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A Cognitive-Inspired Event-Based Control for Power-Aware Human Mobility Analysis in IoT Devices
Mobile Edge Computing (MEC) relates to the deployment of decision-making processes at the network edge or mobile devices rather than in a centralized network entity like the cloud. This paradigm shift is acknowledged as one key pillar to enable autonomous operation and self-awareness in mobile devic...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412476/ https://www.ncbi.nlm.nih.gov/pubmed/30781622 http://dx.doi.org/10.3390/s19040832 |
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author | Pérez-Torres, Rafael Torres-Huitzil, César Galeana-Zapién, Hiram |
author_facet | Pérez-Torres, Rafael Torres-Huitzil, César Galeana-Zapién, Hiram |
author_sort | Pérez-Torres, Rafael |
collection | PubMed |
description | Mobile Edge Computing (MEC) relates to the deployment of decision-making processes at the network edge or mobile devices rather than in a centralized network entity like the cloud. This paradigm shift is acknowledged as one key pillar to enable autonomous operation and self-awareness in mobile devices in IoT. Under this paradigm, we focus on mobility-based services (MBSs), where mobile devices are expected to perform energy-efficient GPS data acquisition while also providing location accuracy. We rely on a fully on-device Cognitive Dynamic Systems (CDS) platform to propose and evaluate a cognitive controller aimed at both tackling the presence of uncertainties and exploiting the mobility information learned by such CDS toward energy-efficient and accurate location tracking via mobility-aware sampling policies. We performed a set of experiments and validated that the proposed control strategy outperformed similar approaches in terms of energy savings and spatio-temporal accuracy in LBS and MBS for smartphone devices. |
format | Online Article Text |
id | pubmed-6412476 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-64124762019-04-03 A Cognitive-Inspired Event-Based Control for Power-Aware Human Mobility Analysis in IoT Devices Pérez-Torres, Rafael Torres-Huitzil, César Galeana-Zapién, Hiram Sensors (Basel) Article Mobile Edge Computing (MEC) relates to the deployment of decision-making processes at the network edge or mobile devices rather than in a centralized network entity like the cloud. This paradigm shift is acknowledged as one key pillar to enable autonomous operation and self-awareness in mobile devices in IoT. Under this paradigm, we focus on mobility-based services (MBSs), where mobile devices are expected to perform energy-efficient GPS data acquisition while also providing location accuracy. We rely on a fully on-device Cognitive Dynamic Systems (CDS) platform to propose and evaluate a cognitive controller aimed at both tackling the presence of uncertainties and exploiting the mobility information learned by such CDS toward energy-efficient and accurate location tracking via mobility-aware sampling policies. We performed a set of experiments and validated that the proposed control strategy outperformed similar approaches in terms of energy savings and spatio-temporal accuracy in LBS and MBS for smartphone devices. MDPI 2019-02-18 /pmc/articles/PMC6412476/ /pubmed/30781622 http://dx.doi.org/10.3390/s19040832 Text en © 2019 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 Pérez-Torres, Rafael Torres-Huitzil, César Galeana-Zapién, Hiram A Cognitive-Inspired Event-Based Control for Power-Aware Human Mobility Analysis in IoT Devices |
title | A Cognitive-Inspired Event-Based Control for Power-Aware Human Mobility Analysis in IoT Devices |
title_full | A Cognitive-Inspired Event-Based Control for Power-Aware Human Mobility Analysis in IoT Devices |
title_fullStr | A Cognitive-Inspired Event-Based Control for Power-Aware Human Mobility Analysis in IoT Devices |
title_full_unstemmed | A Cognitive-Inspired Event-Based Control for Power-Aware Human Mobility Analysis in IoT Devices |
title_short | A Cognitive-Inspired Event-Based Control for Power-Aware Human Mobility Analysis in IoT Devices |
title_sort | cognitive-inspired event-based control for power-aware human mobility analysis in iot devices |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6412476/ https://www.ncbi.nlm.nih.gov/pubmed/30781622 http://dx.doi.org/10.3390/s19040832 |
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