An improved algorithm for practical byzantine fault tolerance to large-scale consortium chain

Consortium chain can better combine blockchain technology with market business, so it is adopted by all walks of life and develops at a large scale. Practical Byzantine Fault Tolerance (PBFT) is more suitable for consortium chain, which are partially decentralized, resistant to Byzantine nodes and strong consistency. However, the limited network scale that PBFT can support is not conducive to the large-scale development of consortium chain. Based on the analysis of the working principle and consensus mechanism of PBFT, this study proposed an al-gorithm to improve PBFT: feature grouping and credit optimization Byzantine Fault Tolerance (FCBFT). In this algorithm, a feature grouping model is proposed to optimize the node structure of large-scale consortium chain, which divides large-scale network nodes into different institutions to form independent consensus groups by feature grouping. On this basis, a reputation score reward mechanism is proposed to improve the consensus efficiency of large-scale consortium chains. It introduces a reputation score calculation formula to select high-reputation primary nodes. At the same time, a replacement cycle is established to replace high-reputation nodes with low-reputation nodes, so as to optimize the consensus efficiency of the consortium chain. The experimental results show that FCBFT has shorter delay and higher throughput (TPS) than PBFT, which becomes more obvious as the number of nodes increases. After the number of nodes ex-ceeds the threshold, the TPS of PBFT drops rapidly, while FCBFT can maintain high efficiency and stability. FCBFT's block generation speed is higher than PBFT, and its relative growth rate has steadily increased.

Automated summary

Consortium chains, which combine blockchain technology with market business, have adopted the Practical Byzantine Fault Tolerance (PBFT) algorithm for its partial decentralization, resistance to Byzantine nodes, and strong consistency. However, PBFT's limited network scale hinders the large-scale development of consortium chains. To address this issue, this study proposes an algorithm called Feature Grouping and Credit Optimization Byzantine Fault Tolerance (FCBFT) to improve PBFT. FCBFT optimizes the node structure of large-scale consortium chains through feature grouping and introduces a reputation score reward mechanism to enhance consensus efficiency. Experimental results demonstrate that FCBFT outperforms PBFT with shorter delay and higher throughput, maintaining high efficiency and stability even with an increasing number of nodes.