A Customized Software Defined Healthcare Infrastructure and Decentralized Computing

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Deepa Jeevaraj


Intelligent city progress is pushing major healthcare developments, the world's most significant sector. Particularly growing expectations for all-round, preventive and customised health services for the population at lower risk and prices. The potential healthcare needs could be fulfilled by mobile cloud computing allowing patient data capturing and processing anywhere, wherever. Network congestion, bandwidth and trust are therefore among the many obstacles that impede future healthcare. This essay provides an omnipresent healthcare platform that incorporates advanced computation, deep learning, high-performance information systems (HPC) and the Internet of Things (IoT) to solve the problems listed above. The architecture allows for better network coverage efficiency with its three core components and four layers. Profound learning, big data and HPC are used to forecast network traffic and in order to refine data speeds, datacache and path decisions using cloud and network layers. Traffic flow application protocols are classified to help serve the communications needs of applications and allow the network layer to detect suspicious traffic and irregular data. The clustering of various data types from the same programme protocols is used for recognition. On the basis of the architecture, a proof-of-concept method was created. The architectural criteria for the proposed framework are calculated by means of a comprehensive literature review. The framework is comprehensive, including the three components and the four layers. Algorithms are identified. The healthcare infrastructure is analysed using three commonly used databases.


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