计算机科学 ›› 2021, Vol. 48 ›› Issue (1): 65-71.doi: 10.11896/jsjkx.200500098

• 智能化边缘计算* 上一篇    下一篇


余雪勇, 陈涛   

  1. 江苏省无线通信重点实验室 南京 210003
  • 收稿日期:2020-05-21 修回日期:2020-08-14 出版日期:2021-01-15 发布日期:2021-01-15
  • 通讯作者: 余雪勇(yuxy@njupt.edu.cn)
  • 基金资助:

Privacy Protection Offloading Algorithm Based on Virtual Mapping in Edge Computing Scene

YU Xue-yong, CHEN Tao   

  1. Wireless Communication Key Lab of Jiangsu Province,Nanjing 210003,China
  • Received:2020-05-21 Revised:2020-08-14 Online:2021-01-15 Published:2021-01-15
  • About author:YU Xue-yong,born in 1979,Ph.D,associate professor.His main researchintere-sts include Internet of Thing (IoT),mobile edge computing and radio resource management on heterogeneous wireless networks.
  • Supported by:
    National Natural Science Foundation of China(61871446) and Natural Science Foundation of Nanjing University of Posts and Telecommunications(NY220047).

摘要: 随着移动边缘计算(Mobile Edge Computing,MEC)和无线充电技术(Wireless Power Transmission,WPT)的诞生和发展,越来越多的计算任务被卸载至MEC服务器以进行处理,并借助WPT技术为终端设备供电,以缓解终端设备计算能力受限和设备能耗过高的问题。由于卸载的任务和数据往往携带用户个人使用习惯等信息,因此将任务卸载到MEC服务器进行处理会导致新的隐私泄露问题。针对上述问题,文中首先对计算任务的隐私量进行定义,并设计了能够降低用户在MEC服务器累积隐私量的虚拟任务映射机制;然后,综合考虑映射机制与隐私约束的优化,提出了一种具有隐私保护效果的在线隐私感知计算卸载算法;最后,对仿真结果进行分析发现,所提卸载方法能够使用户累积隐私量保持在隐私阈值内,达到了隐私保护的效果,同时提高了系统计算速率,降低了用户计算时延。

关键词: 边缘计算, 计算卸载, 隐私保护, 虚拟映射, 神经网络

Abstract: With the development of mobile edge computing (MEC) and wireless power transfer (WPT),more and more computing tasks are offloaded to the MEC server for processing.The terminal equipment is powered by WPT technology to alleviate the limited computing power of the terminal equipment and high energy consumption of the terminal equipment.However,since the offloaded tasks and data often carry information such as users' personal usage habits,tasks are offloaded to the MEC server for processing results in new privacy leakage issues.A privacy-aware computation offloading method based on virtual mapping is proposed in this paper.Firstly,the privacy of the computing task is defined,and then a virtual task mapping mechanism that can reduce the amount of privacy accumulated by users on the MEC server is designed.Secondly,the online privacy-aware computing offloading algorithm is proposed by considering the optimization of the mapping mechanism and privacy constraints jointly.Finally,simulation results validate that the proposed offloading method can keep the cumulative privacy of users below the threshold,increase the system calculation rate and reduce users' calculation delay at the same time.

Key words: Edge computing, Computation offloading, Privacy protection, Virtual mapping, Neural network


  • TP393
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