Dynamic Byzantine Fault-Tolerant Consensus Algorithm with Supervised Feedback Mechanisms

Anqi Li, Yingbiao Yao () and Xin Xu
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Anqi Li: School of Communications Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
Yingbiao Yao: School of Communications Engineering, Hangzhou Dianzi University, Hangzhou 310018, China
Xin Xu: School of Communications Engineering, Hangzhou Dianzi University, Hangzhou 310018, China

Mathematics, 2024, vol. 12, issue 17, 1-21

Abstract: Among the existing consensus algorithms, there are very few low-latency consensus algorithms that can simultaneously take into account node dynamics, fault tolerance, and scalability, and which are applicable to large-scale open scenarios where low latency is required. Therefore, this paper proposes a low-latency scalable dynamic consensus algorithm with high fault tolerance utilizing a combination of layered and threshold signature technologies, known briefly as LTSBFT. Firstly, LTSBFT achieves linear communication complexity through the utilization of threshold signature technology and a two-layer structure. Secondly, the mutual supervision feedback mechanism among nodes enables the attainment of linear complexity for reaching consensus on the faulty upper-layer nodes during the view-change. Lastly, a node dynamic protocol was proposed for the first time to support dynamic changes in the number of nodes during the consensus process. That is to say, consensus can still be reached when the number of nodes dynamically changes without interrupting the client’s request for consensus in the network. The experimental results indicate that LTSBFT exhibits lower communication latency and higher throughput compared to the classic HotStuff and PBFT algorithms. Furthermore, in comparison to double-layer PBFT, the LTSBFT has been demonstrated to have improved fault tolerance.

Keywords: blockchain; consensus; Byzantine fault tolerance; supervised feedback (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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