Emergency Automobile Data Transmission with Ant Colony Optimization (ACO)

Pub Date : 2023-01-01 DOI:10.12720/jait.14.5.1003-1011
Chetana Hemant Nemade, Uma Pujeri
{"title":"Emergency Automobile Data Transmission with Ant Colony Optimization (ACO)","authors":"Chetana Hemant Nemade, Uma Pujeri","doi":"10.12720/jait.14.5.1003-1011","DOIUrl":null,"url":null,"abstract":"—Vehicular Adhoc Networks (VANET) have grown in popularity recently. Several analytical challenges must address to build VANETs that improve driver assistance, safety, and traffic management. Another big problem is the development of expandable route findings that can assess fast topography variations and numerous network detachments brought on through excellent vehicle quality. This paper will first discuss extensive technological investigations comprising and defects of the current progressive routing algorithms. Then, author suggests an entirely original routing theme called Emergency Data Transmission using ACO (EDTA). Design this protocol to use any freeway the ambulance driver has access to or any less-traveled paths with the least amount of communication overhead and delay and the highest amount of communication throughput. The patients received treatment more promptly since the driver was alerted earlier. Author developed a novel fitness function for the Ant Colony Optimization (ACO) that concentrates on two crucial vehicle parameters: current travel speed and data/network congestion. The ACO is used to optimize to identify a more stable and reliable channel that enables rapid communication between vehicles. The performance of this protocol will compare to that of a state-of-the-art protocol in conclusion with “average throughput”, “packet delivery ratio”, “communication overhead”","PeriodicalId":0,"journal":{"name":"","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12720/jait.14.5.1003-1011","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

—Vehicular Adhoc Networks (VANET) have grown in popularity recently. Several analytical challenges must address to build VANETs that improve driver assistance, safety, and traffic management. Another big problem is the development of expandable route findings that can assess fast topography variations and numerous network detachments brought on through excellent vehicle quality. This paper will first discuss extensive technological investigations comprising and defects of the current progressive routing algorithms. Then, author suggests an entirely original routing theme called Emergency Data Transmission using ACO (EDTA). Design this protocol to use any freeway the ambulance driver has access to or any less-traveled paths with the least amount of communication overhead and delay and the highest amount of communication throughput. The patients received treatment more promptly since the driver was alerted earlier. Author developed a novel fitness function for the Ant Colony Optimization (ACO) that concentrates on two crucial vehicle parameters: current travel speed and data/network congestion. The ACO is used to optimize to identify a more stable and reliable channel that enables rapid communication between vehicles. The performance of this protocol will compare to that of a state-of-the-art protocol in conclusion with “average throughput”, “packet delivery ratio”, “communication overhead”
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
基于蚁群算法的应急汽车数据传输
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 去求助
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1