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A novel transversal processing model to build environmental big data services in the cloud

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dc.affiliation.dptoUC3M. Departamento de Informáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Arquitectura de Computadores, Comunicaciones y Sistemases
dc.contributor.authorBarrón Lugo, Juan Armando
dc.contributor.authorGonzalez-Compean, Jose Luis
dc.contributor.authorCarretero Pérez, Jesús
dc.contributor.authorLópez Arévalo, Iván
dc.contributor.authorMontella, Raffaele
dc.date.accessioned2021-12-15T13:06:39Z
dc.date.available2023-10-01T23:00:05Z
dc.date.issued2021-10
dc.description.abstractThis paper presents a novel transversal, agnostic-infrastructure, and generic processing model to build environmental big data services in the cloud. Transversality is used for building processing structures (PS) by reusing/coupling multiple existent software for processing environmental monitoring, climate, and earth observation data, even in execution time, with datasets available in cloud-based repositories. Infrastructure-agnosticism is used for deploying/executing PSs on/in edge, fog, and/or cloud. Genericity is used to embed analytic, merging information, machine learning, and statistic micro-services into PSs for automatically and transparently converting PSs into big data services to support decision-making procedures. A prototype was developed for conducting case studies based on the data climate classification, earth observation products, and making predictions of air data pollution by merging different monitoring climate data sources. The experimental evaluation revealed the efficacy and flexibility of this model to create complex environmental big data services.en
dc.description.sponsorshipThis work has been partially supported by the project 41756 "Plataforma tecnológica para la gestión, aseguramiento, intercambio y preservación de grandes volúmenes de datos en salud y construcción de un repositorio nacional de servicios de análisis de datos de salud" by the FORDECYT-PRONACES.en
dc.format.extent17
dc.identifier.bibliographicCitationArmando Barron-Lugo, J., Gonzalez-Compean, J. L., Carretero, J., Lopez-Arevalo, I. & Montella, R. (2021). A novel transversal processing model to build environmental big data services in the cloud. Environmental Modelling & Software, 144, 105173.en
dc.identifier.doihttps://doi.org/10.1016/j.envsoft.2021.105173
dc.identifier.issn1364-8152
dc.identifier.publicationfirstpage1
dc.identifier.publicationissue105173
dc.identifier.publicationlastpage17
dc.identifier.publicationtitleEnvironmental Modelling & Softwareen
dc.identifier.publicationvolume144
dc.identifier.urihttps://hdl.handle.net/10016/33774
dc.identifier.uxxiAR/0000028875
dc.language.isoengen
dc.publisherElsevieren
dc.rights© 2021 Elsevier Ltd. All rights reserved.en
dc.rightsAtribución-NoComercial-SinDerivadas 3.0 España*
dc.rights.accessRightsopen accessen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/*
dc.subject.ecienciaInformáticaes
dc.subject.otherBig dataen
dc.subject.otherCloud computingen
dc.subject.otherEnvironmental dataen
dc.subject.otherClimate dataen
dc.subject.otherMachine learningen
dc.subject.otherData analyticen
dc.titleA novel transversal processing model to build environmental big data services in the clouden
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
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