UAV’s enhanced data collection for heterogeneous wireless sensor networks

Kamel Barka, Lyamine Guezouli, Assem Rezki
{"title":"UAV’s enhanced data collection for heterogeneous wireless sensor networks","authors":"Kamel Barka, Lyamine Guezouli, Assem Rezki","doi":"10.53375/icmame.2023.253","DOIUrl":null,"url":null,"abstract":"In this article, we propose a protocol called DataGA-DRF (a protocol for Data collection using a Genetic Algorithm through Dynamic Reference Points) that collects data from Heterogeneous wireless sensor networks. This protocol is based on DGA (Destination selection according to Genetic Algorithm) to control the movement of the UAV (Unmanned aerial vehicle) between dynamic reference points that virtually represent the sensor node deployment. The dynamics of these points ensure an even distribution of energy consumption among the sensors and also improve network performance. To determine the best points, DataGA-DRF uses a classification algorithm such as K-Means.","PeriodicalId":385901,"journal":{"name":"ICMAME 2023 Conference Proceedings","volume":"94 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ICMAME 2023 Conference Proceedings","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53375/icmame.2023.253","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

In this article, we propose a protocol called DataGA-DRF (a protocol for Data collection using a Genetic Algorithm through Dynamic Reference Points) that collects data from Heterogeneous wireless sensor networks. This protocol is based on DGA (Destination selection according to Genetic Algorithm) to control the movement of the UAV (Unmanned aerial vehicle) between dynamic reference points that virtually represent the sensor node deployment. The dynamics of these points ensure an even distribution of energy consumption among the sensors and also improve network performance. To determine the best points, DataGA-DRF uses a classification algorithm such as K-Means.
无人机在异构无线传感器网络中的增强数据收集
在本文中,我们提出了一种名为DataGA-DRF(一种通过动态参考点使用遗传算法进行数据收集的协议)的协议,该协议从异构无线传感器网络收集数据。该协议基于DGA (Destination selection根据遗传算法)来控制无人机(UAV)在动态参考点之间的运动,这些参考点实际上代表了传感器节点的部署。这些点的动态确保了能量消耗在传感器之间的均匀分布,也提高了网络性能。为了确定最佳点,DataGA-DRF使用K-Means等分类算法。
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:481959085
Book学术官方微信