An Efficient Supply Chain Traceability Architecture Based on Blockchain and a Dynamic-Credit PBFT Consensus Algorithm

Dong Wang, Xiang Huang, Zhanpeng Jiang, Mingyi Wang, Hongying Zhou

Abstract


In the context of global economic integration, supply chains are becoming increasingly complex and volatile. Traditional traceability systems are difficult to meet the requirements of large-scale data processing, tamper resistance, and scalability. To this end, a supply chain traceability system based on blockchain and improved Practical Byzantine Fault Tolerance consensus algorithm is proposed. The system optimizes the consensus process by introducing credit and voting mechanisms, improving the model performance under high-frequency trading and malicious attacks. Meanwhile, a decentralized architecture combining the blockchain technology and an improved PBFT algorithm for fast consistency model is designed. A supply chain traceability mechanism including data layer, network layer, consensus layer, contract layer, and view layer is constructed. The experiment was implemented on the Ethereum simulation platform and tested on 30 nodes, with metrics including throughput, transaction latency, view switching time, etc. Compared with GC-PBFT and LC-PBFT, IPBFT had an average throughput increase of 8.5%, transaction latency reduction of 12.7%, and fault tolerance increase of 5.3%. In terms of cost-effectiveness, the annual operation and maintenance cost of the proposed supply chain traceability system was about 60,000 RMB, and the upgrade and expansion cost was about 120,000 RMB, which was significantly reduced compared to traditional systems. The product recall rate decreased from 5.2% to 2.1%, which not only improved economic efficiency, but also enhanced system reliability. The research results provide new technological solutions for transparent management and traceability construction of complex supply chains, which have significant theoretical value and practical application significance.

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References


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DOI: https://doi.org/10.31449/inf.v49i31.11784

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