基于可编辑区块链的农产品供应链追溯高效存储查询模型

High-efficiency storage and retrieval model to trace agri-food supply chain using redactable blockchain

基于区块链的农产品追溯系统可有效解决农产品追溯的信任问题。然而,区块链的不可篡改性和全冗余存储导致了区块链节点存储数据量的持续增加,提高了区块链设备的门槛,限制了农产品区块链追溯系统的大规模落地应用。针对农产品区块链追溯系统的高存储量问题,该研究提出了一种基于可编辑区块链的农产品供应链追溯高效存储查询模型。首先,针对农产品追溯数据的周期特性,总结了农产品供应链追溯信息生命周期。其次,通过卸载超出生命周期的追溯数据降低数据存储量,研究农产品可编辑区块链存储模型。最后,通过计数布隆过滤器降低了农产品可编辑区块链数据卸载后假阳率高的问题,提高了农产品可编辑区块链追溯系统的查询效率。试验结果表明,在系统运行60个月时,模型的存储量为传统农产品区块链追溯系统的48.70%。当区块数据量为1 000条,数据卸载量为30%时,模型的假阳率较传统模型下降了21个百分点,数据查询效率提高了19.02%。该研究为农产品区块链追溯系统的规模化落地应用提供了解决方案。

A blockchain-based agri-food traceability can be expected to remedy the inherent trust within agri-food supply chains.However,the immutable and redundant nature of traditional blockchain storage has posed formidable challenges,particularly on the scalability of data storage for blockchain nodes.Agri-food traceability has also been limited to historically impede the widespread adoption in recent years.In this study,an efficient storage and query model was introduced to specifically design for the agri-food supply chain traceability,in order to leverage the concept of a redactable blockchain.The cyclical nature of agri-food traceability data was examined to form the model.The lifecycle of the supply chain was analyzed for the agri-food products.The opportunities were identified for streamline data management.A key innovation involved the strategic offloading of traceability data over the lifecycle.Storage resources were optimized to preserve the essential traceability functionalities.The information remained accessible throughout the supply chain journey.Furthermore,the counter Bloom filter was incorporated to enhance the operational efficiency of data offloading.The high false positive rates were reduced for the data manipulation in redactable blockchains.False positives were effectively reduced to significantly enhance the overall query efficiency of the agri-food traceability system,thereby facilitating expedient access to accurate supply chain information.A counter Bloom filter was operated to leverage the probabilistic hashing techniques.The large datasets were efficiently managed and queried to minimize the occurrence of false positives.A robust mechanism was translated to verify the accuracy of traceability information post-data offloading in the context of the agri-food traceability system.A compact representation of recently offloaded data was maintained to employ the efficient hash functions.The counter Bloom filter effectively reduced the likelihood of mistakenly,in order to identify non-existent data during queries.The efficacy of the improved model was underscored to validate the comprehensive empirical data.The extensive experiment was conducted over a simulated 60-month operational period.Notably,the better performance of the model was achieved with a remarkable 48.70%reduction in storage volume,compared with the conventional agri-food blockchain traceability systems.This reduction was attributed to the strategic lifecycle-based data management,and the storage was optimized without compromising data integrity.The improved model was often verified in a simulated scenario involving 1000 block records and a 30%data offloading rate.There was a notable 21 percentage points decrease in the false positive rates,indicating the efficacy of the integrated counter Bloom filter with the data accuracy post-offloading.Moreover,there was a commendable 19.02%enhancement in the data query efficiency,compared with the traditional approaches.The compelling solution fully met the operational demands of large-scale agri-food supply chain environments.The blockchain-based agri-food traceability was presented to facilitate the widespread deployment.A significant advancement was achieved in data integrity with the pragmatic storage and query optimizations in the field.Beyond technical innovation,a robust framework was offered to enhance transparency,accountability,and consumer confidence across agri-food supply chains.Looking ahead,the scalability and adaptability of the improved model can promise to support the diverse applications within the agri-food sector.Product authenticity and quality assurance can be enhanced to enable efficient recalls and regulatory compliance.As the blockchain continues to evolve,insights can be gained to pave the way for future advancements in agri-food traceability and industry-wide transformation toward a more resilient and sustainable supply chain.