Research on PBFT consensus algorithm for grouping based on feature trust

• Published in: Scientific reports Vol. 12; no. 1; p. 12515
• Main Authors: Wang, Yong, Zhong, Meiling, Cheng, Tong
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 22-07-2022; Nature Publishing Group; Nature Portfolio
• Subjects: 639/705/117; 639/705/258; 639/705/794; Algorithms; Blockchain; Humanities and Social Sciences; Latency; multidisciplinary; Nodes; Science; Science (multidisciplinary)
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-022-15282-8

The consensus mechanism is the core of the blockchain system, which plays an important role in the performance and security of the blockchain system . The Practical Byzantine Fault Tolerance (PBFT) algorithm is a widely used consensus algorithm, but the PBFT algorithm also suffers from high consensus latency, low throughput and performance. In this paper, we propose a grouped PBFT consensus algorithm (GPBFT) based on feature trust. First, the algorithm evaluates the trust degree of nodes in the transaction process through the EigenTrust trust model, and uses the trust degree of nodes as the basis for electing master nodes and proxy nodes. Then, the algorithm divides the nodes in the blockchain system into multiple groups, and the consensus within each independent group does not affect the other groups, which greatly reduces the communication overhead of the consensus process when the number of nodes in the system is large. Finally, we demonstrate through theoretical and experimental analysis that the GPBFT algorithm has a significant improvement in security and performance.