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Managing the Quality of Experience in the Multimedia Internet of Things: A Layered-Based Approach †

This paper addresses the issue of evaluating the Quality of Experience (QoE) for Internet of Things (IoT) applications, with particular attention to the case where multimedia content is involved. A layered IoT architecture is firstly analyzed to understand which QoE influence factors have to be cons...

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Detalles Bibliográficos
Autores principales: Floris, Alessandro, Atzori, Luigi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5191038/
https://www.ncbi.nlm.nih.gov/pubmed/27918437
http://dx.doi.org/10.3390/s16122057
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author Floris, Alessandro
Atzori, Luigi
author_facet Floris, Alessandro
Atzori, Luigi
author_sort Floris, Alessandro
collection PubMed
description This paper addresses the issue of evaluating the Quality of Experience (QoE) for Internet of Things (IoT) applications, with particular attention to the case where multimedia content is involved. A layered IoT architecture is firstly analyzed to understand which QoE influence factors have to be considered in relevant application scenarios. We then introduce the concept of Multimedia IoT (MIoT) and define a layered QoE model aimed at evaluating and combining the contributions of each influence factor to estimate the overall QoE in MIoT applications. Finally, we present a use case related to the remote monitoring of vehicles during driving practices, which is used to validate the proposed layered model, and we discuss a second use case for smart surveillance, to emphasize the generality of the proposed framework. The effectiveness in evaluating classes of influence factors separately is demonstrated.
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spelling pubmed-51910382017-01-03 Managing the Quality of Experience in the Multimedia Internet of Things: A Layered-Based Approach † Floris, Alessandro Atzori, Luigi Sensors (Basel) Article This paper addresses the issue of evaluating the Quality of Experience (QoE) for Internet of Things (IoT) applications, with particular attention to the case where multimedia content is involved. A layered IoT architecture is firstly analyzed to understand which QoE influence factors have to be considered in relevant application scenarios. We then introduce the concept of Multimedia IoT (MIoT) and define a layered QoE model aimed at evaluating and combining the contributions of each influence factor to estimate the overall QoE in MIoT applications. Finally, we present a use case related to the remote monitoring of vehicles during driving practices, which is used to validate the proposed layered model, and we discuss a second use case for smart surveillance, to emphasize the generality of the proposed framework. The effectiveness in evaluating classes of influence factors separately is demonstrated. MDPI 2016-12-02 /pmc/articles/PMC5191038/ /pubmed/27918437 http://dx.doi.org/10.3390/s16122057 Text en © 2016 by the authors; 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Floris, Alessandro
Atzori, Luigi
Managing the Quality of Experience in the Multimedia Internet of Things: A Layered-Based Approach †
title Managing the Quality of Experience in the Multimedia Internet of Things: A Layered-Based Approach †
title_full Managing the Quality of Experience in the Multimedia Internet of Things: A Layered-Based Approach †
title_fullStr Managing the Quality of Experience in the Multimedia Internet of Things: A Layered-Based Approach †
title_full_unstemmed Managing the Quality of Experience in the Multimedia Internet of Things: A Layered-Based Approach †
title_short Managing the Quality of Experience in the Multimedia Internet of Things: A Layered-Based Approach †
title_sort managing the quality of experience in the multimedia internet of things: a layered-based approach †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5191038/
https://www.ncbi.nlm.nih.gov/pubmed/27918437
http://dx.doi.org/10.3390/s16122057
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