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

作　　者：Liang YAO Xiaolong XU Wanchun DOU Muhammad Bilal 

机构地区：[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]Department of Computer and Electronics Systems Engineering,Hankuk University of Foreign Studies,Yongin-si 17035,Korea

出　　处：《Chinese Journal of Electronics》2024年第4期910-919,共10页电子学报（英文版）

基　　金：Natural Science Foundation of Jiangsu Province of China (Grant No. BK20211284);National Natural Science Foundation of China (Grant No. 92267104);Financial and Science Technology Plan Project of Xinjiang Production and Construction Corps (Grant No. 2020DB005)。

摘　　要：As a pivotal enabler of intelligent transportation system(ITS), Internet of vehicles(Io V) has aroused extensive attention from academia and industry. The exponential growth of computation-intensive, latency-sensitive,and privacy-aware vehicular applications in Io V 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.

关 键 词：Intelligent transportation system Deep reinforcement learning Edge computing Privacy protection 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程] TP309[自动化与计算机技术—控制科学与工程] U495[交通运输工程—交通运输规划与管理]