Multi-Agent Systems in Fog–Cloud Computing for Critical Healthcare Task Management Model (CHTM) Used for ECG Monitoring
In the last decade, the developments in healthcare technologies have been increasing progressively in practice. Healthcare applications such as ECG monitoring, heartbeat analysis, and blood pressure control connect with external servers in a manner called cloud computing. The emerging cloud paradigm...
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| Format: | Article |
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MDPI AG
2021-10-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/21/20/6923 |
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| author | Ammar Awad Mutlag Mohd Khanapi Abd Ghani Mazin Abed Mohammed Abdullah Lakhan Othman Mohd Karrar Hameed Abdulkareem Begonya Garcia-Zapirain |
| author_facet | Ammar Awad Mutlag Mohd Khanapi Abd Ghani Mazin Abed Mohammed Abdullah Lakhan Othman Mohd Karrar Hameed Abdulkareem Begonya Garcia-Zapirain |
| author_sort | Ammar Awad Mutlag |
| collection | DOAJ |
| description | In the last decade, the developments in healthcare technologies have been increasing progressively in practice. Healthcare applications such as ECG monitoring, heartbeat analysis, and blood pressure control connect with external servers in a manner called cloud computing. The emerging cloud paradigm offers different models, such as fog computing and edge computing, to enhance the performances of healthcare applications with minimum end-to-end delay in the network. However, many research challenges exist in the fog-cloud enabled network for healthcare applications. Therefore, in this paper, a Critical Healthcare Task Management (CHTM) model is proposed and implemented using an ECG dataset. We design a resource scheduling model among fog nodes at the fog level. A multi-agent system is proposed to provide the complete management of the network from the edge to the cloud. The proposed model overcomes the limitations of providing interoperability, resource sharing, scheduling, and dynamic task allocation to manage critical tasks significantly. The simulation results show that our model, in comparison with the cloud, significantly reduces the network usage by 79%, the response time by 90%, the network delay by 65%, the energy consumption by 81%, and the instance cost by 80%. |
| first_indexed | 2024-03-10T06:12:03Z |
| format | Article |
| id | doaj.art-1784cc3dfd2044b58ef840da91cf758e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T06:12:03Z |
| publishDate | 2021-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1784cc3dfd2044b58ef840da91cf758e2023-11-22T19:59:36ZengMDPI AGSensors1424-82202021-10-012120692310.3390/s21206923Multi-Agent Systems in Fog–Cloud Computing for Critical Healthcare Task Management Model (CHTM) Used for ECG MonitoringAmmar Awad Mutlag0Mohd Khanapi Abd Ghani1Mazin Abed Mohammed2Abdullah Lakhan3Othman Mohd4Karrar Hameed Abdulkareem5Begonya Garcia-Zapirain6Biomedical Computing and Engineering Technologies (BIOCORE) Applied Research Group, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Durian Tunggal 76100, MalaysiaBiomedical Computing and Engineering Technologies (BIOCORE) Applied Research Group, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Durian Tunggal 76100, MalaysiaCollege of Computer Science and Information Technology, University of Anbar, 11, Ramadi 31001, IraqDepartment of Computer Science and Artificial Intelligence, Wenzhou University, Wenzhou 325035, ChinaBiomedical Computing and Engineering Technologies (BIOCORE) Applied Research Group, Faculty of Information and Communication Technology, Universiti Teknikal Malaysia Melaka, Durian Tunggal 76100, MalaysiaCollege of Agriculture, Al-Muthanna University, Samawah 66001, IraqeVIDA Laboratory, University of Deusto, Avda/Universidades 24, 48007 Bilbao, SpainIn the last decade, the developments in healthcare technologies have been increasing progressively in practice. Healthcare applications such as ECG monitoring, heartbeat analysis, and blood pressure control connect with external servers in a manner called cloud computing. The emerging cloud paradigm offers different models, such as fog computing and edge computing, to enhance the performances of healthcare applications with minimum end-to-end delay in the network. However, many research challenges exist in the fog-cloud enabled network for healthcare applications. Therefore, in this paper, a Critical Healthcare Task Management (CHTM) model is proposed and implemented using an ECG dataset. We design a resource scheduling model among fog nodes at the fog level. A multi-agent system is proposed to provide the complete management of the network from the edge to the cloud. The proposed model overcomes the limitations of providing interoperability, resource sharing, scheduling, and dynamic task allocation to manage critical tasks significantly. The simulation results show that our model, in comparison with the cloud, significantly reduces the network usage by 79%, the response time by 90%, the network delay by 65%, the energy consumption by 81%, and the instance cost by 80%.https://www.mdpi.com/1424-8220/21/20/6923cloud computingfog computingschedulingmulti-agent systembalancingprioritization |
| spellingShingle | Ammar Awad Mutlag Mohd Khanapi Abd Ghani Mazin Abed Mohammed Abdullah Lakhan Othman Mohd Karrar Hameed Abdulkareem Begonya Garcia-Zapirain Multi-Agent Systems in Fog–Cloud Computing for Critical Healthcare Task Management Model (CHTM) Used for ECG Monitoring Sensors cloud computing fog computing scheduling multi-agent system balancing prioritization |
| title | Multi-Agent Systems in Fog–Cloud Computing for Critical Healthcare Task Management Model (CHTM) Used for ECG Monitoring |
| title_full | Multi-Agent Systems in Fog–Cloud Computing for Critical Healthcare Task Management Model (CHTM) Used for ECG Monitoring |
| title_fullStr | Multi-Agent Systems in Fog–Cloud Computing for Critical Healthcare Task Management Model (CHTM) Used for ECG Monitoring |
| title_full_unstemmed | Multi-Agent Systems in Fog–Cloud Computing for Critical Healthcare Task Management Model (CHTM) Used for ECG Monitoring |
| title_short | Multi-Agent Systems in Fog–Cloud Computing for Critical Healthcare Task Management Model (CHTM) Used for ECG Monitoring |
| title_sort | multi agent systems in fog cloud computing for critical healthcare task management model chtm used for ecg monitoring |
| topic | cloud computing fog computing scheduling multi-agent system balancing prioritization |
| url | https://www.mdpi.com/1424-8220/21/20/6923 |
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