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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...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2018
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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. |
format | Online Article Text |
id | pubmed-6134167 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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