RE-BPFT: An Improved PBFT Consensus Algorithm for Consortium Blockchain Based on Node Credibility and ID3-Based Classification
Practical Byzantine Fault Tolerance (PBFT) has been widely used in consortium blockchain systems; however, it suffers from performance degradation and susceptibility to Byzantine faults in complex environments. To overcome these limitations, this paper proposes RE-BPFT, an enhanced consensus algorit...
Saved in:
Main Authors: | , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2025-07-01
|
Series: | Applied Sciences |
Subjects: | |
Online Access: | https://www.mdpi.com/2076-3417/15/13/7591 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Summary: | Practical Byzantine Fault Tolerance (PBFT) has been widely used in consortium blockchain systems; however, it suffers from performance degradation and susceptibility to Byzantine faults in complex environments. To overcome these limitations, this paper proposes RE-BPFT, an enhanced consensus algorithm that integrates a nuanced node credibility model considering direct interactions, indirect reputations, and historical behavior. Additionally, we adopt an optimized ID3 decision-tree method for node classification, dynamically identifying high-performing, trustworthy, ordinary, and malicious nodes based on real-time data. To address issues related to centralization risk in leader selection, we introduce a weighted random primary node election mechanism. We implemented a prototype of the RE-BPFT algorithm in Python and conducted extensive evaluations across diverse network scales and transaction scenarios. Experimental results indicate that RE-BPFT markedly reduces consensus latency and communication costs while achieving higher throughput and better scalability than classical PBFT, RBFT, and PPoR algorithms. Thus, RE-BPFT demonstrates significant advantages for large-scale and high-demand consortium blockchain use cases, particularly in areas like digital traceability and forensic data management. The insights gained from this study offer valuable improvements for ensuring node reliability, consensus performance, and overall system resilience. |
---|---|
ISSN: | 2076-3417 |