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Improving Signal-Strength Aggregation for Mobile Crowdsourcing Scenarios

Due to its huge impact on the overall quality of service (QoS) of wireless networks, both academic and industrial research have actively focused on analyzing the received signal strength in areas of particular interest. In this paper, we propose the improvement of signal-strength aggregation with a...

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Autores principales: Madariaga, Diego, Madariaga, Javier, Bustos-Jiménez, Javier, Bustos, Benjamin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7914496/
https://www.ncbi.nlm.nih.gov/pubmed/33562430
http://dx.doi.org/10.3390/s21041084
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author Madariaga, Diego
Madariaga, Javier
Bustos-Jiménez, Javier
Bustos, Benjamin
author_facet Madariaga, Diego
Madariaga, Javier
Bustos-Jiménez, Javier
Bustos, Benjamin
author_sort Madariaga, Diego
collection PubMed
description Due to its huge impact on the overall quality of service (QoS) of wireless networks, both academic and industrial research have actively focused on analyzing the received signal strength in areas of particular interest. In this paper, we propose the improvement of signal-strength aggregation with a special focus on Mobile Crowdsourcing scenarios by avoiding common issues related to the mishandling of log-scaled signal values, and by the proposal of a novel aggregation method based on interpolation. Our paper presents two clear contributions. First, we discuss the misuse of log-scaled signal-strength values, which is a persistent problem within the mobile computing community. We present the physical and mathematical formalities on how signal-strength values must be handled in a scientific environment. Second, we present a solution to the difficulties of aggregating signal strength in Mobile Crowdsourcing scenarios, as a low number of measurements and nonuniformity in spatial distribution. Our proposed method obtained consistently lower Root Mean Squared Error (RMSE) values than other commonly used methods at estimating the expected value of signal strength over an area. Both contributions of this paper are important for several recent pieces of research that characterize signal strength for an area of interest.
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spelling pubmed-79144962021-03-01 Improving Signal-Strength Aggregation for Mobile Crowdsourcing Scenarios Madariaga, Diego Madariaga, Javier Bustos-Jiménez, Javier Bustos, Benjamin Sensors (Basel) Article Due to its huge impact on the overall quality of service (QoS) of wireless networks, both academic and industrial research have actively focused on analyzing the received signal strength in areas of particular interest. In this paper, we propose the improvement of signal-strength aggregation with a special focus on Mobile Crowdsourcing scenarios by avoiding common issues related to the mishandling of log-scaled signal values, and by the proposal of a novel aggregation method based on interpolation. Our paper presents two clear contributions. First, we discuss the misuse of log-scaled signal-strength values, which is a persistent problem within the mobile computing community. We present the physical and mathematical formalities on how signal-strength values must be handled in a scientific environment. Second, we present a solution to the difficulties of aggregating signal strength in Mobile Crowdsourcing scenarios, as a low number of measurements and nonuniformity in spatial distribution. Our proposed method obtained consistently lower Root Mean Squared Error (RMSE) values than other commonly used methods at estimating the expected value of signal strength over an area. Both contributions of this paper are important for several recent pieces of research that characterize signal strength for an area of interest. MDPI 2021-02-05 /pmc/articles/PMC7914496/ /pubmed/33562430 http://dx.doi.org/10.3390/s21041084 Text en © 2021 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
Madariaga, Diego
Madariaga, Javier
Bustos-Jiménez, Javier
Bustos, Benjamin
Improving Signal-Strength Aggregation for Mobile Crowdsourcing Scenarios
title Improving Signal-Strength Aggregation for Mobile Crowdsourcing Scenarios
title_full Improving Signal-Strength Aggregation for Mobile Crowdsourcing Scenarios
title_fullStr Improving Signal-Strength Aggregation for Mobile Crowdsourcing Scenarios
title_full_unstemmed Improving Signal-Strength Aggregation for Mobile Crowdsourcing Scenarios
title_short Improving Signal-Strength Aggregation for Mobile Crowdsourcing Scenarios
title_sort improving signal-strength aggregation for mobile crowdsourcing scenarios
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7914496/
https://www.ncbi.nlm.nih.gov/pubmed/33562430
http://dx.doi.org/10.3390/s21041084
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