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An improved PBFT consensus mechanism with trust value evaluation application in the agricultural product trusted traceability system

可追溯性 计算机科学 块链 Byzantine容错 供应链 产品(数学) 架空(工程) 分布式计算 吞吐量 计算机安全 计算机网络 容错 业务 电信 操作系统 几何学 软件工程 数学 营销 无线
作者
Wei Sun,S.C. Wang,Wei Shen,Pengfei Cao,Yan Zhao,Lifeng Xi,Xinlu Liu,Lihua Wang
出处
期刊:Journal of High Speed Networks [IOS Press]
卷期号:29 (4): 321-336
标识
DOI:10.3233/jhs-222077
摘要

Blockchain has the advantages of tamper proof, high reliability and traceability, so it can better support the agricultural product traceability system. However, the agricultural product supply chain has the characteristics of long chain and decentralized production, which makes the application of the combination of blockchain technology and agricultural product traceability have many nodes, large system overhead and other problems. In order to solve the above problems, this paper proposes a Practical Byzantine Fault Tolerance (PBFT) consensus mechanism based on trust value evaluation, and uses this optimization algorithm to propose an architecture model to meet the demand for trusted traceability of agricultural product supply chain, so as to realize the distributed storage and security protection of supply chain data. In order to ensure the effective operation of the blockchain system, this paper studies the consensus mechanism in the blockchain network, designs a trust value evaluation model to calculate the trust value of nodes, and selects trusted nodes to join the consensus group based on the trust value, which ensures the credibility of the consensus nodes. At the same time, the consistency protocol is optimized to reduce the communication overhead in the consensus process. The experimental results show that the consensus mechanism improved in this paper has certain advantages in communication overhead, transaction delay and throughput. Compared with the existing storage model, the model described in this paper has higher security and throughput efficiency, effectively ensures the reliable traceability of data, and can be better applied to the traceability scenario of agricultural product supply chain.
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