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Two-Way Approach for Improved Real-Time Transmission in Fog-IoT-Based Health Monitoring System for Critical Patients

Abeera Ilyas1,*, Saeed Mahfooz1, Zahid Mehmood2,3, Gauhar Ali4, Muhammad ElAffendi4

1 Department of Computer Science, University of Peshawar, Peshawar, 25120, Pakistan
2 Department of Computer Engineering, University of Engineering and Technology, Taxila, 47050, Pakistan
3 The FAMLIR Group, The University of Lahore, Lahore, 54000, Pakistan
4 EIAS Data Science and Blockchain Lab, College of Computer and Information Sciences, Prince Sultan University, Riyadh, 11586, Saudi Arabia

* Corresponding Author: Abeera Ilyas. Email:

Computer Systems Science and Engineering 2023, 46(3), 3815-3829.


Health monitoring systems are now required, particularly for essential patients, following the COVID-19 pandemic, which was followed by its variants and other epidemics of a similar nature. Effective procedures and strategies are required, though, to react promptly to the enormous volume of real-time data offered by monitoring equipment. Although fog-based designs for IoT health systems typically result in enhanced services, they also give rise to issues that need to be resolved. In this paper, we propose a two-way strategy to reduce network latency and use while increasing real-time data transmission of device gateways used for sensors by making educated judgments for connection setup with BS and task assignment. For this, a simulation using iFogSim in the Eclipse IDE showed how effective the suggested strategy for massive IoT health monitoring systems is. The algorithm is analyzed for network usage and latency, and the results reveal 20%–25% improvements compared to the existing methods regarding network usage and latency.


Cite This Article

A. Ilyas, S. Mahfooz, Z. Mehmood, G. Ali and M. ElAffendi, "Two-way approach for improved real-time transmission in fog-iot-based health monitoring system for critical patients," Computer Systems Science and Engineering, vol. 46, no.3, pp. 3815–3829, 2023.

This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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