Cloud-Based Data Fabric Architectures for National Healthcare Interoperability

Main Article Content

Ganesh Pambala

Abstract

Cloud-based services are revolutionizing storage and processing, breaking the strong coupling between applications, data, and infrastructures within a single organization. Different components can now be deployed in different geographic areas, in a flexible and cost-effective manner. A cloud-based architecture for data virtualization, sensitive-data-oriented, based on a fabric model, is presented. The architecture optimizes operational and system-recovery costs by leveraging a cloud resources-market-driven processing environment. A sensitive-data protection mechanism prevents sensitive data from being exposed even during data re-use. A system-cache approach based on a monitoring and statistical model mechanism improves system utilization and performance by offloading data from the system cache to cloud storage. Concepts, principles, phases, and building blocks of the fabric support any type of resource and information service from the cloud, and any resource-market-driven virtualization requirements that improve application-provisioning flexibility and processing cost.


The presentation of National Cloud Platform for Data Sharing shows that Public and Private sectors maintain distributed data resources in Taiwan, but most national data cannot be integrated and shared easily, due to different forms, contents, and access mechanisms. Recently, strategy of Cloud Computing was proposed to solve resource-usage optimization and fault-tolerant problems. A Cloud Platform connecting the Information-resource-provide agencies by Cloud links is developed, so that their resources can be shared without unnecessary data-refining and –duplication processes. The platform optimizes last-mile data-sharing processes for data consumers and build a Cloud Sharing Marketplace for Information Resources.

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How to Cite

Cloud-Based Data Fabric Architectures for National Healthcare Interoperability. (2022). International Journal of Research Publications in Engineering, Technology and Management (IJRPETM), 5(6), 7846-7862. https://doi.org/10.15662/IJRPETM.2022.0506019

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