Research And Optimization Of WSN Positioning Algorithm Based On DV-Hop

In recent years,with the rising popularity of Internet of Things,the key technology of Internet of Things-Wireless Sensor Network(WSN)has drawn much attention.WSN is closely linked with our lives and is widely used in smart home,agricultural production and medical system testing.One of the most important technologies in WSN is positioning technology.For a long time,various positioning algorithms emerge in an endless stream.Based on the comprehensive consideration of algorithm complexity,algorithm convergence and cost,DV-Hop positioning algorithm is widely used in practical applications Therefore,it has great research value.This article focuses on non-ranging-based DV-Hop positioning algorithm,the main work of this paper are:(1)The basic principle of DV-Hop localization algorithm is researched,and the reason of each phase error is analyzed.Based on a large number of literature about DV-Hop localization algorithm,the simulation experiment is carried out.From qualitative and quantitative perspectives Describe the DV-Hop algorithm error.(2)The influence of the number of hops and the transmission distance of nodes on the DV-Hop localization algorithm is studied in the algorithm.In the simulation,random high-density node scene,fixed-grid high-density node scene,dynamic grid low-density node scene;In a random scene to change the number of unknown nodes to calculate the positioning error DV-Hop positioning algorithm.Simulation results show that in high-density nodes,the transmission distance is shorter and the number of hops is more,and the positioning accuracy of DV-Hop positioning algorithm is higher.However,in low-density nodes,the transmission distance is longer and the number of hops is less,so the positioning accuracy of DV-Hop positioning algorithm is higher.(3)In the above three deployment scenarios,the noise conditions are increased and the positioning errors of the DV-Hop positioning algorithm and the DV-Distance positioning algorithm under high noise and low noise are respectively calculated and compared.The simulation results show that the DV-Hop positioning algorithm has much higher positioning accuracy than DV-Distance positioning algorithm under high noise conditions.Under low noise conditions,the overall positioning accuracy of the DV-Distance positioning algorithm and the DV-Hop positioning algorithm are not significantly different,and it can be known that the DV-Hop positioning algorithm is less affected by noise.(4)Proposed a genetic algorithm and binary ant colony algorithm to optimize DV-Hop localization algorithm,using the replica operator,crossover operator and mutation operator in the initial population to search,and then on this basis,Using binary ant colony algorithm to further search,and then use the principle of survival of the fittest generation of new individuals and parent population individuals,retain the best individual as a new generation of population,iterative loop to get the optimal solution.The simulation results show that the positioning accuracy of GABACDV-Hop positioning algorithm is greatly improved compared with the traditional DV-Hop positioning algorithm,which has advantages and disadvantages compared with the GADV-Hop positioning algorithm proposed in the literature.However,the overall GABACDV-Hop positioning algorithm is superior.