计算机科学

计算机科学 ›› 2025, Vol. 52 ›› Issue (5): 366-374.doi: 10.11896/jsjkx.240300018

• 信息安全 • 上一篇    下一篇

BDBFT:一种物联网场景下基于信誉预测模型的共识协议

王璞1, 高湛云1, 王振飞1, 宋哲理2   

  1. 1 郑州大学计算机与人工智能学院 郑州 450001
    2 郑州财税金融职业学院信息技术系 郑州 450048
  • 收稿日期:2024-03-02 修回日期:2024-07-19 出版日期:2025-05-15 发布日期:2025-05-12
  • 通讯作者: 宋哲理(710491238@qq.com)
  • 作者简介:(iezfwang@zzu.edu.cn)
  • 基金资助:
    国家重点研发计划(2023YFB4502704);河南省科技攻关项目(232102210189)

BDBFT:A Consensus Protocol Based on Reputation Prediction Model for IoT Scenario

WANG Pu1, GAO Zhanyun1, WANG Zhenfei1, SONG Zheli2   

  1. 1 College of Computer and Artificial Intelligence,Zhengzhou University,Zhengzhou 450001,China
    2 Department of Information Technology,Zhengzhou Vocational College of Finance and Taxation,Zhengzhou 450048,China
  • Received:2024-03-02 Revised:2024-07-19 Online:2025-05-15 Published:2025-05-12
  • About author:
    WANG Pu,born in 1998,postgraduate.His main research interests include blockchain technology and consensus algorithm.
    SONG Zheli,born in 1983,postgra-duate,associate professor.Her main research interests include big data and blockchain technology.
  • Supported by:
    National Key Research and Development Program of China(2023YFB4502704) and Science and Technology Research Project of Henan Province(232102210189).

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摘要： 区块链技术在物联网场景的应用中具有强数据安全性和高可信度的优势,但区块链技术中的共识算法存在能耗高、计算成本高、可扩展性低等缺点,在物联网应用中部署区块链系统面临物联网节点存储容量小、能耗低和计算能力不足的问题。在实用拜占庭容错算法(PBFT)的基础上,提出了一种物联网场景下基于信誉预测模型的共识协议(BDBFT)。首先,根据分组策略的地理位置分类标准对节点进行分组以选取共识节点,减少组内通信的通信时延;其次,引入基于Dirichlet分布的细粒度信誉预测模型,根据每轮视图生命周期中的信誉信息动态地更新模型,并基于历史信誉信息和当前信誉信息投票高预测概率的节点作为共识节点。仿真实验结果表明,相对于PBFT算法和LRBFT算法,BDBFT算法有效地降低了拜占庭节点参与共识的概率,在时间延迟、吞吐量、通信开销和安全性4个方面具有明显的性能提升。

关键词: 物联网, 区块链, PBFT, Dirichlet分布, 分组策略, 信誉预测模型

Abstract: Blockchain technology has the advantages of strong data security and high trustworthiness in IoT scenarios,but the consensus algorithm in blockchain technology has the disadvantages of high energy consumption,high computational cost,and low scalability,and the deployment of blockchain system in IoT applications faces the problems of low storage capacity,low energy consumption,and low computational capacity of IoT nodes.Based on practical Byzantine fault tolerant algorithm(PBFT),this paper proposes a consensus protocol based on reputation prediction model(BDBFT) in IoT scenario.Firstly,nodes are grouped according to the geographic location classification criteria of the grouping policy to select consensus nodes and reduce the communication delay of intra-group communication.Secondly,a fine-grained reputation prediction model based on Dirichlet distribution is introduced to dynamically update the model according to the reputation information in the lifecycle of each round of view,and nodes with high prediction probability based on the historical and current reputation information are voted as the consensus nodes.The simulation experiment results show that compared with PBFT algorithm and LRBFT algorithm,BDBFT algorithm effectively reduces the probability of Byzantine nodes participating in the consensus,and has obvious performance improvement in four aspects:time delay,throughput,communication overhead and security.

Key words: IoT, Blockchain, PBFT, Dirichlet distribution, Grouping strategy, Reputation prediction model

中图分类号: 

  • TP311
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