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Communications and Networking. 17th EAI International Conference, Chinacom 2022, Virtual Event, November 19-20, 2022, Proceedings

Research Article

Privacy-Aware Task Allocation with Service Differentiation for Mobile Edge Computing: Multi-armed Bandits Approach

Cite
BibTeX Plain Text
  • @INPROCEEDINGS{10.1007/978-3-031-34790-0_7,
        author={Hangfan Li and Lin Shi and Xiaoxiong Zhong and Yun Ji and Sheng Zhang},
        title={Privacy-Aware Task Allocation with Service Differentiation for Mobile Edge Computing: Multi-armed Bandits Approach},
        proceedings={Communications and Networking. 17th EAI International Conference, Chinacom 2022, Virtual Event, November 19-20, 2022, Proceedings},
        proceedings_a={CHINACOM},
        year={2023},
        month={6},
        keywords={Mobile Edge Computing (MEC) Privacy Preserving Multi-armed Bandits (MAB)},
        doi={10.1007/978-3-031-34790-0_7}
    }
    
  • Hangfan Li
    Lin Shi
    Xiaoxiong Zhong
    Yun Ji
    Sheng Zhang
    Year: 2023
    Privacy-Aware Task Allocation with Service Differentiation for Mobile Edge Computing: Multi-armed Bandits Approach
    CHINACOM
    Springer
    DOI: 10.1007/978-3-031-34790-0_7
Hangfan Li1, Lin Shi1, Xiaoxiong Zhong1,*, Yun Ji2, Sheng Zhang2
  • 1: Guilin University of Electronic Technology
  • 2: Graduate School at Shenzhen, Tsinghua University
*Contact email: xixzhong@gmail.com

Abstract

With the development of fifth generation (5G) technology, mobile edge computing (MEC) is becoming an essential architecture which is envisioned as a cloud extension version. MEC system can push the resources from cloud side to edge side, aiming to solve many computation intensive problems. The task offloading policy is vital and has an important influence on MEC system. Meanwhile, privacy leakage may occur during the task offloading period which may degrade MEC system performance. The attention on these issues is lack according to existing works. Inspired by this, we present a privacy-preserving aware Multi-Armed Bandits based task allocation algorithm,PrivacyUpperConfidenceBound (pUCB), to find a balance between the privacy preserving and the efficiency of task processing. In addition, we take regret analysis of the proposed algorithm. The extensive simulation results show that pUCB scheme can achieve a higher optimal rate, a lower lock rate and less total time cost comparing with traditional Multi-arm bandits (MAB) based algorithm.

Keywords
Mobile Edge Computing (MEC) Privacy Preserving Multi-armed Bandits (MAB)
Published
2023-06-10
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-031-34790-0_7
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