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Performability Evaluation of Load Balancing and Fail-over Strategies for Medical Information Systems with Edge/Fog
Tuan Anh Nguyen1, Iure Fe2, Carlos Brito2
1Konkuk Aerospace Design-Airworthiness Research Institute (KADA), Konkuk University, Seoul 05029, Korea.
Sensors (Basel, Switzerland)
|September 28, 2021
Summary
This study introduces a performability model for edge/fog medical information systems (MIS) to ensure reliable patient care during pandemics. Combining load balancing and fail-over mechanisms significantly enhances medical service continuity and trustworthiness.
Area of Science:
- Computer Science
- Information Systems
- Healthcare Technology
Background:
- Global virus pandemics necessitate robust local computing infrastructures in healthcare facilities.
- Existing research often focuses on remote data centers, with limited investigation into local medical center performance under operational constraints.
- There is a critical need for models to quantify medical service operational metrics within Medical Information Systems (MIS).
Purpose of the Study:
- To propose a comprehensive performability Stochastic Reward Net (SRN) model for edge/fog-based MIS.
- To quantify the performability of medical data transactions and services in local hospitals.
- To analyze the impact of load-balancing techniques and fail-over mechanisms on system performance and service continuity.
Main Methods:
- Developed a performability SRN model for an edge/fog MIS, incorporating failure modes of fog nodes and virtual machines (VMs).
- Integrated and analyzed three load-balancing techniques (probability-based, random-based, shortest queue-based) for medical data distribution.
- Evaluated the effects of fail-over mechanisms at fog node and VM levels using discrete-event simulation.
Main Results:
- The combination of load-balancing techniques and fail-over mechanisms significantly enhances MIS performability.
- Fail-over mechanisms improve medical service continuity and quality metrics.
- Load-balancing techniques enhance system performance metrics, with integrated strategies yielding superior results.
Conclusions:
- Integrated load balancing and fail-over mechanisms provide high-level performability and trustworthiness for medical services.
- The proposed model aids in designing MIS that maintain continuous performance under heavy workloads and availability constraints.
- This research supports the development of resilient healthcare IT infrastructure to combat future pandemics.
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