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Simulation Tools for Fog Computing: A Comparative Analysis

Fog Computing (FC) was introduced to offer resources closer to the users. Researchers propose different solutions to make FC mature and use simulators for evaluating their solutions at early stages. In this paper, we compare different FC simulators based on their technical and non-technical characte...

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Detalles Bibliográficos
Autores principales: Fahimullah, Muhammad, Philippe, Guillaume, Ahvar, Shohreh, Trocan, Maria
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099336/
https://www.ncbi.nlm.nih.gov/pubmed/37050551
http://dx.doi.org/10.3390/s23073492
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author Fahimullah, Muhammad
Philippe, Guillaume
Ahvar, Shohreh
Trocan, Maria
author_facet Fahimullah, Muhammad
Philippe, Guillaume
Ahvar, Shohreh
Trocan, Maria
author_sort Fahimullah, Muhammad
collection PubMed
description Fog Computing (FC) was introduced to offer resources closer to the users. Researchers propose different solutions to make FC mature and use simulators for evaluating their solutions at early stages. In this paper, we compare different FC simulators based on their technical and non-technical characteristics. In addition, a practical comparison is conducted to compare the three main FC simulators based on their performance such as execution time, CPU, and memory usage for running different applications. The analysis can be helpful for researchers to select the appropriate simulator and platform to evaluate their solutions on different use cases. Furthermore, open issues and challenges for FC simulators are discussed that require attention and need to be addressed in the future.
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spelling pubmed-100993362023-04-14 Simulation Tools for Fog Computing: A Comparative Analysis Fahimullah, Muhammad Philippe, Guillaume Ahvar, Shohreh Trocan, Maria Sensors (Basel) Article Fog Computing (FC) was introduced to offer resources closer to the users. Researchers propose different solutions to make FC mature and use simulators for evaluating their solutions at early stages. In this paper, we compare different FC simulators based on their technical and non-technical characteristics. In addition, a practical comparison is conducted to compare the three main FC simulators based on their performance such as execution time, CPU, and memory usage for running different applications. The analysis can be helpful for researchers to select the appropriate simulator and platform to evaluate their solutions on different use cases. Furthermore, open issues and challenges for FC simulators are discussed that require attention and need to be addressed in the future. MDPI 2023-03-27 /pmc/articles/PMC10099336/ /pubmed/37050551 http://dx.doi.org/10.3390/s23073492 Text en © 2023 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
Fahimullah, Muhammad
Philippe, Guillaume
Ahvar, Shohreh
Trocan, Maria
Simulation Tools for Fog Computing: A Comparative Analysis
title Simulation Tools for Fog Computing: A Comparative Analysis
title_full Simulation Tools for Fog Computing: A Comparative Analysis
title_fullStr Simulation Tools for Fog Computing: A Comparative Analysis
title_full_unstemmed Simulation Tools for Fog Computing: A Comparative Analysis
title_short Simulation Tools for Fog Computing: A Comparative Analysis
title_sort simulation tools for fog computing: a comparative analysis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10099336/
https://www.ncbi.nlm.nih.gov/pubmed/37050551
http://dx.doi.org/10.3390/s23073492
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