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HiCH: Hierarchical Fog-Assisted Computing Architecture for Healthcare IoT

Authors:

Arman Anzanpour,

Amir M. Rahmani,

Tapio Pahikkala,

Marco Levorato,

Pasi Liljeberg,

Nikil DuttAuthors Info & Claims

ACM Transactions on Embedded Computing Systems (TECS), Volume 16, Issue 5s

Article No.: 174, Pages 1 - 20

https://doi.org/10.1145/3126501

Published: 27 September 2017 Publication History

Abstract

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).

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Cited By

El-Gayar OBojja GAmbati LBoit JNawar N(2024)The Impact of the Internet of Things in Healthcare DeliveryImpact of Digital Solutions for Improved Healthcare Delivery10.4018/979-8-3693-5237-3.ch002(35-100)Online publication date: 18-Oct-2024
https://doi.org/10.4018/979-8-3693-5237-3.ch002
Batra ISom S(2024)Architecture, Framework, and Models for Edge-AI in HealthcarePractical Applications of Data Processing, Algorithms, and Modeling10.4018/979-8-3693-2909-2.ch004(44-56)Online publication date: 14-Jun-2024
https://doi.org/10.4018/979-8-3693-2909-2.ch004
Singhal CWu YMalandrino FLevorato MChiasserini C(2024)Resource-aware Deployment of Dynamic DNNs over Multi-tiered Interconnected SystemsIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621218(1621-1630)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOM52122.2024.10621218
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Index Terms

HiCH: Hierarchical Fog-Assisted Computing Architecture for Healthcare IoT

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Published In

cover image ACM Transactions on Embedded Computing Systems

ACM Transactions on Embedded Computing Systems Volume 16, Issue 5s

Special Issue ESWEEK 2017, CASES 2017, CODES + ISSS 2017 and EMSOFT 2017

October 2017

1448 pages

ISSN:1539-9087

EISSN:1558-3465

DOI:10.1145/3145508

Editor:
Sandeep K. Shukla
Indian Institute of Technology, India

Issue’s Table of Contents

Copyright © 2017 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 27 September 2017

Accepted: 01 June 2017

Revised: 01 June 2017

Received: 01 April 2017

Published in TECS Volume 16, Issue 5s

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Cited By

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https://doi.org/10.4018/979-8-3693-5237-3.ch002
Batra ISom S(2024)Architecture, Framework, and Models for Edge-AI in HealthcarePractical Applications of Data Processing, Algorithms, and Modeling10.4018/979-8-3693-2909-2.ch004(44-56)Online publication date: 14-Jun-2024
https://doi.org/10.4018/979-8-3693-2909-2.ch004
Singhal CWu YMalandrino FLevorato MChiasserini C(2024)Resource-aware Deployment of Dynamic DNNs over Multi-tiered Interconnected SystemsIEEE INFOCOM 2024 - IEEE Conference on Computer Communications10.1109/INFOCOM52122.2024.10621218(1621-1630)Online publication date: 20-May-2024
https://doi.org/10.1109/INFOCOM52122.2024.10621218
Mullick ASenguptta S(2024)Machine Learning-Based Analysis of IoT Healthcare Data- A Review of Contemporary Research2024 International Conference on Computer, Electrical & Communication Engineering (ICCECE)10.1109/ICCECE58645.2024.10497422(1-9)Online publication date: 2-Feb-2024
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Raman RVerma MKumar VRastogi SPillai BMeenakshi R(2024)Fog Computing Integrated with and Blockchain Technology for Accurate Disease Prediction2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE)10.1109/ICACITE60783.2024.10616443(677-682)Online publication date: 14-May-2024
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