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Primary node selection based on node reputation evaluation for PBFT in UAV-assisted MEC environment

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Abstract

Blockchain technology is widely used in various fields due to its high security and reliability. And Unmanned aerial vehicle (UAV)-assisted edge computing is easy to deploy, fast, and flexible. Combining blockchain technology with UAV-assisted edge computing is a hot research topic today. In order to improve the problem of the high overhead of node communication in this environment. In this paper, a primary node selection method based on node reputation evaluation is proposed. In the traditional Practical Byzantine Fault Tolerance (PBFT) algorithm, the efficiency of node communication is very low when the number of nodes becomes large. The algorithm proposed in this paper selects the primary node based on the reputation value, which not only reduces the probability that the primary node is the wrong node but also reduces the number of communications and the communication overhead during the communication process, based on the node identity determined by the node reputation. In the experimental results, three benchmarks are selected for comparison experiments, and it is concluded that the algorithm proposed in this paper can effectively reduce the communication overhead in the PBFT algorithm, reduce the communication delay and improve the efficiency of nodes.

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Funding

The work was supported by the National Natural Science Foundation of China (NSFC) under grants (No. 62171330), Key Research and Development Plan of Hubei Province (2023BAB015), Open Fund of Chuan and Zang Smart Tourism Engineering Research Center of Colleges and universities of Sichuan Province (No. ZLGC2022A02), the open Foundation of Intelligent Manufacturing Fujian University Application Technology Engineering Center (No. ZNZZ23-01), Open Project Fund of Guangdong Provincial Key Laboratory of Intelligent Urban Security Monitoring Urban Security Monitoring and Smart City Planning (No. GPKLIUSMSCP-2023-KF-03), the Open Project Program of Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry, Wuyi University, (No. FKLBDAITI202205),Open Fund of Innovation Centre for Digital Business and Capital Development of Beijing Technology and Business University (SZSK2022015).

Author information

Authors and Affiliations

  1. Intelligent Manufacturing Fujian University Application Technology Engineering Center, Quanzhou Vocational and Technical University, Quanzhou, People’s Republic of China

    Yafeng Zhang & Chunlin Li

  2. Guangdong Provincial Key Laboratory of Intelligent Urban Security Monitoring Urban Security Monitoring and Smart City Planning, Guangzhou, People’s Republic of China

    Yafeng Zhang & Chunlin Li

  3. Sichuan Tourism College, Chengdu, 610100, People’s Republic of China

    Chunlin Li

  4. Department of Computer Science, Wuhan University of Technology, Wuhan, 430063, People’s Republic of China

    Yongzheng Gan, Chunlin Li & Youlong Luo

  5. Fujian Key Laboratory of Big Data Application and Intellectualization for Tea Industry (Wuyi University), Wuyi, China

    Youlong Luo

  6. Innovation Centre for Digital Business and Capital Development of Beijing Technology and Business University, Beijing, 430063, People’s Republic of China

    ChunPing Deng

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  1. Yafeng Zhang
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  2. Yongzheng Gan
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  3. Chunlin Li
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  4. ChunPing Deng
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  5. Youlong Luo
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Contributions

YZ,YG, CL, CD, YL designed the study, developed the methodology, performed the analysis, and wrote the manuscript. YG, CL collected the data.

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Correspondence to Chunlin Li or ChunPing Deng.

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Zhang, Y., Gan, Y., Li, C. et al. Primary node selection based on node reputation evaluation for PBFT in UAV-assisted MEC environment. Wireless Netw 29, 3515–3539 (2023). https://doi.org/10.1007/s11276-023-03407-4

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