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A Novel Cost-Efficient Framework for Critical Heartbeat Task Scheduling Using the Internet of Medical Things in a Fog Cloud System

机译：在雾云系统中使用医疗物联网进行关键心跳任务调度的新型经济高效框架

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摘要

Recently, there has been a cloud-based Internet of Medical Things (IoMT) solution offering different healthcare services to wearable sensor devices for patients. These services are global, and can be invoked anywhere at any place. Especially, electrocardiogram (ECG) sensors, such as Lead I and Lead II, demands continuous cloud services for real-time execution. However, these services are paid and need a lower cost-efficient process for the users. In this paper, this study considered critical heartbeat cost-efficient task scheduling problems for healthcare applications in the fog cloud system. The objective was to offer omnipresent cloud services to the generated data with minimum cost. This study proposed a novel health care based fog cloud system (HCBFS) to collect, analyze, and determine the process of critical tasks of the heartbeat medical application for the purpose of minimizing the total cost. This study devised a health care awareness cost-efficient task scheduling (HCCETS) algorithm framework, which not only schedule all tasks with minimum cost, but also executes them on their deadlines. Performance evaluation shows that the proposed task scheduling algorithm framework outperformed the existing algorithm methods in terms of cost.
机译：最近，已经有了基于云的医疗物联网（IoMT）解决方案，可为患者的可穿戴传感器设备提供不同的医疗服务。这些服务是全局的，可以在任何地方的任何地方调用。特别是，诸如Lead I和Lead II之类的心电图（ECG）传感器需要连续的云服务来实时执行。但是，这些服务是付费的，需要用户降低成本效益的过程。在本文中，本研究考虑了雾云系统中医疗应用的关键心跳成本效益型任务调度问题。目的是以最小的成本为生成的数据提供无所不在的云服务。这项研究提出了一种新颖的基于医疗保健的雾云系统（HCBFS），用于收集，分析和确定心跳医疗应用的关键任务的过程，以最大程度地降低总成本。这项研究设计了一种卫生保健意识，具有成本效益的任务调度（HCCETS）算法框架，该框架不仅以最小的成本调度所有任务，而且在任务的最后期限执行它们。性能评估表明，所提出的任务调度算法框架在成本方面优于现有算法。

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