Variable Speed Elastic Collision Lion Swarm Algorithm And Its Application In Improved 3D DV-Hop Positioning Algorithm

Wireless sensor networks are self-organizing networks based on sensors,which can send real-time information about perceived objects within the network coverage area to users.They play a crucial role in social development,and node localization technology is a key technology in wireless sensor networks.The DV Hop algorithm in node localization algorithms has attracted widespread attention due to its low cost and easy implementation advantages.However,there are certain errors in the accuracy of localization,which cannot meet certain application scenarios.By analyzing the causes of errors in the DV-Hop algorithm,an improvement plan is proposed.The main work is as follows:(1)This article proposes a variable speed elastic collision lion swarm optimization(VELSO)DV-Hop localization algorithm to reduce the accumulated error caused by the maximum likelihood estimation method in the DV-Hop localization algorithm.This algorithm introduces the Lion Swarm Optimization(LSO)algorithm,which has strong optimization ability and is easy to implement,into the DV-HOP localization algorithm.By analyzing the shortcomings of LSO algorithm,a variable spiral search strategy is introduced to increase the flexibility of lion search.At the same time,the mother lion learns the learning strategy of teaching and learning algorithms to enhance the interactive behavior of lion hunting.Secondly,an improved refraction Reverse learning strategy is used to increase the diversity of the population and the selection of candidate solutions.Finally,a variable speed elastic collision strategy is adopted to improve the algorithm’s ability to jump out of local optima.In order to verify the effectiveness of the algorithm,16 test functions were used to test the proposed algorithm and compared with other algorithms to verify the effectiveness of the VELSO algorithm.And the VELSO algorithm was applied to two-dimensional DV-Hop positioning,and the experimental results showed that the application of this algorithm can effectively improve the positioning accuracy.(2)In order to reduce the positioning error of the 3D DV-Hop positioning algorithm,this article proposes a 3D DV-Hop positioning algorithm based on the VELSO algorithm,combining previous communication radius partitioning methods and similar path search algorithms.Firstly,the communication radius of anchor nodes is subdivided based on the reciprocal of unknown nodes,so that when the number of unknown nodes is large,multiple levels are used,and when the number of unknown nodes is small,fewer levels are used.This allows the algorithm to improve hop accuracy while ensuring adaptation efficiency.Secondly,the minimum mean square error criterion is introduced in the calculation stage of the average jump distance of anchor nodes to reduce the error of the average jump distance of anchor nodes;In the stage of obtaining the average hop distance of unknown nodes,due to the fact that the average hop distance of unknown nodes comes from the anchor node closest to its hop count,which leads to errors caused by different unknown nodes having the same average hop distance,a weighted average hop distance calculation method based on neighboring anchor nodes is designed to make the average hop distance of unknown nodes more accurate.Finally,use the VELSO algorithm to locate unknown nodes.Simulation experiments were conducted on the proposed algorithm,and the experimental results showed that the proposed algorithm can effectively improve the positioning accuracy of 3D DV-Hop.In this article,the effectiveness of the VELSO algorithm was first verified,and then the average positioning error of the two positioning algorithms was verified.From the experimental results,it can be seen that both algorithms can improve the positioning effect.At the same time,the average of multiple experimental results shows that both algorithms also have good stability.