Computation of traffic time series for large populations of IoT devices
| dc.contributor.author | Izal Azcárate, Mikel | |
| dc.contributor.author | Morató Osés, Daniel | |
| dc.contributor.author | Magaña Lizarrondo, Eduardo | |
| dc.contributor.author | García-Jiménez, Santiago | |
| dc.contributor.department | Ingeniaritza Elektrikoa, Elektronikoaren eta Telekomunikazio Ingeniaritzaren | eu |
| dc.contributor.department | Institute of Smart Cities - ISC | en |
| dc.contributor.department | Ingeniería Eléctrica, Electrónica y de Comunicación | es_ES |
| dc.date.accessioned | 2019-02-21T10:47:29Z | |
| dc.date.available | 2019-02-21T10:47:29Z | |
| dc.date.issued | 2018 | |
| dc.description.abstract | En este artículo se estudian las tecnicas para clasificar paquetes de tráfico de red en múltiples clases orientadas a la realización de series temporales de tráfico en escenarios de un elevado numero de clases como pueden ser los proveedores de red para dispositivos IoT. Se muestra que usando técnicas basadas en DStries se pueden monitorizar en tiempo real redes con decenas de miles de dispositivos. | es_ES |
| dc.description.abstract | In this work we study multi class packet classification algorithms to be used in network traffic time series extraction. This study is done for scenarios with a large number of time series to extract such as in monitoring IoT network providers. We show that using DStries based techniques, large networks with tens of thousands of devices can be monitored in real time. | en |
| dc.description.sponsorship | This work is funded by Spanish MINECO through project PIT (TEC2015-69417-C2-2-R). | en |
| dc.format.extent | 16 p. | |
| dc.format.mimetype | application/pdf | en |
| dc.identifier.doi | 10.3390/s19010078 | |
| dc.identifier.issn | 1424-8220 (Electronic) | |
| dc.identifier.uri | https://academica-e.unavarra.es/handle/2454/32350 | |
| dc.language.iso | eng | en |
| dc.publisher | MDPI | en |
| dc.relation.ispartof | Sensors, 2019, 19, 78 | en |
| dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//TEC2015-69417-C2-2-R/ES/ | |
| dc.relation.publisherversion | https://doi.org/10.3390/s19010078 | |
| dc.rights | © 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/). | en |
| dc.rights.accessRights | info:eu-repo/semantics/openAccess | |
| dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | IoT | en |
| dc.subject | Network traffic | en |
| dc.subject | Monitoring | en |
| dc.subject | DDoS | en |
| dc.subject | Packet classification | en |
| dc.title | Computation of traffic time series for large populations of IoT devices | en |
| dc.type | info:eu-repo/semantics/article | |
| dc.type.version | info:eu-repo/semantics/publishedVersion | |
| dspace.entity.type | Publication | |
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