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dc.contributor.author | Silvestre-Blanes, Javier | es_ES |
dc.contributor.author | Sempere Paya, Víctor Miguel | es_ES |
dc.contributor.author | Albero Albero, Teresa | es_ES |
dc.date.accessioned | 2021-06-12T03:32:58Z | |
dc.date.available | 2021-06-12T03:32:58Z | |
dc.date.issued | 2020-03 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/167844 | |
dc.description.abstract | [EN] 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%. | es_ES |
dc.description.sponsorship | This work has been supported by the MCyU (Spanish Ministry of Science and Universities) under the project ATLAS (PGC2018-094151-B-I00), which is partially funded by AEI, FEDER and EU. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | MDPI AG | es_ES |
dc.relation.ispartof | Sensors | es_ES |
dc.rights | Reconocimiento (by) | es_ES |
dc.subject | IoMT | es_ES |
dc.subject | Governor | es_ES |
dc.subject | Edge computing | es_ES |
dc.subject | Near sensor computing | es_ES |
dc.subject.classification | ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES | es_ES |
dc.subject.classification | INGENIERIA TELEMATICA | es_ES |
dc.title | Smart Sensor Architectures for Multimedia Sensing in IoMT | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.3390/s20051400 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PGC2018-094151-B-I00/ES/SLICING DINAMICO EN REDES DE ACCESO RADIO 5G/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions | es_ES |
dc.description.bibliographicCitation | Silvestre-Blanes, J.; Sempere Paya, VM.; Albero Albero, T. (2020). Smart Sensor Architectures for Multimedia Sensing in IoMT. Sensors. 20(5):1-16. https://doi.org/10.3390/s20051400 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.3390/s20051400 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 16 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 20 | es_ES |
dc.description.issue | 5 | es_ES |
dc.identifier.eissn | 1424-8220 | es_ES |
dc.identifier.pmid | 32143389 | es_ES |
dc.identifier.pmcid | PMC7085541 | es_ES |
dc.relation.pasarela | S\406793 | es_ES |
dc.contributor.funder | European Regional Development Fund | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |
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