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arXiv · 2105.11097

Criticality and Utility-aware Fog Computing System for Remote Health Monitoring

Moirangthem Biken Singh·Navneet Taunk·Naveen Kumar Mall·Ajay Pratap
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Abstract

Growing remote health monitoring system allows constant monitoring of the patient's condition and performance of preventive and control check-ups outside medical facilities. However, the real-time smart-healthcare application poses a delay constraint that has to be solved efficiently. Fog computing is emerging as an efficient solution for such real-time applications. Moreover, different medical centers are getting attracted to the growing IoT-based remote healthcare system in order to make a profit by hiring Fog computing resources. However, there is a need for an efficient algorithmic model for allocation of limited fog computing resources in the criticality-aware smart-healthcare system considering the profit of medical centers. Thus, the objective of this work is to maximize the system utility calculated as a linear combination of the profit of the medical center and the loss of patients. To measure profit, we propose a flat-pricing-based model. Further, we propose a swapping-based heuristic to maximize the system utility. The proposed heuristic is tested on various parameters and shown to perform close to the optimal with criticality-awareness in its core. Through extensive simulations, we show that the proposed heuristic achieves an average utility of $96\%$ of the optimal, in polynomial time complexity.

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Moirangthem Biken Singh, Navneet Taunk, Naveen Kumar Mall, Ajay Pratap. 2021-05-24. Criticality and Utility-aware Fog Computing System for Remote Health Monitoring. https://arxiv.org/abs/2105.11097

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