Research on glowworm swarm optimization localization algorithm based on wireless sensor network

Ting Zeng, Yu Hua, Xian Zhao, Tao Liu
{"title":"Research on glowworm swarm optimization localization algorithm based on wireless sensor network","authors":"Ting Zeng, Yu Hua, Xian Zhao, Tao Liu","doi":"10.1109/FCS.2016.7546730","DOIUrl":null,"url":null,"abstract":"For sensor network, the localization of node is one of the current hotspots. In order to improve the localization precision of the unknown nodes, a glowworm swarm optimization localization (GSOL) algorithm is proposed to be applied in wireless sensor network (WSN). Through multiple iterations to solve the optimization issue, the location of unknown nodes can be acquired, and fitness function can be founded. The proposed algorithm can be used for node localization in multidimensional space. The effectiveness of the algorithm has been theoretic analyzed and verified by simulation. The accuracy and stability of node localization have been largely improved, and the performance of the algorithm is much better in case of a bit larger ranging error exist.","PeriodicalId":122928,"journal":{"name":"2016 IEEE International Frequency Control Symposium (IFCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Frequency Control Symposium (IFCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/FCS.2016.7546730","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

For sensor network, the localization of node is one of the current hotspots. In order to improve the localization precision of the unknown nodes, a glowworm swarm optimization localization (GSOL) algorithm is proposed to be applied in wireless sensor network (WSN). Through multiple iterations to solve the optimization issue, the location of unknown nodes can be acquired, and fitness function can be founded. The proposed algorithm can be used for node localization in multidimensional space. The effectiveness of the algorithm has been theoretic analyzed and verified by simulation. The accuracy and stability of node localization have been largely improved, and the performance of the algorithm is much better in case of a bit larger ranging error exist.
基于无线传感器网络的萤火虫群优化定位算法研究
对于传感器网络来说,节点定位是当前研究的热点之一。为了提高未知节点的定位精度,提出了一种应用于无线传感器网络的萤火虫群优化定位算法(GSOL)。通过多次迭代求解优化问题,获取未知节点的位置,建立适应度函数。该算法可用于多维空间的节点定位。通过理论分析和仿真验证了该算法的有效性。节点定位的精度和稳定性得到了很大的提高,在存在较大测距误差的情况下,算法的性能要好得多。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信