Research On Node Localization Algorithm Based On DV-Hop In Wireless Sensor Network

As a technology capable of collecting,sensing,and monitoring information,wireless sensor network technology has received high attention in the scientific research community and has become the focus of many scientific research experts.As a new technology of multi-disciplinary integration,wireless sensor network has a wide range of applications.For most applications,it needs to be able to determine the specific location of the monitored information.If the location information of the monitored event is not known,the wireless sensor network will lose its application value.Therefore,in order to determine the specific location of the monitored object,the node positioning technology plays a key role in the wireless sensor network,and the accuracy of node positioning is extremely important for the application of wireless sensor networks.This paper focuses on the distance vector-hop(DV-Hop)node positioning algorithm,which is a positioning technology without ranging in wireless sensor networks.After systematically studying the positioning technology of wireless sensor networks,after mastering the positioning principle of the DV-Hop algorithm,the problems existing in the positioning process of the algorithm are analyzed in detail,and puts forward corresponding improvement scheme for the shortcomings of the original algorithm,the specific contents are as follows:(1)In order to reduce the positioning error of the DV-Hop algorithm,a corresponding solution is proposed for the problems existing in the two stages of hop number acquisition and distance calculation of the algorithm.In the hop number acquisition stage,the hop number correction coefficient is determined by the received signal strength value when the nodes communicate with each other,so that the hop number information corresponding to different distances between nodes is different,and the original algorithm considers the hop values between different nodes to be equal,thus effectively reducing the error caused by the hop number acquisition;In the distance calculation stage,according to the deviation caused by the distance between beacon nodes,the average hop distance of the revaluation is obtained by the principle of minimizing the mean square error,and then uses the signal strength value between nodes to construct a weighting factor to assign a corresponding weight to the revaluated average hop distance,which makes the distance calculation between nodes more accurate,and also considering the average hop distance information of all beacon nodes in the network,which solves the original algorithm only considers the problem of hop distance information of the beacon node received first when calculating the distance.Finally,the position of the nodes to be tested is obtained by the node position coordinate calculation method.(2)In order to further improve the positioning accuracy of the DV-Hop algorithm,an improvement scheme is proposed for the shortcomings of the coordinate calculation of the tested nodes in the third stage of the algorithm.Based on the improvement of hop number and hop distance,the artificial immune algorithm is introduced.Because the algorithm is easy to fall into the local optimum and the convergence speed is slow,it is improved by Gaussian mutation to expand the scope of searching the optimal solution and accelerate the convergence ability of the algorithm.By using the improved artificial immune algorithm instead of the traditional algorithm's position coordinate calculation method to further optimize the node coordinates,and the optimal solution is the final coordinates of the positioning node.Finally,the performance of the two improved schemes is analyzed,and the improved algorithm and the original algorithm are simulated and verified from the aspects of node communication radius,total number of nodes and number of beacon nodes.The final results show that the improved algorithm of hop number and hop distance is better than the original algorithm.On this basis,the improved artificial immune algorithm is used to optimize node coordinate positioning accuracy can be further improved.