An Intelligent Privacy Protection Scheme for Efficient Edge Computation Offloading in IoV

YAO Liang; XU Xiaolong; DOU Wanchun; Bilal Muhammad

doi:10.23919/cje.2023.00.111

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Liang YAO, Xiaolong XU, Wanchun DOU, et al., “An Intelligent Privacy Protection Scheme for Efficient Edge Computation Offloading in IoV,” Chinese Journal of Electronics, vol. 33, no. 5, pp. 1–10, 2024 doi: 10.23919/cje.2023.00.111

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Liang YAO, Xiaolong XU, Wanchun DOU, et al., “An Intelligent Privacy Protection Scheme for Efficient Edge Computation Offloading in IoV,” Chinese Journal of Electronics, vol. 33, no. 5, pp. 1–10, 2024 doi: 10.23919/cje.2023.00.111

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An Intelligent Privacy Protection Scheme for Efficient Edge Computation Offloading in IoV

doi: 10.23919/cje.2023.00.111

YAO Liang^1
,,
XU Xiaolong^{1, 2
,
,},
DOU Wanchun^2
,,
Bilal Muhammad^3
,

1.
School of Software, Nanjing University of Information Science and Technology, Nanjing 210044, China
2.
State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210044, China
3.
Dept of Computer and Electronics Systems Engineering, Hankuk University of Foreign Studies, Yongin-si, Gyeonggi-do, 17035, Korea

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Author Bio:
Liang YAO is currently studying for his masters degree in Software Engineering in Nanjing University of Information Science and Technology. His areas of interest are mobile computing, big data, cloud computing and machine learning. (Email: nuistlyao@gmail.com)

Xiaolong XU received the Ph.D. degree in Computer Science and Technology from Nanjing University, China, in 2016. He was a Research Scholar with Michigan State University, USA, from April 2017 to May 2018. He is currently an Associate Professor with the School of Computer and Software, Nanjing University of Information Science and Technology. He received the Best Paper Award from the IEEE CBD 2016, the TOP citation award from the Computational Intelligence journal in 2019, the Distinguished Paper Award and the Best Student Paper of EAI Cloudcomp 2019. His research interests include edge computing, the Internet of Things (IoT), cloud computing, and big data.(Email: xlxu@ieee.org)

Wanchun DOU is currently a Full Professor at the State Key Laboratory for Novel Software Technology, Nanjing University. His research interests include workflow, cloud computing, and service computing. (Email: douwc@nju.edu.cn)

Muhammad Bilal received the B.S. degree in Computer Systems Engineering from the University of Engineering and Technology, Peshawar, Pakistan, the M.S. degree in computer engineering from Chosun University, Gwangju, South Korea, and the Ph.D. degree in Information and Communication Network Engineering from School of Electronics and Telecommunications Research Institute, Korea University of Science and Technology, Daejeon, South Korea. He is an Assistant Professor of computer sciencewith the Department of Computer and Electronic Systems Engineering, Hankuk University of Foreign Studies, Yongin, South Korea. Prior to joining Hankuk University of Foreign Studies, he was a Postdoctoral Research Fellow with the Smart Quantum Communication Center, Korea University. His primary research interests include design and analysis of network protocols, network architecture, network security, IoT, named data networking and future internet.Dr. Bilal has served as a Reviewer of various international journals including IEEE SYSTEMS JOURNAL, IEEE ACCESS, IEEE COMMUNICATIONS LETTERS, IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT, Journal of Network and Computer Applications, Personal and Ubiquitous Computing, and International Journal of Communication Systems. He has also served as a program committee member on many international conferences.(Email: m.bilal@ieee.ac.kr)
Corresponding author: Email: xlxu@ieee.org
Received Date: 2023-03-31
Accepted Date: 2023-09-07

Available Online: 2024-02-04

Abstract

Abstract

As a pivotal enabler of intelligent transportation system (ITS), internet of vehicles (IoV) has aroused extensive attention from academia and industry. The exponential growth of computation-intensive, latency-sensitive and privacy-aware vehicular applications in IoV result in the transformation from cloud computing to edge computing, which enables tasks to be offloaded to edge nodes (ENs) closer to vehicles for efficient execution. In ITS environment, however, due to dynamic and stochastic computation offloading requests, it is challenging to efficiently orchestrate offloading decisions for application requirements. How to accomplish complex computation offloading of vehicles while ensuring data privacy remains challenging. In this paper, we propose an intelligent computation offloading with privacy protection scheme, named COPP. In particular, an Advanced Encryption Standard-based encryption method is utilized to implement privacy protection. Furthermore, an online offloading scheme is proposed to find optimal offloading policies. Finally, experimental results demonstrate that COPP significantly outperforms benchmark schemes in the performance of both delay and energy consumption.
- Intelligent transportation system,
- deep reinforcement learning,
- edge computing,
- privacy protection

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References(29)

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