Version 1
: Received: 22 September 2023 / Approved: 25 September 2023 / Online: 26 September 2023 (13:57:37 CEST)
How to cite:
Alharbi, A.M.; Al-Hagery, M.A. Enhancement of the Fog Computing Efficiency: Healthcare as a Case Study. Preprints2023, 2023091737. https://doi.org/10.20944/preprints202309.1737.v1
Alharbi, A.M.; Al-Hagery, M.A. Enhancement of the Fog Computing Efficiency: Healthcare as a Case Study. Preprints 2023, 2023091737. https://doi.org/10.20944/preprints202309.1737.v1
Alharbi, A.M.; Al-Hagery, M.A. Enhancement of the Fog Computing Efficiency: Healthcare as a Case Study. Preprints2023, 2023091737. https://doi.org/10.20944/preprints202309.1737.v1
APA Style
Alharbi, A.M., & Al-Hagery, M.A. (2023). Enhancement of the Fog Computing Efficiency: Healthcare as a Case Study. Preprints. https://doi.org/10.20944/preprints202309.1737.v1
Chicago/Turabian Style
Alharbi, A.M. and Mohammed Abdullah Al-Hagery. 2023 "Enhancement of the Fog Computing Efficiency: Healthcare as a Case Study" Preprints. https://doi.org/10.20944/preprints202309.1737.v1
Abstract
Cloud computing is a strong and efficient technology facing some efficiency challenges attributable to its decentralized nature. The emergence of fog computing has subdivided the expansive cloud into numerous smaller units known as "cloudlets." Fog computing is one of the most recent advancements in today’s cloud computing landscape. Each cloudlet is a novel and diminutive architectural element extending the contemporary cloud computing infrastructure. The term "cloudlets" has been integrated with fog computing due to its augmenting impact on the attributes of cloud computing. F fog computing is a significant foundation and an indispensable cloud component. Consequently, this technology holds the potential to address efficiency concerns effectively. As a result, this paper focuses on enhancing the efficiency of the cloud computing environment by fine-tuning the efficiency parameters derived from fog computing. These parameters encompass response time, latency, and network utilization. The proposed solution involves developing a simulation system to minimize task redundancy and increase performance levels in the healthcare environment. The outcomes manifest a substantial improvement in the performance of the suggested system, with a clear increase depending on the three key parameters (response time, network utilization, and latency). Therefore, these findings are encouraging and carry significant implications, promoting the application of the proposed system in the real healthcare environment.
Computer Science and Mathematics, Computer Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
