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dc.contributor.author | Naranjo-Delgado, Diana María | es_ES |
dc.contributor.author | Risco, Sebastián | es_ES |
dc.contributor.author | Moltó, Germán | es_ES |
dc.contributor.author | Blanquer Espert, Ignacio | es_ES |
dc.date.accessioned | 2023-12-05T19:03:33Z | |
dc.date.available | 2023-12-05T19:03:33Z | |
dc.date.issued | 2023-08-15 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/200525 | |
dc.description.abstract | [EN] Serverless computing and, in particular, the functions as a service model has become a convincing paradigm for the development and implementation of highly scalable applications in the cloud. This is due to the transparent management of three key functionalities: triggering of functions due to events, automatic provisioning and scalability of resources, and fine-grained pay-per-use. This article presents a serverless web-based scientific gateway to execute the inference phase of previously trained machine learning and artificial intelligence models. The execution of the models is performed both in Amazon Web Services and in on-premises clouds with the OSCAR framework for serverless scientific computing. In both cases, the computing infrastructure grows elastically according to the demand adopting scale-to-zero approaches to minimize costs. The web interface provides an improved user experience by simplifying the use of the models. The usage of machine learning in a computing platform that can use both on-premises clouds and public clouds constitutes a step forward in the adoption of serverless computing for scientific applications. | es_ES |
dc.description.sponsorship | AI-SPRINT "Artificial Intelligence in Secure PRIvacy-preserving computing coN-Tinuum", Grant/Award Number: 101016577; DEEP-Hybrid-DataCloud "Designing and Enabling E-infrastructures for intensive Processing in a Hybrid DataCloud", Grant/Award Number: 777435; SERCLOCO, Grant/Award Numbers: MCIN/AEI/10.13039/501100011033, PID2020-113126RB-I00 | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | John Wiley & Sons | es_ES |
dc.relation.ispartof | Concurrency and Computation: Practice and Experience (Online) | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Cloud computing | es_ES |
dc.subject | Function as a service | es_ES |
dc.subject | Machine learning | es_ES |
dc.subject | Serverless computing | es_ES |
dc.subject.classification | CIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIAL | es_ES |
dc.title | A serverless gateway for event-driven machine learning inference in multiple clouds | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1002/cpe.6728 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-113126RB-I00/ES/COMPUTACION CIENTIFICA SERVERLESS A TRAVES DEL HIBRIDO CONTINUO CLOUD/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/101016577/EU | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/EC/H2020/777435/EU | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica | es_ES |
dc.description.bibliographicCitation | Naranjo-Delgado, DM.; Risco, S.; Moltó, G.; Blanquer Espert, I. (2023). A serverless gateway for event-driven machine learning inference in multiple clouds. Concurrency and Computation: Practice and Experience (Online). 35(18):1-17. https://doi.org/10.1002/cpe.6728 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1002/cpe.6728 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 17 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 35 | es_ES |
dc.description.issue | 18 | es_ES |
dc.identifier.eissn | 1532-0634 | es_ES |
dc.relation.pasarela | S\452114 | es_ES |
dc.contributor.funder | AGENCIA ESTATAL DE INVESTIGACION | es_ES |
dc.contributor.funder | COMISION DE LAS COMUNIDADES EUROPEA | es_ES |
dc.relation.references | 10.31224/osf.io/u8xth | es_ES |
dc.relation.references | 10.1145/3127479.3128601 | es_ES |
dc.relation.references | 10.1002/spe.2966 | es_ES |
dc.relation.references | 10.5220/0010376500230033 | es_ES |
dc.relation.references | 10.1016/j.future.2019.02.057 | es_ES |
dc.relation.references | 10.1186/s13677-016-0054-z | es_ES |
dc.relation.references | 10.1145/3366623.3368135 | es_ES |
dc.relation.references | 10.1109/SERVICES.2019.00057 | es_ES |
dc.relation.references | 10.1145/3366623.3368139 | es_ES |
dc.relation.references | 10.3390/s21030928 | es_ES |
dc.relation.references | 10.1109/IC2E.2018.00052 | es_ES |
dc.relation.references | 10.1109/IC2E.2019.00-10 | es_ES |
dc.relation.references | 10.1109/SOCA.2019.00016 | es_ES |
dc.relation.references | 10.1109/ACCESS.2020.2985282 | es_ES |
dc.relation.references | 10.1145/3447545.3451181 | es_ES |
dc.relation.references | 10.1145/3065386 | es_ES |
dc.relation.references | 10.21105/joss.01517 | es_ES |
dc.relation.references | 10.1109/PDP.2013.32 | es_ES |
dc.relation.references | 10.1016/j.cpc.2018.05.021 | es_ES |
dc.relation.references | 10.1371/journal.pone.0177459 | es_ES |
dc.relation.references | 10.1145/3126908.3126925 | es_ES |
dc.relation.references | 10.1007/978-3-030-59851-8_23 | es_ES |
dc.relation.references | 10.1016/j.future.2018.01.022 | es_ES |
dc.relation.references | 10.3390/app11041438 | es_ES |
dc.relation.references | 10.1109/CLOUD.2019.00073 | es_ES |
dc.relation.references | 10.1016/j.jpdc.2020.01.004 | es_ES |
dc.relation.references | 10.1145/2830013.2830015 | es_ES |
dc.relation.references | 10.1109/CLUSTER.2015.76 | es_ES |