Journal article
Secure Multi-Layer MEC Systems With UAV-Enabled Reconfigurable Intelligent Surface Against Full-Duplex Eavesdropper
IEEE Transactions on Communications, Vol.72(3), pp.1565-1577
2024
Abstract
In this paper, we develop a secure multi-layer mobile edge computing (MEC) system where an unmanned aerial vehicle (UAV) equipped with a reconfigurable intelligent surface (RIS) acts as an aerial edge server and assists the offloading from multiple ground users to a base station (BS), in the presence of a full-duplex active eavesdropper (AE). To enhance the computing performance, we consider a partially offloading scheme where the computational task at each user can be executed at itself and offloaded to the UAV edge server and the BS via the UAV-enabled RIS, respectively. To maximize the total number of secure computing tasks among all users, we design a low complexity iterative algorithm by jointly optimizing the RIS phase shift, UAV deployment, power and computing resource allocation subject to certain power constraints. Numerical results show that compared to benchmark offloading schemes, our proposed UAV-RIS aided multi-layer MEC design improves the computing performance by at least 12.91%. Numerical results also demonstrate the impact of the full-duplex AE and validate the robustness of our proposed solution.
Details
- Title
- Secure Multi-Layer MEC Systems With UAV-Enabled Reconfigurable Intelligent Surface Against Full-Duplex Eavesdropper
- Authors
- Yi Zhou (Author) - Southwest Jiaotong UniversityZheng Ma (Author) - Southwest Jiaotong UniversityGang Liu (Author) - Southwest Jiaotong UniversityZhengquan Zhang (Author) - Southwest Jiaotong UniversityPhee Lep Yeoh (Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringBranka Vucetic (Author) - University of SydneyYonghui Li (Author) - University of Sydney
- Publication details
- IEEE Transactions on Communications, Vol.72(3), pp.1565-1577
- Publisher
- Institute of Electrical and Electronics Engineers
- DOI
- 10.1109/TCOMM.2023.3337239
- ISSN
- 1558-0857
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 99982897302621
- Output Type
- Journal article
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