全球卫生危机中的可扩展数据管理:利用区块链技术

IET Blockchain Pub Date : 2024-08-01 DOI:10.1049/blc2.12084
Sakib Al Jobaid, Upama Kabir, Mosarrat Jahan
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引用次数: 0

摘要

有效的数据管理对于应对任何健康危机至关重要。有了适当的数据管理协议,利益相关者可以在充满挑战的时期迅速适应不断变化的环境。最近发生的COVID-19大流行等事件明确显示了其重要性。开展疾病监测、采取预防措施和制定政策以控制局势至关重要。由于这一过程涉及大量数据增长,因此需要高度的监督和控制。监控这些庞大的敏感数据面临多方面的限制,即数据篡改、侵犯隐私和集中数据管理。针对这些挑战,我们提出了一种创新的基于区块链的可扩展数据管理方案。然而,区块链无法在大型生态系统中扩展,因为它将所有内容存储在每个参与节点中。这项工作通过提出一种轻量级解决方案来解决这个缺点,该解决方案将节点分组到集群中,从而减少内存和处理开销。此外,它采用脱链技术来减少每个节点的内存负载,从而减少整个网络的内存负载。实验结果表明,每个节点和整个网络的存储空间分别减少了85%和94%,事务处理时间减少了87%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Scalable data management in global health crises: Leveraging blockchain technology

Scalable data management in global health crises: Leveraging blockchain technology

Effective data management is crucial in navigating any health crisis. With proper data management protocols in place, stakeholders can swiftly adapt to evolving circumstances during challenging times. A recent event like the COVID-19 pandemic has unequivocally revealed its significance. It is essential to conduct disease surveillance, practice preventive measures, and devise policies to contain the situation. As the process involves massive data growth, it demands an acute level of oversight and control. Monitoring this vast sensitive data faces multifaceted limitations, namely data tampering, breach of privacy, and centralized data stewardship. In response to these challenges, we propose an innovative blockchain-enabled scalable data management scheme in light of the COVID-19 scenario. However, blockchain cannot scale in a large ecosystem due to storing all contents in every participating node. This work addresses this shortcoming by proposing a lightweight solution that groups nodes into clusters, resulting in less memory and processing overhead. Moreover, it adopts an off-chaining technique to reduce the memory load of every node and, thereby, the entire network. The experimental results demonstrate that it attains approximately 85% and 94% storage reduction per node and the whole network, respectively, and an 87% reduction in transaction processing time.

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