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Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems †

In sensor-based systems, the data of an object is often provided by multiple sources. Since the data quality of these sources might be different, when querying the observations, it is necessary to carefully select the sources to make sure that high quality data is accessed. A solution is to perform...

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Detalles Bibliográficos
Autores principales: Li, Mohan, Sun, Yanbin, Jiang, Yu, Tian, Zhihong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308571/
https://www.ncbi.nlm.nih.gov/pubmed/30567395
http://dx.doi.org/10.3390/s18124486
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author Li, Mohan
Sun, Yanbin
Jiang, Yu
Tian, Zhihong
author_facet Li, Mohan
Sun, Yanbin
Jiang, Yu
Tian, Zhihong
author_sort Li, Mohan
collection PubMed
description In sensor-based systems, the data of an object is often provided by multiple sources. Since the data quality of these sources might be different, when querying the observations, it is necessary to carefully select the sources to make sure that high quality data is accessed. A solution is to perform a quality evaluation in the cloud and select a set of high-quality, low-cost data sources (i.e., sensors or small sensor networks) that can answer queries. This paper studies the problem of min-cost quality-aware query which aims to find high quality results from multi-sources with the minimized cost. The measurement of the query results is provided, and two methods for answering min-cost quality-aware query are proposed. How to get a reasonable parameter setting is also discussed. Experiments on real-life data verify that the proposed techniques are efficient and effective.
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spelling pubmed-63085712019-01-04 Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems † Li, Mohan Sun, Yanbin Jiang, Yu Tian, Zhihong Sensors (Basel) Article In sensor-based systems, the data of an object is often provided by multiple sources. Since the data quality of these sources might be different, when querying the observations, it is necessary to carefully select the sources to make sure that high quality data is accessed. A solution is to perform a quality evaluation in the cloud and select a set of high-quality, low-cost data sources (i.e., sensors or small sensor networks) that can answer queries. This paper studies the problem of min-cost quality-aware query which aims to find high quality results from multi-sources with the minimized cost. The measurement of the query results is provided, and two methods for answering min-cost quality-aware query are proposed. How to get a reasonable parameter setting is also discussed. Experiments on real-life data verify that the proposed techniques are efficient and effective. MDPI 2018-12-18 /pmc/articles/PMC6308571/ /pubmed/30567395 http://dx.doi.org/10.3390/s18124486 Text en © 2018 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
Li, Mohan
Sun, Yanbin
Jiang, Yu
Tian, Zhihong
Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems †
title Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems †
title_full Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems †
title_fullStr Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems †
title_full_unstemmed Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems †
title_short Answering the Min-Cost Quality-Aware Query on Multi-Sources in Sensor-Cloud Systems †
title_sort answering the min-cost quality-aware query on multi-sources in sensor-cloud systems †
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6308571/
https://www.ncbi.nlm.nih.gov/pubmed/30567395
http://dx.doi.org/10.3390/s18124486
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