HiCH: Hierarchical Fog-Assisted Computing Architecture for Healthcare IoT
HiCH: Hierarchical Fog-Assisted Computing Architecture for Healthcare IoT
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DOI：
10.1145/3126501
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发表时间：
2017-10-01
影响因子：
2
通讯作者：
Dutt, Nikil
中科院分区：
文献类型：
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作者：
Azimi, Iman;Anzanpour, Arman;Dutt, Nikil
物联网（IoT）范式为远程健康监测系统带来了巨大的希望。由于它们的生命或任务关键性质，这些系统需要提供高水平的可用性和准确性。一方面，集中式基于云的物联网系统缺乏可靠性、准时性和可用性（例如，在互联网连接缓慢或不可靠的情况下），另一方面，由于边缘节点的计算能力有限，将数据分析完全外包给网络边缘可能导致准确性和适应性水平降低。在本文中，我们通过为基于物联网的健康监测系统提出分层计算架构high来解决这些问题。该系统的核心组件是1)一种适合分层划分和执行基于机器学习的数据分析的新型计算架构，2)一种能够根据患者病情自主调整系统的闭环管理技术。high从雾和云计算提供的功能中受益，并为医疗保健物联网系统引入了量身定制的管理方法。我们通过对心血管疾病（cvd）患者心律失常检测的连续远程健康监测案例研究进行综合绩效评估和评价，证明了HiCH的有效性。
The Internet of Things (IoT) paradigm holds significant promises for remote health monitoring systems. Due to their life-or mission-critical nature, these systems need to provide a high level of availability and accuracy. On the one hand, centralized cloud-based IoT systems lack reliability, punctuality and availability (e.g., in case of slow or unreliable Internet connection), and on the other hand, fully outsourcing data analytics to the edge of the network can result in diminished level of accuracy and adaptability due to the limited computational capacity in edge nodes. In this paper, we tackle these issues by proposing a hierarchical computing architecture, HiCH, for IoT-based health monitoring systems. The core components of the proposed system are 1) a novel computing architecture suitable for hierarchical partitioning and execution of machine learning based data analytics, 2) a closed-loop management technique capable of autonomous system adjustments with respect to patient's condition. HiCH benefits from the features offered by both fog and cloud computing and introduces a tailored management methodology for healthcare IoT systems. We demonstrate the efficacy of HiCH via a comprehensive performance assessment and evaluation on a continuous remote health monitoring case study focusing on arrhythmia detection for patients suffering from CardioVascular Diseases (CVDs).