Reputation evaluation based fault tolerance consensus algorithm for blockchain network

Shimin Sun; Xiaofan Wang; Aixin Xu; Li Han

doi:10.1117/12.2662662

16 December 2022 Reputation evaluation based fault tolerance consensus algorithm for blockchain network

Shimin Sun, Xiaofan Wang, Aixin Xu, Li Han

Proceedings Volume 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022); 1250049 (2022) https://doi.org/10.1117/12.2662662
Event: 5th International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 2022, Chongqing, China

Abstract

With the development and application of Blockchain technology, some consensus algorithms emerged. Practical Byzantine Fault Tolerance (PBFT), as a type of classic consensus algorithm, has been widely applied in Consortium Blockchain. However, it still has some issues need to be resolved via optimization, such as low node reliability, poor scalability, insufficient dynamics, and frequent view change. To address those problems, this paper proposes a Reputation evaluation-based fault tolerance consensus algorithm, named RPBFT. We introduce a reputation evaluation model based on the service performance and enthusiasm of nodes to participate in consensus. A reward-punishment mechanism is proposed to make nodes with high reliability more likely to participate in block production, which improves the security and reliability of the blockchain. Finally, a two-phase consensus process is presented to achieve a more efficient consensus. The experimental results show that, compared with relevant consensus algorithms, RPBFT is superior in reducing consensus delay and improving communication efficiency.

Citation Download Citation

Shimin Sun, Xiaofan Wang, Aixin Xu, and Li Han "Reputation evaluation based fault tolerance consensus algorithm for blockchain network", Proc. SPIE 12500, Fifth International Conference on Mechatronics and Computer Technology Engineering (MCTE 2022), 1250049 (16 December 2022); https://doi.org/10.1117/12.2662662

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