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A multi-tier fog content orchestrator mechanism with quality of experience support
Video-on-Demand (VoD) services create a demand for content orchestrator mechanisms to support Quality of Experience (QoE). Fog computing brings benefits for enhancing the QoE for VoD services by caching the content closer to the user in a multi-tier fog architecture, considering their available reso...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier B.V.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7202856/ http://dx.doi.org/10.1016/j.comnet.2020.107288 |
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author | Santos, Hugo Alencar, Derian Meneguette, Rodolfo Rosário, Denis Nobre, Jéferson Both, Cristiano Cerqueira, Eduardo Braun, Torsten |
author_facet | Santos, Hugo Alencar, Derian Meneguette, Rodolfo Rosário, Denis Nobre, Jéferson Both, Cristiano Cerqueira, Eduardo Braun, Torsten |
author_sort | Santos, Hugo |
collection | PubMed |
description | Video-on-Demand (VoD) services create a demand for content orchestrator mechanisms to support Quality of Experience (QoE). Fog computing brings benefits for enhancing the QoE for VoD services by caching the content closer to the user in a multi-tier fog architecture, considering their available resources to improve QoE. In this context, it is mandatory to consider network, fog node, and user metrics to choose an appropriate fog node to distribute videos with QoE support properly. In this article, we introduce a content orchestrator mechanism, called of Fog4Video, which chooses an appropriate fog node to download video content. The mechanism considers the available bandwidth, delay, and cost, besides the QoE metrics for VoD, namely number of stalls and stalls duration, to deploy VoD services in the opportune fog node. Decision-making acknowledges periodical reports of QoE from the clients to assess the video streaming from each fog node. These values serve as inputs for a real-time Analytic Hierarchy Process method to compute the influence factor for each parameter and compute the QoE improvement potential of the fog node. Fog4Video is executed in fog nodes organized in multiple tiers, having different characteristics to provide VoD services. Simulation results demonstrate that Fog4Video transmits adapted videos with 30% higher QoE and reduced monetary cost up to 24% than other content request mechanisms. |
format | Online Article Text |
id | pubmed-7202856 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier B.V. |
record_format | MEDLINE/PubMed |
spelling | pubmed-72028562020-05-07 A multi-tier fog content orchestrator mechanism with quality of experience support Santos, Hugo Alencar, Derian Meneguette, Rodolfo Rosário, Denis Nobre, Jéferson Both, Cristiano Cerqueira, Eduardo Braun, Torsten Computer Networks Article Video-on-Demand (VoD) services create a demand for content orchestrator mechanisms to support Quality of Experience (QoE). Fog computing brings benefits for enhancing the QoE for VoD services by caching the content closer to the user in a multi-tier fog architecture, considering their available resources to improve QoE. In this context, it is mandatory to consider network, fog node, and user metrics to choose an appropriate fog node to distribute videos with QoE support properly. In this article, we introduce a content orchestrator mechanism, called of Fog4Video, which chooses an appropriate fog node to download video content. The mechanism considers the available bandwidth, delay, and cost, besides the QoE metrics for VoD, namely number of stalls and stalls duration, to deploy VoD services in the opportune fog node. Decision-making acknowledges periodical reports of QoE from the clients to assess the video streaming from each fog node. These values serve as inputs for a real-time Analytic Hierarchy Process method to compute the influence factor for each parameter and compute the QoE improvement potential of the fog node. Fog4Video is executed in fog nodes organized in multiple tiers, having different characteristics to provide VoD services. Simulation results demonstrate that Fog4Video transmits adapted videos with 30% higher QoE and reduced monetary cost up to 24% than other content request mechanisms. Elsevier B.V. 2020-08-04 2020-05-06 /pmc/articles/PMC7202856/ http://dx.doi.org/10.1016/j.comnet.2020.107288 Text en © 2020 Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Santos, Hugo Alencar, Derian Meneguette, Rodolfo Rosário, Denis Nobre, Jéferson Both, Cristiano Cerqueira, Eduardo Braun, Torsten A multi-tier fog content orchestrator mechanism with quality of experience support |
title | A multi-tier fog content orchestrator mechanism with quality of experience support |
title_full | A multi-tier fog content orchestrator mechanism with quality of experience support |
title_fullStr | A multi-tier fog content orchestrator mechanism with quality of experience support |
title_full_unstemmed | A multi-tier fog content orchestrator mechanism with quality of experience support |
title_short | A multi-tier fog content orchestrator mechanism with quality of experience support |
title_sort | multi-tier fog content orchestrator mechanism with quality of experience support |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7202856/ http://dx.doi.org/10.1016/j.comnet.2020.107288 |
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