- -

Open Source Framework for Enabling HPC and Cloud Geoprocessing Services

RiuNet: Repositorio Institucional de la Universidad Politécnica de Valencia

Compartir/Enviar a

Citas

Estadísticas

  • Estadisticas de Uso

Open Source Framework for Enabling HPC and Cloud Geoprocessing Services

Mostrar el registro sencillo del ítem

Ficheros en el ítem

dc.contributor.author Montañana, José Miguel es_ES
dc.contributor.author Marangio, Paolo es_ES
dc.contributor.author Hervás, Antonio es_ES
dc.date.accessioned 2021-03-11T04:31:06Z
dc.date.available 2021-03-11T04:31:06Z
dc.date.issued 2020-12 es_ES
dc.identifier.uri http://hdl.handle.net/10251/163616
dc.description.abstract [EN] Geoprocessing is a set of tools that can be used to efficiently address several pressing chal-lenges for the global economy ranging from agricultural productivity, the design of transport networks, to the prediction of climate change and natural disasters. This paper describes an Open Source Framework developed, within three European projects, for Ena-bling High-Performance Computing (HPC) and Cloud geoprocessing services applied to agricultural challenges. The main goals of the European Union projects EUXDAT (EUro-pean e-infrastructure for eXtreme Data Analytics in sustainable developmenT), CYBELE (fostering precision agriculture and livestock farming through secure access to large-scale HPC-enabled virtual industrial experimentation environment empowering scalable big data analytics), and EOPEN (opEn interOperable Platform for unified access and analysis of Earth observatioN data) are to enable the use of large HPC systems, as well as big data management, user-friendly access and visualization of results. In addition, these projects focus on the development of software frameworks, and fuse Earth-observation data, such as Copernicus data, with non-Earth-observation data, such as weather, environmental and social media information. In this paper, we describe the agroclimatic-zones pilot used to validate the framework. Finally, performance metrics collected during the execution (up to 182 times speedup with 256 MPI processes) of the pilot are presented. es_ES
dc.description.sponsorship This work has been carried out within the context of the following projects: European e-infrastructure for extreme data ana-lytics in sustainable development (EUXDAT); Fostering precision agricul-ture and livestock farming through secure access to large-scale HPC-enabled virtual industrial experimentation environment empowering scalable big data analytic (CYBELE); Open interoperable platform for unified access and analysis of Earth observation data (EOPEN). Further information about the projects is available at the respective web pages (Nieto et al., 2020; Vingione et al., 2020; Davy et al., 2020). The research leading to these results has received funding from the European Unions Horizon 2020 Research and Innovation Programme, grant agreements n. 777549, 825355, 776019, respectively. es_ES
dc.language Inglés es_ES
dc.publisher Czech University of Life Sciences Prague es_ES
dc.relation.ispartof Agris on-line Papers in Economics and Informatics es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject High performance computing es_ES
dc.subject Cloud computing es_ES
dc.subject Big data es_ES
dc.subject Agriculture es_ES
dc.subject Land monitoring es_ES
dc.subject Geoprocessing es_ES
dc.subject.classification MATEMATICA APLICADA es_ES
dc.subject.classification ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES es_ES
dc.title Open Source Framework for Enabling HPC and Cloud Geoprocessing Services es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.7160/aol.2020.120405 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/776019/EU/EOPEN: opEn interOperable Platform for unified access and analysis of Earth observatioN data/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/777549/EU/European e-Infrastructure for Extreme Data Analytics in Sustainable Development/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/EC/H2020/825355/EU/FOSTERING PRECISION AGRICULTURE AND LIVESTOCK FARMING THROUGH SECURE ACCESS TO LARGE-SCALE HPC-ENABLED VIRTUAL INDUSTRIAL EXPERIMENTATION ENVIRONMENT EMPOWERING SCALABLE BIG DATA ANALYTICS/ es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Matemática Aplicada - Departament de Matemàtica Aplicada es_ES
dc.contributor.affiliation Universitat Politècnica de València. Instituto Universitario de Aplicaciones de las Tecnologías de la Información - Institut Universitari d'Aplicacions de les Tecnologies de la Informació es_ES
dc.description.bibliographicCitation Montañana, JM.; Marangio, P.; Hervás, A. (2020). Open Source Framework for Enabling HPC and Cloud Geoprocessing Services. Agris on-line Papers in Economics and Informatics. 12(4):61-76. https://doi.org/10.7160/aol.2020.120405 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.7160/aol.2020.120405 es_ES
dc.description.upvformatpinicio 61 es_ES
dc.description.upvformatpfin 76 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 12 es_ES
dc.description.issue 4 es_ES
dc.identifier.eissn 1804-1930 es_ES
dc.relation.pasarela S\424715 es_ES
dc.contributor.funder European Commission es_ES
dc.subject.ods 12.- Garantizar las pautas de consumo y de producción sostenibles es_ES


Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo del ítem