Improvement Research of PBFT Consensus Algorithm Based on Credit This paper analyzes the advantages and disadvantages of the PBFT consensus algorithm and proposes an improved creditbased PBFT consensus algorithm(CPBFT). CPBFT changes the original CS architecture to P2P architecture, reduces the consensus steps, and uses the voting method to elect the master node. In the election process, credit levels and credit coefficient are introduced, so that the probability that each node is elected as the master node is affected by the past behavior, and a reliable master node is elected more probably. Experiments show that compared with the PBFT algorithm, the CPBFT algorithm reduces the amount of data transmission on the network and increases the throughput.

KBucket Based RaftLike Consensus Algorithm for Permissioned Blockchain With the development of blockchain, more and more blockchain types emerge: public blockchain, consortium blockchain and private blockchain. Because of the node trust in some consortium blockchain and private blockchain, a no byzantine fault tolerance algorithm KRaft(KademliaRaft) algorithm with high throughput and high scalability is proposed. KRaft consensus algorithm is a Raftlike consensus algorithm that preserves the logic of part of Raft consensus algorithm. It optimized leader election and consensus process of the Raft consensus algorithm through the established KBucket node relationships in the Kademlia protocol, improved leader election speed and throughput. Firstly, the KRaft algorithm uses the Kbucket established by Kademlia protocol to achieve stable and efficient leader election process for the candidate node split vote problem and the low voting efficiency caused by the increase of the Follower node in the Raft algorithm. Secondly, aiming at the low efficiency and load imbalance of the leader singlenode log replication in the Raft algorithm consensus process, a parallel log replication scheme with multiple candidate nodes for balancing the leader node load is proposed to improve the throughput and the scalability of the algorithm. Finally, as a Raftlike consensus algorithm, KRaft consensus algorithm satisfied the safety and liveness requirements of Raft consensus algorithm. KRaft consensus algorithm and Raft consensus algorithm were evaluated with local cluster simulation. The experimental results show that the KRaft consensus algorithm has a 41% improvement in transaction throughput and has a 67% improvement in the leader election speed.