A Novel Framework for Fog-Assisted Smart Healthcare System with Workload Optimization

Abdellatif, Ahmed A. H. and Singh, Aman and Aldribi, Abdulaziz and Ortega-Mansilla, Arturo and Ibrahim, Muhammad and Rehman, Ateeq Ur UNSPECIFIED, aman.singh@uneatlantico.es, UNSPECIFIED, arturo.ortega@uneatlantico.es, UNSPECIFIED, UNSPECIFIED (2022) A Novel Framework for Fog-Assisted Smart Healthcare System with Workload Optimization. Computational Intelligence and Neuroscience, 2022. pp. 1-12. ISSN 1687-5265

[img]
Preview
Text
4174805.pdf
Available under License Creative Commons Attribution.

Download (1MB) | Preview

Abstract

Fog-assisted and IoT-enabled smart healthcare system with rapid response rates is the major area of concern now a days. Dynamic and heterogeneous fog networks are difficult to manage and a considerable amount of overhead could be realized while managing ever increasing load on foglets. Fog computing plays a vital role in managing ever increasing processing demands from diverse IoT-based applications. Smart healthcare systems work with the assistance of sensor-based devices and automatic data collection and processing can speed up overall system functionality. In the proposed work, a novel framework for smart health care is presented where a series of activities are performed with prime objective of reducing latency and execution time. Principal component analysis is used for feature reduction and support vector machines with radial basis function kernel is used for classification purpose. Workload optimization on the fog nodes is implemented using genetic algorithm. Data collection process also involves preprocessing as a leading step for generating cleaner data. Amalgamation of intelligent and optimization techniques in the presented framework certainly improves the efficiency of the overall system. Experimental results reveal that proposed work outperforms the existing fog-assisted smart healthcare systems in terms of latency, execution time, overall system accuracy, and system stability.

Item Type: Article
Subjects: Subjects > Engineering
Divisions: Europe University of Atlantic > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Ibero-american International University > Research > Scientific Production
Depositing User: Sr Bibliotecario
Date Deposited: 03 Oct 2022 07:16
Last Modified: 11 Jul 2023 06:30
URI: http://repositorio.funiber.org/id/eprint/3796

Actions (login required)

View Item View Item