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Dynamically Controlling Offloading Thresholds in Fog Systems
Fog computing is a potential solution to overcome the shortcomings of cloud-based processing of IoT tasks. These drawbacks can include high latency, location awareness, and security—attributed to the distance between IoT devices and cloud-hosted servers. Although fog computing has evolved as a solut...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038364/ https://www.ncbi.nlm.nih.gov/pubmed/33916818 http://dx.doi.org/10.3390/s21072512 |
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author | Alenizi, Faten Rana, Omer |
author_facet | Alenizi, Faten Rana, Omer |
author_sort | Alenizi, Faten |
collection | PubMed |
description | Fog computing is a potential solution to overcome the shortcomings of cloud-based processing of IoT tasks. These drawbacks can include high latency, location awareness, and security—attributed to the distance between IoT devices and cloud-hosted servers. Although fog computing has evolved as a solution to address these challenges, it is known for having limited resources that need to be effectively utilized, or its advantages could be lost. Computational offloading and resource management are critical to be able to benefit from fog computing systems. We introduce a dynamic, online, offloading scheme that involves the execution of delay-sensitive tasks. This paper proposes an architecture of a fog node able to adjust its offloading threshold dynamically (i.e., the criteria by which a fog node decides whether tasks should be offloaded rather than executed locally) using two algorithms: dynamic task scheduling (DTS) and dynamic energy control (DEC). These algorithms seek to minimize overall delay, maximize throughput, and minimize energy consumption at the fog layer. Compared to other benchmarks, our approach could reduce latency by up to 95%, improve throughput by 71%, and reduce energy consumption by up to 67% in fog nodes. |
format | Online Article Text |
id | pubmed-8038364 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-80383642021-04-12 Dynamically Controlling Offloading Thresholds in Fog Systems Alenizi, Faten Rana, Omer Sensors (Basel) Article Fog computing is a potential solution to overcome the shortcomings of cloud-based processing of IoT tasks. These drawbacks can include high latency, location awareness, and security—attributed to the distance between IoT devices and cloud-hosted servers. Although fog computing has evolved as a solution to address these challenges, it is known for having limited resources that need to be effectively utilized, or its advantages could be lost. Computational offloading and resource management are critical to be able to benefit from fog computing systems. We introduce a dynamic, online, offloading scheme that involves the execution of delay-sensitive tasks. This paper proposes an architecture of a fog node able to adjust its offloading threshold dynamically (i.e., the criteria by which a fog node decides whether tasks should be offloaded rather than executed locally) using two algorithms: dynamic task scheduling (DTS) and dynamic energy control (DEC). These algorithms seek to minimize overall delay, maximize throughput, and minimize energy consumption at the fog layer. Compared to other benchmarks, our approach could reduce latency by up to 95%, improve throughput by 71%, and reduce energy consumption by up to 67% in fog nodes. MDPI 2021-04-03 /pmc/articles/PMC8038364/ /pubmed/33916818 http://dx.doi.org/10.3390/s21072512 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Alenizi, Faten Rana, Omer Dynamically Controlling Offloading Thresholds in Fog Systems |
title | Dynamically Controlling Offloading Thresholds in Fog Systems |
title_full | Dynamically Controlling Offloading Thresholds in Fog Systems |
title_fullStr | Dynamically Controlling Offloading Thresholds in Fog Systems |
title_full_unstemmed | Dynamically Controlling Offloading Thresholds in Fog Systems |
title_short | Dynamically Controlling Offloading Thresholds in Fog Systems |
title_sort | dynamically controlling offloading thresholds in fog systems |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8038364/ https://www.ncbi.nlm.nih.gov/pubmed/33916818 http://dx.doi.org/10.3390/s21072512 |
work_keys_str_mv | AT alenizifaten dynamicallycontrollingoffloadingthresholdsinfogsystems AT ranaomer dynamicallycontrollingoffloadingthresholdsinfogsystems |