Abstract
Data management methods using blockchain have the advantages of being traceable and not easy to tamper. Therefore, blockchain is widely used in supply chain finance, credit reporting and other fields. However, in the actual blockchain system application, there are two main problems in the Hyperledger Fabric license alliance chain based on the Practical Byzantine Fault Tolerance (PBFT) consensus mechanism: 1) The non-honesty node acts as the primary node to interfere with the consensus process; 2) The network bandwidth resource consumption caused by the flooded message broadcast of the consensus node is too large. To solve these problems, a blockchain PBFT consensus performance optimization method for fusing C4.5 decision tree is proposed. This method uses the C4.5 decision tree with high model classification accuracy to evaluate the trust degree of the consensus nodes in the blockchain network, and effectively reduces the non-honesty node as the primary node. On this basis, the voting weight is introduced. Consistency verification can be completed only by considering a small number of trusted nodes voting weights, thereby reducing the number of messages broadcasted in the network. The experimental results show that compared with the existing methods, the trust node classification and voting weights of the consensus nodes are improved in the consensus performance of throughput, delay and fault tolerance, and the effectiveness of the proposed method is verified.
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Acknowledgments
This work has been supported by the Major Project of Science and Technology of Yunnan Province under Grant No. 202002AD080002 and No. 2019ZE005.
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Liang, Z., Huang, Y., Guo, Z., Liu, Q., Liu, T. (2020). PBFT Consensus Performance Optimization Method for Fusing C4.5 Decision Tree in Blockchain. In: Zheng, Z., Dai, HN., Fu, X., Chen, B. (eds) Blockchain and Trustworthy Systems. BlockSys 2020. Communications in Computer and Information Science, vol 1267. Springer, Singapore. https://doi.org/10.1007/978-981-15-9213-3_7
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DOI: https://doi.org/10.1007/978-981-15-9213-3_7
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