Joint Optimization of Energy Consumption and Network Latency in Blockchain-Enabled Fog Computing Networks

被引:0
|
作者
Huang Xiaoge [1 ]
Yin Hongbo [1 ]
Cao Bin [2 ]
Wang Yongsheng [1 ]
Chen Qianbin [1 ]
Zhang Jie [3 ]
机构
[1] School of Communications and Information Engineering, Chongqing University of Posts and Telecommunications
[2] State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications
[3] School of Communication and Information Engineering, University of Sheffield
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
D O I
暂无
中图分类号
TP311.13 []; TP393.09 [];
学科分类号
080402 ; 1201 ;
摘要
Fog computing is considered as a solution to accommodate the emergence of booming requirements from a large variety of resource-limited Internet of Things(Io T) devices. To ensure the security of private data, in this paper, we introduce a blockchain-enabled three-layer device-fog-cloud heterogeneous network. A reputation model is proposed to update the credibility of the fog nodes(FN), which is used to select blockchain nodes(BN) from FNs to participate in the consensus process. According to the Rivest-Shamir-Adleman(RSA) encryption algorithm applied to the blockchain system, FNs could verify the identity of the node through its public key to avoid malicious attacks. Additionally, to reduce the computation complexity of the consensus algorithms and the network overhead, we propose a dynamic offloading and resource allocation(DORA) algorithm and a reputation-based democratic byzantine fault tolerant(R-DBFT) algorithm to optimize the offloading decisions and decrease the number of BNs in the consensus algorithm while ensuring the network security.Simulation results demonstrate that the proposed algorithm could efficiently reduce the network overhead,and obtain a considerable performance improvement compared to the related algorithms in the previous literature.
引用
收藏
页码:104 / 119
页数:16
相关论文
共 50 条
  • [1] Joint optimization of energy consumption and network latency in blockchain-enabled fog computing networks
    Huang, Xiaoge
    Yin, Hongbo
    Cao, Bin
    Wang, Yongsheng
    Chen, Qianbin
    Zhang, Jie
    CHINA COMMUNICATIONS, 2024, 21 (04) : 104 - 119
  • [2] Blockchain-Enabled Clustered Federated Learning in Fog Computing Networks
    Huang, Xiaoge
    Zhi, Chen
    Chen, Qianbin
    Zhang, Jie
    2021 IEEE 94TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2021-FALL), 2021,
  • [3] Blockchain-enabled cooperative computing strategy for resource sharing in fog networks
    Rani, Shalli
    Gupta, Divya
    Herencsar, Norbert
    Srivastava, Gautam
    INTERNET OF THINGS, 2023, 21
  • [4] Blockchain-Enabled Task Offloading and Resource Allocation in Fog Computing Networks
    Huang, Xiaoge
    Deng, Xuesong
    Liang, Chengchao
    Fan, Weiwei
    WIRELESS COMMUNICATIONS & MOBILE COMPUTING, 2021, 2021
  • [5] Resource Allocation and Task Offloading in Blockchain-Enabled Fog Computing Networks
    Huang, Xiaoge
    Liu, Xin
    Chen, Qianbin
    Zhang, Jie
    2021 IEEE 94TH VEHICULAR TECHNOLOGY CONFERENCE (VTC2021-FALL), 2021,
  • [6] Research on Optimization Scheme of Task Offloading in Blockchain-enabled Fog Networks
    Huang Xiaoge
    Liu Xin
    He Yong
    Chen Qianbin
    JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY, 2022, 44 (07) : 2440 - 2448
  • [7] Location-Based Reliable Sharding in Blockchain-Enabled Fog Computing Networks
    Huang, Xiaoge
    Yin, Hongbo
    Wang, Yongsheng
    Chen, Qianbin
    Zhang, Jie
    2022 14TH INTERNATIONAL CONFERENCE ON WIRELESS COMMUNICATIONS AND SIGNAL PROCESSING, WCSP, 2022, : 12 - 16
  • [8] A REVIEW OF BLOCKCHAIN-ENABLED FOG COMPUTING IN THE CLOUD CONTINUUM CONTEXT
    Spataru, Adrian
    SCALABLE COMPUTING-PRACTICE AND EXPERIENCE, 2021, 22 (04): : 463 - 468
  • [9] A Blockchain-Enabled Fog Computing Model for Peer-To-Peer Energy Trading in Smart Grid
    Shukla, Saurabh
    Thakur, Subhasis
    Hussainf, Shahid
    Breslin, John G.
    BLOCKCHAIN AND APPLICATIONS, 2022, 320 : 14 - 23
  • [10] Decentralized Privacy Using Blockchain-Enabled Federated Learning in Fog Computing
    Qu, Youyang
    Gao, Longxiang
    Luan, Tom H.
    Xiang, Yong
    Yu, Shui
    Li, Bai
    Zheng, Gavin
    IEEE INTERNET OF THINGS JOURNAL, 2020, 7 (06): : 5171 - 5183