Next Article in Journal
Sentiment Analysis of Arabic Tweets Regarding Distance Learning in Saudi Arabia during the COVID-19 Pandemic
Next Article in Special Issue
Security and Privacy for Mobile IoT Applications Using Blockchain
Previous Article in Journal
River Basin Cyberinfrastructure in the Big Data Era: An Integrated Observational Data Control System in the Heihe River Basin
Previous Article in Special Issue
A Scalable Implementation of Anonymous Voting over Ethereum Blockchain
Article

A Scheduling Mechanism Based on Optimization Using IoT-Tasks Orchestration for Efficient Patient Health Monitoring

1
Department of Computer Engineering, Jeju National University, Jeju 63243, Korea
2
Department of IT Convergence Engineering, Gachon University, Seongnam 13120, Korea
3
Department of Computer Science, COMSATS University Islamabad at Attock, Attock 43600, Pakistan
*
Author to whom correspondence should be addressed.
Academic Editor: Ju Wook Jang
Sensors 2021, 21(16), 5430; https://doi.org/10.3390/s21165430
Received: 31 May 2021 / Revised: 2 August 2021 / Accepted: 2 August 2021 / Published: 11 August 2021
(This article belongs to the Special Issue Blockchain for IoT Security, Privacy and Intelligence)
Over the past years, numerous Internet of Things (IoT)-based healthcare systems have been developed to monitor patient health conditions, but these traditional systems do not adapt to constraints imposed by revolutionized IoT technology. IoT-based healthcare systems are considered mission-critical applications whose missing deadlines cause critical situations. For example, in patients with chronic diseases or other fatal diseases, a missed task could lead to fatalities. This study presents a smart patient health monitoring system (PHMS) based on an optimized scheduling mechanism using IoT-tasks orchestration architecture to monitor vital signs data of remote patients. The proposed smart PHMS consists of two core modules: a healthcare task scheduling based on optimization and optimization of healthcare services using a real-time IoT-based task orchestration architecture. First, an optimized time-constraint-aware scheduling mechanism using a real-time IoT-based task orchestration architecture is developed to generate autonomous healthcare tasks and effectively handle the deployment of emergent healthcare tasks. Second, an optimization module is developed to optimize the services of the e-Health industry based on objective functions. Furthermore, our study uses Libelium e-Health toolkit to monitors the physiological data of remote patients continuously. The experimental results reveal that an optimized scheduling mechanism reduces the tasks starvation by 14% and tasks failure by 17% compared to a conventional fair emergency first (FEF) scheduling mechanism. The performance analysis results demonstrate the effectiveness of the proposed system, and it suggests that the proposed solution can be an effective and sustainable solution towards monitoring patient’s vital signs data in the IoT-based e-Health domain. View Full-Text
Keywords: Internet of Things; smart healthcare; remote health monitoring; vital signs monitoring; optimization Internet of Things; smart healthcare; remote health monitoring; vital signs monitoring; optimization
Show Figures

Figure 1

MDPI and ACS Style

Iqbal, N.; Imran; Ahmad, S.; Ahmad, R.; Kim, D.-H. A Scheduling Mechanism Based on Optimization Using IoT-Tasks Orchestration for Efficient Patient Health Monitoring. Sensors 2021, 21, 5430. https://doi.org/10.3390/s21165430

AMA Style

Iqbal N, Imran, Ahmad S, Ahmad R, Kim D-H. A Scheduling Mechanism Based on Optimization Using IoT-Tasks Orchestration for Efficient Patient Health Monitoring. Sensors. 2021; 21(16):5430. https://doi.org/10.3390/s21165430

Chicago/Turabian Style

Iqbal, Naeem, Imran, Shabir Ahmad, Rashid Ahmad, and Do-Hyeun Kim. 2021. "A Scheduling Mechanism Based on Optimization Using IoT-Tasks Orchestration for Efficient Patient Health Monitoring" Sensors 21, no. 16: 5430. https://doi.org/10.3390/s21165430

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop