In response to the problems of the practical Byzantine fault-tolerant algorithm (PBFT), such as random selection of master nodes and poor scalability, a CART-based PBFT optimization algorithm is proposed, namely the C-PBFT algorithm. First, the introduction of weighted impurity variables improves the CART algorithm, overcomes the mutual influence of attributes between nodes, and improves the classification accuracy. Secondly, through the point grouping mechanism, the nodes are divided into three types: consensus nodes, candidate nodes, and alternate nodes, which are dynamically adjusted based on node behavior to ensure the reliability of consensus nodes. Finally, the voting weight is introduced into the consensus node, and the consensus is reached by using the voting weight exceeding the threshold, which reduces the message transmission in the blockchain network and improves the efficiency of the algorithm operation. The experimental results show that the improved consensus algorithm has better performance in terms of delay, throughput, and fault tolerance and reduces the frequent switching of views caused by the failure of the master node.
This study proposes an improved Byzantine fault-tolerant consensus RB-BFT based on the reputation model to address the problems of low reliability of primary nodes and high communication complexity in the practical Byzantine algorithm (PBFT). First, this algorithm establishes a dynamic reputation model of nodes to distinguish honest and malicious nodes in the system, lowering the likelihood of malicious nodes being chosen as primary nodes and increasing the dependability of primary nodes. Second, the algorithm introduces supervisory nodes for information supervision while reducing the centrality of the system. Finally, this algorithm improves the consistency protocol of the PBFT algorithm by optimizing the process of mutual communication between nodes in the preparation and commitment phases, which reduces the algorithm communication complexity from O(n2) to O(n). Theoretical and practical studies reveal that the RB-BFT algorithm enhances performance and reliability greatly.
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