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Intelligent resource allocation in mobile blockchain for privacy and security transactions: a deep reinforcement learning based approach

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Abstract

In order to protect the privacy and data security of mobile devices during the transactions in the industrial Internet of Things (IIoT), we propose a mobile edge computing (MEC)-based mobile blockchain framework by considering the limited bandwidth and computing power of small base stations (SBSs). First, we formulate a joint bandwidth and computing resource allocation problem to maximize the long-term utility of all mobile devices, and take into account the mobility of devices as well as the blockchain throughput. We decompose the formulated problem into two subproblems to decrease the dimension of action space. Then, we propose a deep reinforcement learning additional particle swarm optimization (DRPO) algorithm to solve the two subproblems, in which a particle swarm optimization algorithm is leveraged to avoid the unnecessary search of a deep deterministic policy gradient approach. Simulation results demonstrate the effectiveness of our method from various aspects.

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Acknowledgements

This work was supported in part by National Key R&D Program of China (Grant No. 2018YFE0206800), National Natural Science Foundation of China (Grant Nos. 61701406, 61971084, 62001073), National Natural Science Foundation of Chongqing (Grant Nos. cstc2019jcyjcxttX0002, cstc2019jcyj-msxmX0208), and Chongqing Talent Program (Grant No. CQYC2020058659).

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Authors and Affiliations

  1. School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Zhaolong Ning, Xiaojie Wang & Lei Guo

  2. School of Software, Dalian University of Technology, Dalian, 116620, China

    Zhaolong Ning & Shouming Sun

  3. State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou, 310007, China

    Zhaolong Ning

  4. Chongqing Key Laboratory of Computational Intelligence, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Guoyin Wang

  5. Chongqing Key Laboratory of Image Cognition, Chongqing University of Posts and Telecommunications, Chongqing, 400065, China

    Xinbo Gao

  6. Department of Electrical and Electronic Engineering, University of Hong Kong, Hong Kong, 999077, China

    Ricky Y. K. Kwok

Authors
  1. Zhaolong Ning
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  2. Shouming Sun
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  3. Xiaojie Wang
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  4. Lei Guo
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  5. Guoyin Wang
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  6. Xinbo Gao
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  7. Ricky Y. K. Kwok
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Corresponding author

Correspondence to Xiaojie Wang.

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Ning, Z., Sun, S., Wang, X. et al. Intelligent resource allocation in mobile blockchain for privacy and security transactions: a deep reinforcement learning based approach. Sci. China Inf. Sci. 64, 162303 (2021). https://doi.org/10.1007/s11432-020-3125-y

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  • DOI: https://doi.org/10.1007/s11432-020-3125-y

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