Network Signal Comparison Through Waves Parameters: a Local-Alignment-Based Approach

W. Balzano, A. Murano, L. Sorrentino, Silvia Stranieri
{"title":"Network Signal Comparison Through Waves Parameters: a Local-Alignment-Based Approach","authors":"W. Balzano, A. Murano, L. Sorrentino, Silvia Stranieri","doi":"10.1109/IWMN.2019.8805047","DOIUrl":null,"url":null,"abstract":"The increasing interest in road safety improvement poses researchers attention on Vehicular ad Hoc Networks (VANETs). Their ability to handle vehicles communication through broadcasting and to increase traffic configuration awareness makes them a powerful means to achieve road security. Smart and compact representation of VANETs is then needed in order to collect the most useful information and to reach as much expressiveness as possible. Starting from a meaningful signal-based representation, our goal in this paper is to find affinities between different vehicular networks by identifying similarities between the corresponding waves. To this aim, we detect some parameters characterizing the signal and combine them with specific alignment techniques to obtain a similarity measure. We also experiment our approach by comparing the results against known signal similarity methodologies, such as the Dynamic Time Warping.","PeriodicalId":272577,"journal":{"name":"2019 IEEE International Symposium on Measurements & Networking (M&N)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE International Symposium on Measurements & Networking (M&N)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IWMN.2019.8805047","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

Abstract

The increasing interest in road safety improvement poses researchers attention on Vehicular ad Hoc Networks (VANETs). Their ability to handle vehicles communication through broadcasting and to increase traffic configuration awareness makes them a powerful means to achieve road security. Smart and compact representation of VANETs is then needed in order to collect the most useful information and to reach as much expressiveness as possible. Starting from a meaningful signal-based representation, our goal in this paper is to find affinities between different vehicular networks by identifying similarities between the corresponding waves. To this aim, we detect some parameters characterizing the signal and combine them with specific alignment techniques to obtain a similarity measure. We also experiment our approach by comparing the results against known signal similarity methodologies, such as the Dynamic Time Warping.
通过波参数的网络信号比较:一种基于局部对准的方法
随着人们对道路安全的日益关注,车辆自组织网络(VANETs)引起了研究人员的关注。它们通过广播处理车辆通信和提高交通配置意识的能力使其成为实现道路安全的有力手段。为了收集最有用的信息并达到尽可能多的表达能力,需要vanet的智能和紧凑的表示。从有意义的基于信号的表示开始,本文的目标是通过识别相应波之间的相似性来发现不同车辆网络之间的亲和力。为此,我们检测表征信号的一些参数,并将它们与特定的对准技术相结合,以获得相似度度量。我们还通过将结果与已知的信号相似度方法(如动态时间翘曲)进行比较来实验我们的方法。
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