基于Raft分组的实用拜占庭共识算法

针对现有应用于联盟链的拜占庭容错共识机制可扩展性不足、难以支持大规模网络节点下高效安全共识等问题，采用节点分组策略，提出一种基于Raft聚类分组的实用拜占庭容错共识算法H-PBFT。首先使用混合蛙跳算法结合K-medoids聚类分组策略，将系统中节点聚类形成多个分组；参与主共识集群PBFT共识的节点均为各分组聚类中心节点，各聚类小组内则使用引入监督节点改进的Raft算法进行共识；组内共识机制监督节点的引入使Raft算法具有抗拜占庭的能力。实验研究结果表明，在大规模网络节点环境下，相比于PBFT和Raft，H-PBFT算法提高了容错性能，同时还能够快速高效对节点聚类分组，提高共识效率，降低共识通信开销与复杂度，具有较优的可扩展性，能够更好的在联盟链场景中应用。

Practical Byzantine consensus algorithm based on Raft grouping

Aiming at the problems of the existing Byzantine fault-tolerant consensus mechanism applied to alliance chain, such as insufficient scalability and difficulty to support efficient and secure consensus under large-scale network nodes, this paper proposed a practical Byzantine fault-tolerant consensus algorithm H-PBFT based on Raft clustering grouping by node grouping strategy. Firstly, the shuffled frog leaoing algorithm combined with K-medoids clustering strategy using to cluster nodes in the system into multiple groups participated. The central nodes of each cluster cluster nodes in the PBFT consensus of the main consensus cluster and the Raft algorithm introdued the improved supervision node was used to achieve consensus in each cluster group. Intra-group consensus mechanism supervised the introduction of nodes to make Raft algorithm Byzantine-resistant. Experimental results show that, compared with PBFT and Raft, this algorithm can improve fault tolerance performance in large-scale network node environment, and can also cluster nodes quickly and efficiently, improve consensus efficiency, reduce consensus communication overhead and complexity. This algorithon has better scalability, which can be better applied in alliance chain scenarios.