop localization algorithm based on multi-communication radius and Angle correction is proposed.DV-Hop algorithm is easy to be affected by the distribution of nodes in the network,so the positioning error of some nodes is large.In this paper,a multicommunication radius is adopted to deal with the error of obtaining the minimum number of hops,and a better number of hops is obtained through repeated broadcast of beacon nodes.Secondly,the average hop distance is weighted by introducing the Angle value between the beacon nodes so that the average hop distance is not only dependent on the distance between the beacon nodes.Then,a vector correction is added to the positioning result after the positioning coordinate calculation to reduce the errors caused by the coordinate calculation.Finally,this paper carries out comparative experiments from three aspects: the proportion of beacon nodes,the communication radius of nodes and the total number of network nodes.Experimental results show that compared with the classical DV-Hop algorithm and similar localization algorithm,the positioning accuracy of the algorithm in this chapter is improved.2.A DV-Hop location algorithm based on Hop correction and genetic simulated annealing optimization is proposed.Firstly,in order to control the cost of nodes,the number of hops in the network is weighted and optimized by the distance between beacon nodes without adding additional functions of external devices and nodes.Second in view of the network in the area of the distribution of beacon nodes,starting from the network as a whole,the average hop distance as a function of error and the optimization of the minimum value problem,choose intelligent optimization algorithm to solve the optimal value of average jump from,at the same time using genetic algorithm based on simulated annealing algorithm and hybrid optimization algorithm to solve the limitations of single algorithm.Finally,the simulation results show that the positioning accuracy of the proposed algorithm is improved.Based on the error of DV-Hop algorithm in the minimum Hop number,average Hop distance and coordinate calculation,this paper proposes two different improved algorithms.According to the comparative experiment,the positioning accuracy of the improved algorithm in this paper has been improved.