Grouped Byzantine Fault-Tolerant Consensus Mechanism Based on Node Behaviour Analysis
Boyu Shan, Tianhao Gao, Lihua Song, Youwen Cui · 2025
With the wide application of block-chain technology, Practical Byzantine Fault Tolerance (PBFT) algorithm, as a classical consensus mechanism, has attracted attention due to its advantages in tolerating Byzantine faults. However, the PBFT algorithm faces challenges in practical applications such as Byzantine nodes may be selected as master nodes, high system communication overheads, and long consensus latency. In order to solve these problems, this paper proposes a grouped Byzantine fault-tolerant consensus mechanism based on node behavioral analysis, named ABA-PBFT.Firstly, the mechanism constructs a node voting weight evaluation model by introducing a dynamic analysis of node behavior, and accumulating behavioral data based on node performances in the consensus process. Second, based on the performance values of the nodes, the nodes are divided into high-performance group (HPG), medium-performance group (MPG), and low-performance group (LPG), and the master node is randomly selected from the HPG group. Finally, according to the node grouping, the PBFT full consensus process is optimized in stages to reduce the communication overhead and consensus delay. Through simulation experiments, it is verified that ABA-PBFT significantly outperforms the traditional PBFT algorithm in key performance indicators such as consensus latency, throughput, communications overhead, which effectively reduces the risk of the system suffering from the Byzantine attack and enhances the security and stability of the block-chain system. The research in this paper provides a new idea and method for the optimization of block-chain consensus mechanism, which has a wide application prospect.