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OpenHealthQ: OpenFlow based QoS management of Healthcare Data in a Software-Defined Fog environment
IEEE International Conference on Communications (ICC) ; 2021.
Article in English | Web of Science | ID: covidwho-1562186
ABSTRACT
With the incorporation of Internet of Things (IoT) in healthcare systems immense new possibilities have emerged in the modern healthcare services. In recent times where people around the globe are suffering from the Covid-19 pandemic, providing remote healthcare services maintaining necessary social distancing through e-Healthcare has become an urgent priority. e-Healthcare services like patient's real-time health monitoring, exchange of electronic health reports, tele-consultation, remote surgery etc. require reliable and timely delivery of data and responses. To provide for such critical requirements it is essential to prioritize the forwarding of different types of data varies based on their throughput requirements and the delay sensitivities. In this paper, we study the network Quality of Service (QoS) control mechanism for e-Health services using the Software-Defined Networking (SDN) approach in a Fog based Healthcare Environment. We distinguish the data generated from various types of devices into priority classes looking at their priorities, throughput and privacy requirements in the application. Hence, we propose, OpenHealthQ, an OpenFlow based traffic shaping model using OpenFlow Queues to handle the healthcare data. OpenHealthQ provides a secure, on-demand and low-cost access to Healthcare 4.0's most demanding computing infrastructure in a distributed cloud architecture with SDN based fog nodes at the network's edge. Experimental studies show that OpenHealthQ is capable of reducing response time of the end host and significant increase in network throughput compared to the Best-Effort (BE) approach.
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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: IEEE International Conference on Communications (ICC) Year: 2021 Document Type: Article

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Full text: Available Collection: Databases of international organizations Database: Web of Science Language: English Journal: IEEE International Conference on Communications (ICC) Year: 2021 Document Type: Article