基于神经网络的vanet链路状态估计

IF 4.1 3区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Hamida Ikhlef, Soumia Bourebia, Ali Melit
{"title":"基于神经网络的vanet链路状态估计","authors":"Hamida Ikhlef, Soumia Bourebia, Ali Melit","doi":"10.1007/s10922-023-09786-5","DOIUrl":null,"url":null,"abstract":"<p>In Vehicular Ad-hoc NETworks (VANETs), it is important to consider the quality of the path used to forward data packets. Because of the fluctuating conditions of VANETs, stringent requirements have been imposed on routing protocols and thus complicating the entire process of packet delivery. To determine which path is the best, a routing protocol relies on a path assessment mechanism. In this paper, the problem of link quality estimation in VANET networks is addressed. Based on the information gathered from the packet decoding errors at the physical layer, a novel link quality estimator is proposed. The proposed link quality estimator named LSENN for Link State estimation based on Neural Networks, has been tested under realistic physical layer and mobility models for reactivity, accuracy and stability evaluation.\n</p>","PeriodicalId":50119,"journal":{"name":"Journal of Network and Systems Management","volume":"181 5","pages":""},"PeriodicalIF":4.1000,"publicationDate":"2023-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Link State Estimator for VANETs Using Neural Networks\",\"authors\":\"Hamida Ikhlef, Soumia Bourebia, Ali Melit\",\"doi\":\"10.1007/s10922-023-09786-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In Vehicular Ad-hoc NETworks (VANETs), it is important to consider the quality of the path used to forward data packets. Because of the fluctuating conditions of VANETs, stringent requirements have been imposed on routing protocols and thus complicating the entire process of packet delivery. To determine which path is the best, a routing protocol relies on a path assessment mechanism. In this paper, the problem of link quality estimation in VANET networks is addressed. Based on the information gathered from the packet decoding errors at the physical layer, a novel link quality estimator is proposed. The proposed link quality estimator named LSENN for Link State estimation based on Neural Networks, has been tested under realistic physical layer and mobility models for reactivity, accuracy and stability evaluation.\\n</p>\",\"PeriodicalId\":50119,\"journal\":{\"name\":\"Journal of Network and Systems Management\",\"volume\":\"181 5\",\"pages\":\"\"},\"PeriodicalIF\":4.1000,\"publicationDate\":\"2023-11-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Network and Systems Management\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1007/s10922-023-09786-5\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Network and Systems Management","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10922-023-09786-5","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0

摘要

在车辆自组织网络(vanet)中,考虑用于转发数据包的路径的质量是很重要的。由于vanet的条件波动,对路由协议提出了严格的要求,从而使整个分组传递过程复杂化。为了确定哪条路径是最好的,路由协议依赖于路径评估机制。本文研究了VANET网络中链路质量的估计问题。基于物理层的分组解码错误信息,提出了一种新的链路质量估计方法。提出的基于神经网络的链路状态估计方法LSENN,已在现实物理层和移动模型下进行了反应性、准确性和稳定性评估。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Link State Estimator for VANETs Using Neural Networks

Link State Estimator for VANETs Using Neural Networks

In Vehicular Ad-hoc NETworks (VANETs), it is important to consider the quality of the path used to forward data packets. Because of the fluctuating conditions of VANETs, stringent requirements have been imposed on routing protocols and thus complicating the entire process of packet delivery. To determine which path is the best, a routing protocol relies on a path assessment mechanism. In this paper, the problem of link quality estimation in VANET networks is addressed. Based on the information gathered from the packet decoding errors at the physical layer, a novel link quality estimator is proposed. The proposed link quality estimator named LSENN for Link State estimation based on Neural Networks, has been tested under realistic physical layer and mobility models for reactivity, accuracy and stability evaluation.

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
CiteScore
7.60
自引率
16.70%
发文量
65
审稿时长
>12 weeks
期刊介绍: Journal of Network and Systems Management, features peer-reviewed original research, as well as case studies in the fields of network and system management. The journal regularly disseminates significant new information on both the telecommunications and computing aspects of these fields, as well as their evolution and emerging integration. This outstanding quarterly covers architecture, analysis, design, software, standards, and migration issues related to the operation, management, and control of distributed systems and communication networks for voice, data, video, and networked computing.
×
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