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Article

Performability Evaluation of Load Balancing and Fail-over Strategies for Medical Information Systems with Edge/Fog Computing Using Stochastic Reward Nets

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Konkuk Aerospace Design-Airworthiness Research Institute (KADA), Konkuk University, Seoul 05029, Korea
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Programa de Pós-Graduação em Ciência da Computação, Campus Universitário Ministro Petrônio Portella, Universidade Federal do Piauí (UFPI), Ininga, Teresina 64049-550, PI, Brazil
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School of Software, College of Computer Science, Kookmin University, Seoul 02707, Korea
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Department of Computer Science and Engineering, College of Engineering, Konkuk University, Seoul 05029, Korea
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Department of Aerospace Information Engineering, Konkuk University, Seoul 05029, Korea
*
Author to whom correspondence should be addressed.
Academic Editors: Behnam Dezfouli and Yuhong Liu
Sensors 2021, 21(18), 6253; https://doi.org/10.3390/s21186253
Received: 27 July 2021 / Revised: 9 September 2021 / Accepted: 12 September 2021 / Published: 17 September 2021
(This article belongs to the Special Issue Edge and Fog Computing for Internet of Things Systems)
The aggressive waves of ongoing world-wide virus pandemics urge us to conduct further studies on the performability of local computing infrastructures at hospitals/medical centers to provide a high level of assurance and trustworthiness of medical services and treatment to patients, and to help diminish the burden and chaos of medical management and operations. Previous studies contributed tremendous progress on the dependability quantification of existing computing paradigms (e.g., cloud, grid computing) at remote data centers, while a few works investigated the performance of provided medical services under the constraints of operational availability of devices and systems at local medical centers. Therefore, it is critical to rapidly develop appropriate models to quantify the operational metrics of medical services provided and sustained by medical information systems (MIS) even before practical implementation. In this paper, we propose a comprehensive performability SRN model of an edge/fog based MIS for the performability quantification of medical data transaction and services in local hospitals or medical centers. The model elaborates different failure modes of fog nodes and their VMs under the implementation of fail-over mechanisms. Sophisticated behaviors and dependencies between the performance and availability of data transactions are elaborated in a comprehensive manner when adopting three main load-balancing techniques including: (i) probability-based, (ii) random-based and (iii) shortest queue-based approaches for medical data distribution from edge to fog layers along with/without fail-over mechanisms in the cases of component failures at two levels of fog nodes and fog virtual machines (VMs). Different performability metrics of interest are analyzed including (i) recover token rate, (ii) mean response time, (iii) drop probability, (iv) throughput, (v) queue utilization of network devices and fog nodes to assimilate the impact of load-balancing techniques and fail-over mechanisms. Discrete-event simulation results highlight the effectiveness of the combination of these for enhancing the performability of medical services provided by an MIS. Particularly, performability metrics of medical service continuity and quality are improved with fail-over mechanisms in the MIS while load balancing techniques help to enhance system performance metrics. The implementation of both load balancing techniques along with fail-over mechanisms provide better performability metrics compared to the separate cases. The harmony of the integrated strategies eventually provides the trustworthiness of medical services at a high level of performability. This study can help improve the design of MIS systems integrated with different load-balancing techniques and fail-over mechanisms to maintain continuous performance under the availability constraints of medical services with heavy computing workloads in local hospitals/medical centers, to combat with new waves of virus pandemics. View Full-Text
Keywords: medical information system; edge/fog computing; performability evaluation; load balancing; fail-over mechanism; stochastic reward net; discrete-event simulation medical information system; edge/fog computing; performability evaluation; load balancing; fail-over mechanism; stochastic reward net; discrete-event simulation
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MDPI and ACS Style

Nguyen, T.A.; Fe, I.; Brito, C.; Kaliappan, V.K.; Choi, E.; Min, D.; Lee, J.W.; Silva, F.A. Performability Evaluation of Load Balancing and Fail-over Strategies for Medical Information Systems with Edge/Fog Computing Using Stochastic Reward Nets. Sensors 2021, 21, 6253. https://doi.org/10.3390/s21186253

AMA Style

Nguyen TA, Fe I, Brito C, Kaliappan VK, Choi E, Min D, Lee JW, Silva FA. Performability Evaluation of Load Balancing and Fail-over Strategies for Medical Information Systems with Edge/Fog Computing Using Stochastic Reward Nets. Sensors. 2021; 21(18):6253. https://doi.org/10.3390/s21186253

Chicago/Turabian Style

Nguyen, Tuan A., Iure Fe, Carlos Brito, Vishnu K. Kaliappan, Eunmi Choi, Dugki Min, Jae W. Lee, and Francisco A. Silva 2021. "Performability Evaluation of Load Balancing and Fail-over Strategies for Medical Information Systems with Edge/Fog Computing Using Stochastic Reward Nets" Sensors 21, no. 18: 6253. https://doi.org/10.3390/s21186253

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