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Smart bandwidth allocation for next generation networks adopting software-defined network approach

This data article contains information on a new intelligent bandwidth allocation model for future network (Smart Allocation). The included data describe the topology of the network testbed and the obtained results. Obtained data show the effectiveness of the proposed model in comparison with the MAM...

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Detalles Bibliográficos
Autores principales: Bahnasse, Ayoub, Louhab, Fatima Ezzahraa, Oulahyane, Hafsa Ait, Talea, Mohamed, Bakali, Assia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6134167/
https://www.ncbi.nlm.nih.gov/pubmed/30211284
http://dx.doi.org/10.1016/j.dib.2018.08.091
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author Bahnasse, Ayoub
Louhab, Fatima Ezzahraa
Oulahyane, Hafsa Ait
Talea, Mohamed
Bakali, Assia
author_facet Bahnasse, Ayoub
Louhab, Fatima Ezzahraa
Oulahyane, Hafsa Ait
Talea, Mohamed
Bakali, Assia
author_sort Bahnasse, Ayoub
collection PubMed
description This data article contains information on a new intelligent bandwidth allocation model for future network (Smart Allocation). The included data describe the topology of the network testbed and the obtained results. Obtained data show the effectiveness of the proposed model in comparison with the MAM and RDM bandwidth allocation models. In relation to the performances evaluation, a variety of flows are used such as: voice over IP (VoIP), video, HTTP, and Internet Control Message Protocol (ICMP). The evaluation criteria are: VoIP latency and jitter, Peak Signal to Noise Ratio (PSNR) video, retransmission video, goodput, HTTP response page, and the Round-Trip Time (RTT) ICMP delay. The presented data are extracted based on simulation.
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spelling pubmed-61341672018-09-12 Smart bandwidth allocation for next generation networks adopting software-defined network approach Bahnasse, Ayoub Louhab, Fatima Ezzahraa Oulahyane, Hafsa Ait Talea, Mohamed Bakali, Assia Data Brief Computer Science This data article contains information on a new intelligent bandwidth allocation model for future network (Smart Allocation). The included data describe the topology of the network testbed and the obtained results. Obtained data show the effectiveness of the proposed model in comparison with the MAM and RDM bandwidth allocation models. In relation to the performances evaluation, a variety of flows are used such as: voice over IP (VoIP), video, HTTP, and Internet Control Message Protocol (ICMP). The evaluation criteria are: VoIP latency and jitter, Peak Signal to Noise Ratio (PSNR) video, retransmission video, goodput, HTTP response page, and the Round-Trip Time (RTT) ICMP delay. The presented data are extracted based on simulation. Elsevier 2018-08-30 /pmc/articles/PMC6134167/ /pubmed/30211284 http://dx.doi.org/10.1016/j.dib.2018.08.091 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Computer Science
Bahnasse, Ayoub
Louhab, Fatima Ezzahraa
Oulahyane, Hafsa Ait
Talea, Mohamed
Bakali, Assia
Smart bandwidth allocation for next generation networks adopting software-defined network approach
title Smart bandwidth allocation for next generation networks adopting software-defined network approach
title_full Smart bandwidth allocation for next generation networks adopting software-defined network approach
title_fullStr Smart bandwidth allocation for next generation networks adopting software-defined network approach
title_full_unstemmed Smart bandwidth allocation for next generation networks adopting software-defined network approach
title_short Smart bandwidth allocation for next generation networks adopting software-defined network approach
title_sort smart bandwidth allocation for next generation networks adopting software-defined network approach
topic Computer Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6134167/
https://www.ncbi.nlm.nih.gov/pubmed/30211284
http://dx.doi.org/10.1016/j.dib.2018.08.091
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