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面向车联网异构节点的区块链高效一致性共识算法研究

陈友荣 章阳 陈浩 韩蒙 刘半藤 任条娟

陈友荣, 章阳, 陈浩, 韩蒙, 刘半藤, 任条娟. 面向车联网异构节点的区块链高效一致性共识算法研究[J]. 电子与信息学报, 2022, 44(1): 314-323. doi: 10.11999/JEIT201065
引用本文: 陈友荣, 章阳, 陈浩, 韩蒙, 刘半藤, 任条娟. 面向车联网异构节点的区块链高效一致性共识算法研究[J]. 电子与信息学报, 2022, 44(1): 314-323. doi: 10.11999/JEIT201065
CHEN Yourong, ZHANG Yang, CHEN Hao, HAN Meng, LIU Banteng, REN Tiaojuan. Efficient Consistency Consensus Algorithm of Blockchain for Heterogeneous Nodes in the Internet of Vehicles[J]. Journal of Electronics & Information Technology, 2022, 44(1): 314-323. doi: 10.11999/JEIT201065
Citation: CHEN Yourong, ZHANG Yang, CHEN Hao, HAN Meng, LIU Banteng, REN Tiaojuan. Efficient Consistency Consensus Algorithm of Blockchain for Heterogeneous Nodes in the Internet of Vehicles[J]. Journal of Electronics & Information Technology, 2022, 44(1): 314-323. doi: 10.11999/JEIT201065

面向车联网异构节点的区块链高效一致性共识算法研究

doi: 10.11999/JEIT201065
基金项目: 浙江省公益技术应用研究计划(LGG19F010011)
详细信息
    作者简介:

    陈友荣:男,1982年生,博士,教授,研究方向为网络安全和物联网应用

    章阳:男,1998年生,硕士生,研究方向为网络安全和区块链

    陈浩:男,1998年生,硕士生,研究方向为网络安全和区块链

    韩蒙:男,1987年生,博士,助理教授,研究方向为网络安全和区块链

    刘半藤:男,1984年生,博士,副教授,研究方向为网络安全和人工智能

    任条娟:女,1965年生,博士,教授,研究方向为网络安全和车联网

    通讯作者:

    任条娟 kuanren988 @sina.com

  • 中图分类号: TN915; TP309

Efficient Consistency Consensus Algorithm of Blockchain for Heterogeneous Nodes in the Internet of Vehicles

Funds: The Public Welfare Technology Application and Research Projects of Zhejiang Province of China (LGG19F010011)
  • 摘要: 车联网异构节点由于其性能差异大、具有移动性等原因会造成区块链共识算法交易吞吐率低、交易时延较大等问题,该文提出面向车联网异构节点的区块链高效一致性共识算法(ECCA)。首先,在ECCA中,考虑由验证节点、一般节点和恶意节点组成的车联网异构节点,提出一种信用等级机制,实现信用等级划分和3类异构节点的划分。其次,提出一种跨区下的节点身份变更机制,及时调整当前区域内的节点身份。最后,提出一种改进的一致性共识算法,满足车联网的时效性需求。仿真结果表明:ECCA算法降低性能较差的一般节点和恶意节点对区块共识效率的影响,提高交易吞吐量,降低平均交易时延和平均节点通信开销。
  • 图  1  网络整体结构示意图

    图  2  ECCA算法原理

    图  3  200个节点的初始分布图

    图  4  节点信用值趋势图

    图  5  信用值模型参数对交易吞吐量的影响

    图  6  节点投票权重对交易吞吐量的影响

    图  7  节点数量对交易吞吐量的影响

    图  8  节点数量对平均交易时延的影响

    图  9  节点数量对平均节点通信开销的影响

    图  10  恶意节点比例对查准率的影响

    图  11  恶意节点比例对查全率的影响

    表  1  面向车联网异构节点的区块链高效一致性共识算法(ECCA)算法流程

     输入: 网络中节点的基本信息
     输出: 网络对车联网数据的区块共识结果
     (1) $\gamma $=60; $\kappa $=60; $\theta $=180; $\upsilon $=0.01; $\sigma $=2; ···;
     (2) while 1
     (3) if 当前不是第一次区块共识 then
     (4) 各区域根据前一次区块共识结果执行奖惩机制;
     (5) end
     (6) 各区域将各节点的累积表现分转换为累积信用值,并通过
       FCM聚类方法进行信用等级划分;
     (7) if各区域中验证节点数量小于下限阈值${\vartheta _{1}}$或各区域中验证节
       点数量大于上限阈值${\vartheta _{2}}$ then
     (8) 该区域执行节点身份变更机制,及时调整区域内节点身份;
     (9) end
     (10) if 事务范围只在单个区域内部 then
     (11) 该区域内部的全部验证节点选为参与区块共识的节点;
     (12) else
     (13) 多区域内的全部验证节点选为参与区块共识的节点;
     (14) end
     (15) 参与区块共识的验证节点通过可通信列表与节点信任等
        级,确定其可信任节点列表;
     (16) 参与区块共识的验证节点结合节点的信用等级权重交易,
        统计投票结果,确定交易集共识结果;
     (17) 参与区块共识的验证节点进行区块验证共识;
     (18) if 事务范围只在单个区域内部 then
     (19) 将区块写入到该区域从链;
     (20) else
     (21) 将区块写入全局主链;
     (22) end
     (23) end
    下载: 导出CSV
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出版历程
  • 收稿日期:  2020-12-18
  • 修回日期:  2021-07-17
  • 网络出版日期:  2021-07-30
  • 刊出日期:  2022-01-10

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