CG-PBFT:基于信用分组的高效 PBFT 算法

Juan Liu, Xiaohong Deng, Wangchun Li, Kangting Li
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引用次数: 0

摘要

实用拜占庭容错(PBFT)算法因其容错性、高效性和可用性等优良特性,已成为区块链的主流共识算法。然而,目前的拜占庭容错算法存在主节点选择安全性不足、共识过程中通信开销大、网络延迟等问题。针对这些问题,我们设计了一种基于信用分组的新型高效拜占庭容错算法,称为 CG-PBFT。首先,我们提出了一种新的信用评估模型来获取节点的信用值,并引入了一种优化的三向快速排序算法,将节点分为主节点组、共识节点组和观察节点组,它们具有不同的权限。观察节点组中的节点被限制参与共识,从而减少了通信开销,提高了共识效率。其次,我们提出了一种基于投票机制的主节点优化选择方法,即由共识节点组和观察节点组投票产生主节点,这降低了恶意节点充当主节点的概率,提高了主节点选择的安全性。最后,设计了节点组之间的身份转换机制,对不同组内节点的实际行为给予信用奖惩,从而保持对节点参与适当系统行为的激励,提高节点的工作积极性。实验仿真结果表明,与现有的PBFT算法相比,CG-PBFT算法的平均吞吐量提高了51.3%,平均时延降低了64.5%,大大提高了系统的运行效率,更适合应用于联合体区块链场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
CG-PBFT: an efficient PBFT algorithm based on credit grouping
Because of its excellent properties of fault tolerance, efficiency and availability, the practical Byzantine fault tolerance (PBFT) algorithm has become the mainstream consensus algorithm in blockchain. However, current PBFT algorithms have problems such as inadequate security of primary node selection, high communication overhead and network delay in the process of consensus. To address these problems, we design a novel efficient Byzantine fault tolerance algorithm based on credit grouping, called CG-PBFT. First, we propose a new credit evaluation model to obtain nodes’ credit values and introduce an optimized three-way quick sorting algorithm to divide nodes into the master-node group, the consensus-node group and the observation-node group, which have different privileges. The nodes in the observation-node group are restricted from participating in consensus, which reduces the communication overhead and improves consensus efficiency. Second, we propose an optimized selection method for the primary node based on a voting mechanism whereby the consensus-node group and observation-node group vote to produce the primary node, which reduces the probability of malicious nodes acting as the primary node and improves the security of primary node selection. Finally, the identity conversion mechanism between node groups is designed, and the actual behavior of nodes within different groups is given credit rewards or punishment, so as to keep an incentive for nodes to participate in appropriate system behavior and improve the working enthusiasm of nodes. The experimental simulation results show that compared with existing PBFT algorithms, the CG-PBFT algorithm improves the average throughput by 51.3% and reduces the average delay by 64.5%; it greatly improves the operating efficiency of the system and can be more suitable for application in the consortium blockchain scenarios.
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