Cargando…

Smart Sensor Architectures for Multimedia Sensing in IoMT

Today, a wide range of developments and paradigms require the use of embedded systems characterized by restrictions on their computing capacity, consumption, cost, and network connection. The evolution of the Internet of Things (IoT) towards Industrial IoT (IIoT) or the Internet of Multimedia Things...

Descripción completa

Detalles Bibliográficos
Autores principales: Silvestre-Blanes, Javier, Sempere-Payá, Víctor, Albero-Albero, Teresa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085541/
https://www.ncbi.nlm.nih.gov/pubmed/32143389
http://dx.doi.org/10.3390/s20051400
_version_ 1783508955387920384
author Silvestre-Blanes, Javier
Sempere-Payá, Víctor
Albero-Albero, Teresa
author_facet Silvestre-Blanes, Javier
Sempere-Payá, Víctor
Albero-Albero, Teresa
author_sort Silvestre-Blanes, Javier
collection PubMed
description Today, a wide range of developments and paradigms require the use of embedded systems characterized by restrictions on their computing capacity, consumption, cost, and network connection. The evolution of the Internet of Things (IoT) towards Industrial IoT (IIoT) or the Internet of Multimedia Things (IoMT), its impact within the 4.0 industry, the evolution of cloud computing towards edge or fog computing, also called near-sensor computing, or the increase in the use of embedded vision, are current examples of this trend. One of the most common methods of reducing energy consumption is the use of processor frequency scaling, based on a particular policy. The algorithms to define this policy are intended to obtain good responses to the workloads that occur in smarthphones. There has been no study that allows a correct definition of these algorithms for workloads such as those expected in the above scenarios. This paper presents a method to determine the operating parameters of the dynamic governor algorithm called Interactive, which offers significant improvements in power consumption, without reducing the performance of the application. These improvements depend on the load that the system has to support, so the results are evaluated against three different loads, from higher to lower, showing improvements ranging from 62% to 26%.
format Online
Article
Text
id pubmed-7085541
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-70855412020-03-23 Smart Sensor Architectures for Multimedia Sensing in IoMT Silvestre-Blanes, Javier Sempere-Payá, Víctor Albero-Albero, Teresa Sensors (Basel) Article Today, a wide range of developments and paradigms require the use of embedded systems characterized by restrictions on their computing capacity, consumption, cost, and network connection. The evolution of the Internet of Things (IoT) towards Industrial IoT (IIoT) or the Internet of Multimedia Things (IoMT), its impact within the 4.0 industry, the evolution of cloud computing towards edge or fog computing, also called near-sensor computing, or the increase in the use of embedded vision, are current examples of this trend. One of the most common methods of reducing energy consumption is the use of processor frequency scaling, based on a particular policy. The algorithms to define this policy are intended to obtain good responses to the workloads that occur in smarthphones. There has been no study that allows a correct definition of these algorithms for workloads such as those expected in the above scenarios. This paper presents a method to determine the operating parameters of the dynamic governor algorithm called Interactive, which offers significant improvements in power consumption, without reducing the performance of the application. These improvements depend on the load that the system has to support, so the results are evaluated against three different loads, from higher to lower, showing improvements ranging from 62% to 26%. MDPI 2020-03-04 /pmc/articles/PMC7085541/ /pubmed/32143389 http://dx.doi.org/10.3390/s20051400 Text en © 2020 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
Silvestre-Blanes, Javier
Sempere-Payá, Víctor
Albero-Albero, Teresa
Smart Sensor Architectures for Multimedia Sensing in IoMT
title Smart Sensor Architectures for Multimedia Sensing in IoMT
title_full Smart Sensor Architectures for Multimedia Sensing in IoMT
title_fullStr Smart Sensor Architectures for Multimedia Sensing in IoMT
title_full_unstemmed Smart Sensor Architectures for Multimedia Sensing in IoMT
title_short Smart Sensor Architectures for Multimedia Sensing in IoMT
title_sort smart sensor architectures for multimedia sensing in iomt
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7085541/
https://www.ncbi.nlm.nih.gov/pubmed/32143389
http://dx.doi.org/10.3390/s20051400
work_keys_str_mv AT silvestreblanesjavier smartsensorarchitecturesformultimediasensinginiomt
AT semperepayavictor smartsensorarchitecturesformultimediasensinginiomt
AT alberoalberoteresa smartsensorarchitecturesformultimediasensinginiomt