基于三维网格划分和Meanshift迭代的wsn节点定位算法

2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS) Pub Date : 2019-09-01 DOI:10.1109/ICVRIS.2019.00116

Pingzhang Gou, Mengyuan Sun, Xuezhi Liu, Gang Mao, F. Li

{"title":"基于三维网格划分和Meanshift迭代的wsn节点定位算法","authors":"Pingzhang Gou, Mengyuan Sun, Xuezhi Liu, Gang Mao, F. Li","doi":"10.1109/ICVRIS.2019.00116","DOIUrl":null,"url":null,"abstract":"A MeanShift-based node localization algorithm in three-dimensional grid environment is proposed to solve the problem of wireless sensor network node positioning accuracy. The algorithm embeds the data objects into the three-dimensional space divided into grid cells, which uses a density threshold to identify the dense units and finds the density-based clusters in the grid cells. MeanShift algorithm is used to calculate the optimal solution of probability density and achieve the accurate location of nodes. The simulation results show that the proposed algorithm improves the average relative positioning accuracy of nodes compared with 3D-DV-Hop algorithm and 3D-WD-DV-Hop algorithm, with the increase of the total number of nodes and communication radius.","PeriodicalId":294342,"journal":{"name":"2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Node Localization Algorithm Based on 3D Grid Partition and Meanshift Iteration for WSNs\",\"authors\":\"Pingzhang Gou, Mengyuan Sun, Xuezhi Liu, Gang Mao, F. Li\",\"doi\":\"10.1109/ICVRIS.2019.00116\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A MeanShift-based node localization algorithm in three-dimensional grid environment is proposed to solve the problem of wireless sensor network node positioning accuracy. The algorithm embeds the data objects into the three-dimensional space divided into grid cells, which uses a density threshold to identify the dense units and finds the density-based clusters in the grid cells. MeanShift algorithm is used to calculate the optimal solution of probability density and achieve the accurate location of nodes. The simulation results show that the proposed algorithm improves the average relative positioning accuracy of nodes compared with 3D-DV-Hop algorithm and 3D-WD-DV-Hop algorithm, with the increase of the total number of nodes and communication radius.\",\"PeriodicalId\":294342,\"journal\":{\"name\":\"2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICVRIS.2019.00116\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICVRIS.2019.00116","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

针对无线传感器网络节点定位精度问题，提出了一种基于meanshift的三维网格环境下节点定位算法。该算法将数据对象嵌入到划分为网格单元的三维空间中，使用密度阈值识别密集单元，并在网格单元中找到基于密度的聚类。使用MeanShift算法计算概率密度的最优解，实现节点的精确定位。仿真结果表明，随着节点总数和通信半径的增加，与3D-DV-Hop算法和3D-WD-DV-Hop算法相比，该算法提高了节点的平均相对定位精度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Node Localization Algorithm Based on 3D Grid Partition and Meanshift Iteration for WSNs

A MeanShift-based node localization algorithm in three-dimensional grid environment is proposed to solve the problem of wireless sensor network node positioning accuracy. The algorithm embeds the data objects into the three-dimensional space divided into grid cells, which uses a density threshold to identify the dense units and finds the density-based clusters in the grid cells. MeanShift algorithm is used to calculate the optimal solution of probability density and achieve the accurate location of nodes. The simulation results show that the proposed algorithm improves the average relative positioning accuracy of nodes compared with 3D-DV-Hop algorithm and 3D-WD-DV-Hop algorithm, with the increase of the total number of nodes and communication radius.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

2019 International Conference on Virtual Reality and Intelligent Systems (ICVRIS)

自引率

0.00%

发文量