RT Journal Article
T1 A novel transversal processing model to build environmental big data services in the cloud
A1 Barrón Lugo, Juan Armando
A1 Gonzalez-Compean, Jose Luis
A1 Carretero Pérez, Jesús
A1 López Arévalo, Iván
A1 Montella, Raffaele
AB This 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.
PB Elsevier
SN 1364-8152
YR 2021
FD 2021-10
LK https://hdl.handle.net/10016/33774
UL https://hdl.handle.net/10016/33774
LA eng
NO This 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.
DS e-Archivo
RD 28 may. 2024