PBFT Consensus Algorithm Optimization Scheme Based on Vague Sets and Credit Rating

Many countries and enterprises consider blockchain technology as an important support for digital economy and technological innovation. Consensus algorithm is the key to achieving data information consistency in blockchain networks. At present, one of the most widely used voting consensus algorithms is the Practical Byzantine Fault Tolerant Algorithm (PBFT). However, this algorithm has some problems, such as high communication complexity, low consensus efficiency, and single main node selection method. This paper proposes an optimization scheme of the PBFT consensus algorithm according to Vague sets and credit rating to address these issues. This algorithm introduces Vague sets to boost the voting efficiency in consensus, balances the influence of positive and negative votes of nodes, and provides a more reasonable evaluation standard for the behavior of nodes, which is used as the basis for selecting the master node. Quantify node points again and select consensus nodes to optimize consensus efficiency. If there are Malicious nodes in the consensus network, the consensus node set is dynamically updated through the elimination mechanism. Finally, through theoretical and experimental analysis, it has been proven that the optimization scheme has meaningful improvements in both security and performance.