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面向物联网的改进PBFT共识算法

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随着物联网的发展,高效的共识算法是区块链技术应用于物联网的关键.针对实用拜占庭容错(practical Byzantine fault tolerance,PBFT)算法在物联网场景中通信次数多、未考虑共识功耗、共识时延高等问题,本文提出了一种基于二分K均值算法的改进PBFT共识算法(binary K-means practical Byzantine fault tolerance algorithm,BK-PBFT).首先,获取节点地理坐标并计算节点综合评价值,通过二分K均值算法将节点划分为一个双层多中心聚类集群.然后,先在下层集群再在上层集群对区块进行PBFT共识.最后,集群验证执行并存储区块,完成共识.此外,本文证明了当节点均匀分布在每个簇时算法通信次数可以达到最少,以及通信次数最少时的最优聚类数.分析与仿真结果表明,本文算法可以有效减少通信次数、降低共识功耗和共识时延.
Improved PBFT Consensus Algorithm for Internet of Things
With the development of the Internet of Things(IoT),efficient consensus algorithms are the key to applying blockchain technology to the IoT.This study proposes an improved PBFT consensus algorithm based on the binary K-means practical Byzantine fault tolerance algorithm(BK-PBFT)to address the issues of high communication times,lack of consideration for consensus power consumption,and high consensus latency in IoT scenarios.Firstly,it obtains the geographic coordinates of the nodes,calculates the comprehensive evaluation values of the nodes,and divides the nodes into a two-layer multi-center clustering cluster by the binary K-means algorithm.Then,PBFT consensus is performed on the blocks in the lower-level cluster and then in the upper-level cluster.Finally,the cluster validates and stores the blocks to complete the consensus.Additionally,this study proves that the algorithm can achieve the minimum number of communication times when nodes are evenly distributed in each cluster,and obtain the optimal cluster number under the least communication times.The analysis and simulation results show that the proposed algorithm can effectively reduce communication times,consensus power consumption,and consensus latency.

Internet of Things(IoT)blockchainpractical Byzantine fault tolerance(PBFT)clusteringcomprehensive evaluation valuepower consumption

叶博文、贾小林、顾娅军

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西南科技大学计算机科学与技术学院射频识别与物联网实验室,绵阳 621010

绵阳市移动物联射频识别技术重点实验室,绵阳 621010

物联网 区块链 实用拜占庭容错 聚类 综合评价值 功耗

国家自然科学基金面上项目四川省自然科学基金四川省重点研发计划四川省教育厅教学改革项目

6147136062022NSFSC05482020YFS0360JG2021-1414

2024

10.15888/j.cnki.csa.009455

计算机系统应用
中国科学院软件研究所

计算机系统应用

CSTPCD
影响因子：0.449
ISSN：1003-3254
年,卷(期)：2024.33(4)
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