A Spatial Model for Using the Age of Information in Cooperative Driving Applications

Julian Heinovski, J. T. Gómez, F. Dressler
{"title":"A Spatial Model for Using the Age of Information in Cooperative Driving Applications","authors":"Julian Heinovski, J. T. Gómez, F. Dressler","doi":"10.1145/3551659.3559053","DOIUrl":null,"url":null,"abstract":"The age of information (AoI) has been proposed as a metric for evaluating freshness of information; recently also within the context of intelligent transportation systems (ITS). The most frequently used definition of AoI, however, does only account for the generation time of the data but not for application-specific aspects. In ITS, for example, the distance of vehicles is not considered and nodes farther away may experience an increased AoI due to effects of the wireless communication channel. We propose a new way of interpreting the AoI in such a context, also considering the location of the transmitting vehicle as a metric of importance to the information. In particular, we introduce a weighting coefficient used in combination with the peak age of information (PAoI) metric to describe the AoI requirement, emphasizing on packets from more important neighbors. As an example, we characterize such importance using the orientation and the distance of the involved vehicles. We use the derived model to focus on timely updates of relevant vehicles for meeting a given AoI requirement, which can save resources on the wireless channel while keeping the AoI minimal.","PeriodicalId":423926,"journal":{"name":"Proceedings of the 25th International ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems","volume":"5 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 25th International ACM Conference on Modeling Analysis and Simulation of Wireless and Mobile Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3551659.3559053","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 age of information (AoI) has been proposed as a metric for evaluating freshness of information; recently also within the context of intelligent transportation systems (ITS). The most frequently used definition of AoI, however, does only account for the generation time of the data but not for application-specific aspects. In ITS, for example, the distance of vehicles is not considered and nodes farther away may experience an increased AoI due to effects of the wireless communication channel. We propose a new way of interpreting the AoI in such a context, also considering the location of the transmitting vehicle as a metric of importance to the information. In particular, we introduce a weighting coefficient used in combination with the peak age of information (PAoI) metric to describe the AoI requirement, emphasizing on packets from more important neighbors. As an example, we characterize such importance using the orientation and the distance of the involved vehicles. We use the derived model to focus on timely updates of relevant vehicles for meeting a given AoI requirement, which can save resources on the wireless channel while keeping the AoI minimal.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于信息时代的协同驾驶空间模型
信息年龄(AoI)已被提出作为评估信息新鲜度的指标;最近也在智能交通系统(ITS)的背景下。然而,最常用的AoI定义只考虑数据的生成时间,而不考虑特定于应用程序的方面。例如,在ITS中,由于无线通信信道的影响,车辆的距离不被考虑,距离较远的节点可能会经历更高的AoI。我们提出了一种在这种情况下解释AoI的新方法,同时考虑到传输车辆的位置作为信息重要性的度量。特别是,我们引入了一个加权系数,与峰值信息年龄(PAoI)指标结合使用,以描述AoI需求,强调来自更重要邻居的数据包。作为一个例子,我们使用相关车辆的方向和距离来表征这种重要性。我们使用衍生的模型来关注相关车辆的及时更新,以满足给定的AoI要求,这可以节省无线信道的资源,同时保持最小的AoI。
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
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Interference Aware Heuristics to Optimize Power Beacons for Battery-less WSNs The Interplay Between Intelligent Networks and Enabling Technologies for Future Wireless Networks A Novel Mixed Method of Machine Learning Based Models in Vehicular Traffic Flow Prediction Characterizing Wi-Fi Probing Behavior for Privacy-Preserving Crowdsensing Anonymized Counting of Nonstationary Wi-Fi Devices When Monitoring Crowds
×
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