Energy-efficient Edge Association in Digital Twin empowered 6G Networks

Ruixi Zhao, Kecheng Zhang, Yan Zhang
{"title":"Energy-efficient Edge Association in Digital Twin empowered 6G Networks","authors":"Ruixi Zhao, Kecheng Zhang, Yan Zhang","doi":"10.1109/ICCT56141.2022.10073211","DOIUrl":null,"url":null,"abstract":"Digital twin (DT) emerges as a promising technology to realize highly reliable and low-latency communication in 6G. The co-evolution between physical devices and their virtual twins in DT technology is crucial that guarantees efficient operation of Digital Twin Edge Networks (DITEN). However, due to the huge amount of data transmitted from physical layer to digital twin layer and the heavy tasks offloading to edge servers, the co-evolution may cause quite heavy energy consumption of user devices and high computation overhead of edge servers. In this paper, we propose a digital twin edge association scheme which integrates digital twins with edge networks to enable low energy consumption and low computation overhead edge association. First, we introduce a DITEN model and define energy-efficient edge association problem. Then, we solve the problem in a Stackelberg Game model approach and give performance evaluation results. Finally, we conclude the paper and discuss future work.","PeriodicalId":294057,"journal":{"name":"2022 IEEE 22nd International Conference on Communication Technology (ICCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 22nd International Conference on Communication Technology (ICCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCT56141.2022.10073211","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

Digital twin (DT) emerges as a promising technology to realize highly reliable and low-latency communication in 6G. The co-evolution between physical devices and their virtual twins in DT technology is crucial that guarantees efficient operation of Digital Twin Edge Networks (DITEN). However, due to the huge amount of data transmitted from physical layer to digital twin layer and the heavy tasks offloading to edge servers, the co-evolution may cause quite heavy energy consumption of user devices and high computation overhead of edge servers. In this paper, we propose a digital twin edge association scheme which integrates digital twins with edge networks to enable low energy consumption and low computation overhead edge association. First, we introduce a DITEN model and define energy-efficient edge association problem. Then, we solve the problem in a Stackelberg Game model approach and give performance evaluation results. Finally, we conclude the paper and discuss future work.
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
基于数字孪生的6G网络中的节能边缘关联
数字孪生(DT)技术是在6G环境下实现高可靠、低延迟通信的一种有前景的技术。在数字孪生边缘网络(Digital Twin Edge network, DITEN)中,物理设备与其虚拟孪生设备之间的协同演化是保证其高效运行的关键。但是,由于物理层到数字孪生层之间传输的数据量巨大,并且需要将大量的任务转移到边缘服务器,因此这种协同演化可能会导致用户设备的能耗相当大,边缘服务器的计算开销也很高。本文提出了一种将数字孪生与边缘网络相结合的数字孪生边缘关联方案,以实现低能耗和低计算开销的边缘关联。首先,我们引入了一个DITEN模型,并定义了能效边关联问题。然后,我们用Stackelberg博弈模型的方法解决了这个问题,并给出了性能评价结果。最后,对全文进行了总结,并对今后的工作进行了展望。
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
Anomaly Detection Method For Interactive Data of Third-Party Load Aggregation Platform Based on Multidimensional Feature Information Fusion Stable and Robust Improvement of AMP for Supporting Massive Connectivity Power Allocation and Beamforming Vectors Optimization in STAR-RIS Assisted SWIPT Joint Identification of Modulation and Channel Coding Based on Deep Learning Geometric Feature Detection of Space Targets Based on Color Space
×
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