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A Scalable Multicloud Storage Architecture for Cloud-Supported Medical Internet of Things
IEEE Internet of Things Journal ( IF 9.515 ) Pub Date : 2019-10-08 , DOI: 10.1109/jiot.2019.2946296
Ronghui Cao; Zhuo Tang; Chubo Liu; Bharadwaj Veeravalli

Nowadays, cloud-supported Internet of Things (Cloud-IoT) has been broadly deployed in smart medical systems, where the limitations of Internet of Things (IoT)-associated medical devices in terms of data access, storage, scalability, and computing are solved through the use of cloud computing architectures. However, with the rapid development of medical equipment and the increasing number of medical devices, it will be extremely difficult to program or manage such an expanding and massive medical IoT system in traditional single-cloud platforms. In this article, we design and implement a multicloud framework for building OpenStack-based platform for medical IoT, referred to as the tri-storage failure recovery system (Tri-SFRS). To implement Tri-SFRS, we combine several techniques to achieve this reduction in effort, including a multicloud cascading architecture, a low-overhead native testing framework, a medical data storage-backup mechanism, and snapshot-volume cascaded operations for b-ultrasonic data. Tri-SFRS is also able to simultaneously enable resource management specialization. Tri-SFRS has been designed as a native component in the OpenStack platform, and it demonstrates the degree of native OpenStack multicloud platform management by our proposed cascading framework. Comparing with the traditional single-cloud OpenStack platform, Tri-SFRS can reduce the resource-request processing latency from B ultrasonic machines by up to 20%. Our experiments also demonstrate the broad applicability of Tri-SFRS.
更新日期:2020-03-16

 

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