跳到主要导航 跳到搜索 跳到主要内容

Delay-Optimal Cooperative Vehicle-Infrastructure Computing with IRS-Enhanced Secure Wireless Communications

  • University of Waterloo
  • Shanghai Artificial Intelligence Laboratory
  • University of Glasgow
  • University of Sussex

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Mobile edge computing(MEC) addresses the challenges posed by the rapid growth of VANETs in transmitting real-time, reliable, and large amounts of data between vehicles and roadside infrastructure. To ensure information security in MEC-based VANETs, Intelligent Reflective Surface (IRS) technology is considered as a viable solution. By combining the technical advantages of edge computing and IRS, this study proposes a joint optimization problem to achieve a secure, efficient, and low-latency offloading and communication scheme for vehicular and roadside infrastructure computation and communication. The PSO algorithm is employed as the basis for an alternating optimization scheme to solve the proposed joint optimization problem. Numerical simulation analyses demonstrate the significant advantages of the proposed solution in terms of overall system latency.

源语言英语
主期刊名Proceedings of 2023 IEEE International Conference on Unmanned Systems, ICUS 2023
编辑Rong Song
出版商Institute of Electrical and Electronics Engineers Inc.
1720-1725
页数6
ISBN(电子版)9798350316308
DOI
出版状态已出版 - 2023
活动2023 IEEE International Conference on Unmanned Systems, ICUS 2023 - Hefei, 中国
期限: 13 10月 202315 10月 2023

出版系列

姓名Proceedings of 2023 IEEE International Conference on Unmanned Systems, ICUS 2023

会议

会议2023 IEEE International Conference on Unmanned Systems, ICUS 2023
国家/地区中国
Hefei
时期13/10/2315/10/23

指纹

探究 'Delay-Optimal Cooperative Vehicle-Infrastructure Computing with IRS-Enhanced Secure Wireless Communications' 的科研主题。它们共同构成独一无二的指纹。

引用此