利用人工智能管理6G汽车网络的能源体验权衡

Q1 Social Sciences
Hao Ran Chi, Ayman Radwan, Chunjiong Zhang, Abd-Elhamid M. Taha
{"title":"利用人工智能管理6G汽车网络的能源体验权衡","authors":"Hao Ran Chi, Ayman Radwan, Chunjiong Zhang, Abd-Elhamid M. Taha","doi":"10.1109/mcomstd.0006.2200060","DOIUrl":null,"url":null,"abstract":"While great advances have been made in vehicular networks, especially in terms of softwarization and dynamic infrastructure, increasing dependence on Artificial Intelligence (AI) continues to challenge optimizations of the Energy Efficiency (EE)-Quality of Experience (QoE) tradeoffs. Moreover, optimal achievement of trade-off between EE and QoE will be put under great challenge in upcoming emerging 6G applications, resulting from identifying EE as a quantitative requirement for the first time in 6G. In this article, we present a comprehensive overview for the requirements of QoE and EE, throughout 4G, 5G, and beyond 5G. We summarize the mutual and conflicted perspectives of achieving high QoE and EE, considering the standardizations of the selected scenarios: industrial-based vehicular network and smart transportation. We also provide an insight into the potential challenges and opportunities, for future AI-based 6G vehicular networks, regarding QoE and EE.","PeriodicalId":36719,"journal":{"name":"IEEE Communications Standards Magazine","volume":"118 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Managing Energy-Experience Trade-Off with AI Towards 6G Vehicular Networks\",\"authors\":\"Hao Ran Chi, Ayman Radwan, Chunjiong Zhang, Abd-Elhamid M. Taha\",\"doi\":\"10.1109/mcomstd.0006.2200060\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"While great advances have been made in vehicular networks, especially in terms of softwarization and dynamic infrastructure, increasing dependence on Artificial Intelligence (AI) continues to challenge optimizations of the Energy Efficiency (EE)-Quality of Experience (QoE) tradeoffs. Moreover, optimal achievement of trade-off between EE and QoE will be put under great challenge in upcoming emerging 6G applications, resulting from identifying EE as a quantitative requirement for the first time in 6G. In this article, we present a comprehensive overview for the requirements of QoE and EE, throughout 4G, 5G, and beyond 5G. We summarize the mutual and conflicted perspectives of achieving high QoE and EE, considering the standardizations of the selected scenarios: industrial-based vehicular network and smart transportation. We also provide an insight into the potential challenges and opportunities, for future AI-based 6G vehicular networks, regarding QoE and EE.\",\"PeriodicalId\":36719,\"journal\":{\"name\":\"IEEE Communications Standards Magazine\",\"volume\":\"118 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Communications Standards Magazine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/mcomstd.0006.2200060\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Communications Standards Magazine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/mcomstd.0006.2200060","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Social Sciences","Score":null,"Total":0}
引用次数: 0

摘要

虽然汽车网络已经取得了巨大的进步,特别是在软件化和动态基础设施方面,但对人工智能(AI)的依赖日益增加,继续挑战着能效(EE)和体验质量(QoE)权衡的优化。此外,由于在6G中首次将EE确定为定量需求,在即将出现的6G应用中,EE和QoE之间权衡的最佳实现将面临巨大挑战。在本文中,我们全面概述了4G、5G和5G之后的QoE和EE需求。我们总结了实现高QoE和EE的相互和冲突的观点,考虑了所选场景的标准化:基于工业的车辆网络和智能交通。我们还提供了未来基于人工智能的6G汽车网络在QoE和EE方面的潜在挑战和机遇。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Managing Energy-Experience Trade-Off with AI Towards 6G Vehicular Networks
While great advances have been made in vehicular networks, especially in terms of softwarization and dynamic infrastructure, increasing dependence on Artificial Intelligence (AI) continues to challenge optimizations of the Energy Efficiency (EE)-Quality of Experience (QoE) tradeoffs. Moreover, optimal achievement of trade-off between EE and QoE will be put under great challenge in upcoming emerging 6G applications, resulting from identifying EE as a quantitative requirement for the first time in 6G. In this article, we present a comprehensive overview for the requirements of QoE and EE, throughout 4G, 5G, and beyond 5G. We summarize the mutual and conflicted perspectives of achieving high QoE and EE, considering the standardizations of the selected scenarios: industrial-based vehicular network and smart transportation. We also provide an insight into the potential challenges and opportunities, for future AI-based 6G vehicular networks, regarding QoE and EE.
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
10.80
自引率
0.00%
发文量
55
×
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