An Edge Computing Based Smart Healthcare Framework for Resource Management
The revolution in information technologies, and the spread of the Internet of Things (IoT) and smart city industrial systems, have fostered widespread use of smart systems. As a complex, 24/7 service, healthcare requires efficient and reliable follow-up on daily operations, service and resources. Cl...
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doaj-15c24f058fad4cb9b99ed38e866146a32020-11-24T21:35:10ZengMDPI AGSensors1424-82202018-12-011812430710.3390/s18124307s18124307An Edge Computing Based Smart Healthcare Framework for Resource ManagementSoraia Oueida0Yehia Kotb1Moayad Aloqaily2Yaser Jararweh3Thar Baker4Politehnica University of Bucharest, 060042 Bucharest, RomaniaAmerican University of the Middle East, Eqaila 250 St, KuwaitGnowit Inc., 7 Bayview Road, Ottawa, ON K1Y3B5, CanadaJordan University of Science and Technology, Irbid 22110, JordanLiverpool John Moores University, Liverpool L3 3AF, UKThe revolution in information technologies, and the spread of the Internet of Things (IoT) and smart city industrial systems, have fostered widespread use of smart systems. As a complex, 24/7 service, healthcare requires efficient and reliable follow-up on daily operations, service and resources. Cloud and edge computing are essential for smart and efficient healthcare systems in smart cities. Emergency departments (ED) are real-time systems with complex dynamic behavior, and they require tailored techniques to model, simulate and optimize system resources and service flow. ED issues are mainly due to resource shortage and resource assignment efficiency. In this paper, we propose a resource preservation net (RPN) framework using Petri net, integrated with custom cloud and edge computing suitable for ED systems. The proposed framework is designed to model non-consumable resources and is theoretically described and validated. RPN is applicable to a real-life scenario where key performance indicators such as patient length of stay (LoS), resource utilization rate and average patient waiting time are modeled and optimized. As the system must be reliable, efficient and secure, the use of cloud and edge computing is critical. The proposed framework is simulated, which highlights significant improvements in LoS, resource utilization and patient waiting time.https://www.mdpi.com/1424-8220/18/12/4307edge computingcloud computingsmart citysmart healthcare managementemergency departmentPetri net workflowworkflow soundness |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Soraia Oueida Yehia Kotb Moayad Aloqaily Yaser Jararweh Thar Baker |
spellingShingle |
Soraia Oueida Yehia Kotb Moayad Aloqaily Yaser Jararweh Thar Baker An Edge Computing Based Smart Healthcare Framework for Resource Management Sensors edge computing cloud computing smart city smart healthcare management emergency department Petri net workflow workflow soundness |
author_facet |
Soraia Oueida Yehia Kotb Moayad Aloqaily Yaser Jararweh Thar Baker |
author_sort |
Soraia Oueida |
title |
An Edge Computing Based Smart Healthcare Framework for Resource Management |
title_short |
An Edge Computing Based Smart Healthcare Framework for Resource Management |
title_full |
An Edge Computing Based Smart Healthcare Framework for Resource Management |
title_fullStr |
An Edge Computing Based Smart Healthcare Framework for Resource Management |
title_full_unstemmed |
An Edge Computing Based Smart Healthcare Framework for Resource Management |
title_sort |
edge computing based smart healthcare framework for resource management |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2018-12-01 |
description |
The revolution in information technologies, and the spread of the Internet of Things (IoT) and smart city industrial systems, have fostered widespread use of smart systems. As a complex, 24/7 service, healthcare requires efficient and reliable follow-up on daily operations, service and resources. Cloud and edge computing are essential for smart and efficient healthcare systems in smart cities. Emergency departments (ED) are real-time systems with complex dynamic behavior, and they require tailored techniques to model, simulate and optimize system resources and service flow. ED issues are mainly due to resource shortage and resource assignment efficiency. In this paper, we propose a resource preservation net (RPN) framework using Petri net, integrated with custom cloud and edge computing suitable for ED systems. The proposed framework is designed to model non-consumable resources and is theoretically described and validated. RPN is applicable to a real-life scenario where key performance indicators such as patient length of stay (LoS), resource utilization rate and average patient waiting time are modeled and optimized. As the system must be reliable, efficient and secure, the use of cloud and edge computing is critical. The proposed framework is simulated, which highlights significant improvements in LoS, resource utilization and patient waiting time. |
topic |
edge computing cloud computing smart city smart healthcare management emergency department Petri net workflow workflow soundness |
url |
https://www.mdpi.com/1424-8220/18/12/4307 |
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