K-Bucket Based Raft-Like 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(Kademlia-Raft) algorithm with hig...

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Vydané v:2019 IEEE 25th International Conference on Parallel and Distributed Systems (ICPADS) s. 996 - 999
Hlavní autori: Wang, Rihong, Zhang, Lifeng, Xu, Quanqing, Zhou, Hang
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 01.12.2019
Predmet:
Blockchains
Consensus algorithm
Fault tolerance
Fault tolerant systems
Kademlia protocol
permissioned blockchain
Protocols
Raft consensus algorithm
Safety
Scalability
Stability analysis
Throughput
Voting
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Shrnutí: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(Kademlia-Raft) algorithm with high throughput and high scalability is proposed. KRaft consensus algorithm is a Raft-like 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 K-Bucket node relationships in the Kademlia protocol, improved leader election speed and throughput. Firstly, the KRaft algorithm uses the K-bucket 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 single-node 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 Raft-like 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.
DOI:10.1109/ICPADS47876.2019.00152