用于联盟链的非拜占庭容错共识算法

Non-byzantine Fault Tolerance Consensus Algorithm for Consortium Blockchain

随着区块链技术的发展,区块链出现了多种分类,兼顾公有链多中心特点和私有链高性能优势的联盟链成为了我国区块链的发展重心。结合联盟链中存在节点信任的特性,非拜占庭容错共识算法能为联盟链提供更好的性能支持。文中选取Raft共识算法作为研究对象,针对Raft共识算法中Leader节点选举和日志复制过程中的诸多问题,提出了一种可应用于联盟链的非拜占庭容错共识算法——KRaft(Kademlia-Raft)共识算法,该共识算法结合区块链网络层的双层Kademlia路由协议改进了Raft共识算法中的Leader节点选举和日志复制过程。首先,针对Raft共识算法Leader节点选举中存在的多Candidate节点分票和Follower节点增多引发的投票效率问题,KRaft共识算法利用双层Kademlia协议建立的K桶实现了Candidate节点集合内的稳定选举;其次,针对Raft共识算法日志复制过程中Leader节点单节点日志复制过程效率低和节点负载不均的问题,提出了均衡Leader节点负载的多Candidate节点并行日志复制方案,在提升数据吞吐量的同时提升了算法的可拓展性。本地多节点仿真实验的结果表明,KRaft共识算法相较于Raft共识算法,数据吞吐量提升了34.5%,Leader节点选举速度提升了55.6%。

As a consortium blockchain with the multi-center characteristics of public blockchain and the high-performance advantages of private blockchain,it has become the center of development of China.Combined with the characteristics of node trust in the consortium blockchain,non-byzantine fault tolerance consensus algorithm can provide better performance support for the consortium blockchain.By selecting Raft consensus algorithm as the research object,focusing on the leader election and log replication process in the Raft consensus algorithm,this paper proposes a non-byzantine fault tolerance consensus algorithm for consortium blockchain—Kraft(Kademlia-Raft)consensus algorithm.It improves the process of Leader election and log replication in the Raft consensus algorithm by combining the two-layer Kademlia routing protocol.First,in view of the problem of voting efficiency caused by the number of Candidate nodes and the increase of Follower nodes in the Raft consensus algorithm,KRaft consensus algorithm uses K-bucket established by the two-layer Kademlia protocol to realize the stable election in the Candidate node set.Se-con dly,in view of the low efficiency of the single-node log replication process of the Leader in the log replication process of Raft consensus algorithm and the load balance problem on the nodes,a parallel log replication scheme of multiple Candidate nodes is proposed to equalize the load on the Leader node,so as to improve the data throughput and the scalability of the algorithm at the same time.Finally,the local multi-node simulation experiment shows that the data throughput of KRaft consensus algorithm is increased by 34.5%compared with Raft consensus algorithm,the voting speed of Leader node is increased by 55.6%.