基于区块链的食品溯源技术研究

doi:10.19788/j.issn.2096-6369.200306

Abstract

Abstract:

Blockchain is naturally suited to food traceability systems because of its credibility and non-tamperability, and its application in the field of food traceability is increasing. However, when blockchains are applied in existing food traceability systems, many problems may arise. These problems include there being too many food traceability scenarios, large blockchain network loads, and long network delays. In response to these problems, we introduce the Interpretative Structural Modeling method layered idea to optimize the traditional Practical Byzantine Fault Tolerance (PBFT) consensus mechanism commonly used in blockchains, in order to improve the performance of existing traceability systems. We construct an explanatory structure model through the transaction relationship between the blockchain nodes, layer the blockchain consensus nodes, establish a layered system of blockchain consensus nodes, and then divide the layered blockchain consensus nodes into blocks. We then divide multiple sub-node clusters participating in the consensus and use multi-center sub-node clusters to implement the PBFT consensus. Finally, the consensus center node submits the consensus result to the block to achieve the overall consensus. The food traceability dataset was collected from the intelligent poultry house jointly established by the Beijing Municipal Bureau of Agriculture and Rural Affairs and the Beijing Animal Husbandry Terminus and the intelligent chicken house monitoring and management platform based on the alliance blockchain through the experimental verification of throughput and consensus time-consuming. The improved practical Byzantine fault-tolerant consensus algorithm realizes the multi-center sub-node cluster hierarchical and block consensus, and solves the network congestion problem in the traditional Practical Byzantine Fault Tolerance algorithm. It also reduces the blockchain network broadcast resource waste, reduces the blockchain consensus communication cost, and ensures the security of the blockchain consensus while improving the efficiency of the food traceability blockchain network communication and consensus.

Key words: food safety, traceability, blockchain, Practical Byzantine Fault Tolerance, Interpretative Structural Modeling

CLC Number:

TP311.13

Min Zuo, Siyu He, Qingchuan Zhang, Shuangshun Yao. Research on Food Source Traceability Technology Based on Blockchain[J].Journal of Agricultural Big Data, 2020, 2(3): 52-60.

Figures/Tables 11

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References 16

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追溯环节	追溯对象	追溯信息
生产环节	原料，添加剂	名称、生产日期、数量、规格、保质期等。
	加工环境	生产地点、责任人员信息、环境信息等。
	产品信息	产品名称、规格、生产日期、保质期等。
仓储环节	仓储环境	仓储地点、责任人员信息、环境信息。
仓储环节	物流信息	物流公司信息、驾驶员信息、车辆信息。
运输环节	运输环境	运输路线、责任人员信息、环境信息。

节点	数量
N_B nodes	10
B nodes	3

Command	N_B nodes	B nodes	Meaning
Create: 10:3	10	3	创建13个节点，B node3个，N_B node10个
Make_b: 1	9	4	有1个N_B node转变为B node
Make_nb: 2	11	2	有2个B node转变为N_B node
Delete: 4:0	7	2	删除4个节点，其中删除的全部是N_B node

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Research on Food Source Traceability Technology Based on Blockchain

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