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dc.contributor.author | Borrego, Carlos | es_ES |
dc.contributor.author | Hernández-Orallo, Enrique | es_ES |
dc.contributor.author | Magaia, Naercio | es_ES |
dc.date.accessioned | 2020-05-13T03:02:45Z | |
dc.date.available | 2020-05-13T03:02:45Z | |
dc.date.issued | 2019-10 | es_ES |
dc.identifier.issn | 1570-8705 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/143001 | |
dc.description.abstract | [EN] In the context of Opportunistic Networking (OppNet), routing and delivery algorithms used for content dissemination employ different metrics to perform accurate decisions. It has been shown that of these metrics, the inter-contact time and the contact duration are very useful for characterising OppNet scenarios. In this article, we show that the exponential moving averages of the historical values of these metrics are correlated with future observed values, in addition to also being good estimators for them. Moreover, we go a step further to investigate how to locally, from the OppNet node perspective, improve the estimations for these metrics by defining two novel estimation functions. These estimation functions are based on two different linear models: a general regression model and a mixed regression model, where future values of the studied metrics are explained in terms of their corresponding exponential moving averages. Experimentation using real mobility traces from well-known OppNet scenarios show that our estimation functions greatly reduce the estimation error of the future values of both metrics when compared to representative state of the art proposals. (C) 2019 Elsevier B.V. All rights reserved. | es_ES |
dc.description.sponsorship | This work was supported by LASIGE Research Unit, ref. UlD/CE000408/2013, by the Catalan AGAUR 2017SGR-463 project and the Spanish Ministry of Science and Innovation TIN2017-87211-R project. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Ad Hoc Networks | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | Opportunistic networks | es_ES |
dc.subject | Inter-contact time | es_ES |
dc.subject | Contact duration | es_ES |
dc.subject | Regression models | es_ES |
dc.subject | Mixed models | es_ES |
dc.subject.classification | ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES | es_ES |
dc.title | General and mixed linear regressions to estimate inter-contact times and contact duration in opportunistic networks | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.adhoc.2019.101927 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-87211-R/ES/PLATAFORMA SEGURA CROWD2CROWD PARA APLICACIONES DE TRANPORTE INTELIGENTE OPORTUNISTAS Y DESCENTRALIZADAS/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/ULISBOA//UlD%2FCE000408%2F2013/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/Generalitat de Catalunya//2017 SGR 463/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors | es_ES |
dc.description.bibliographicCitation | Borrego, C.; Hernández-Orallo, E.; Magaia, N. (2019). General and mixed linear regressions to estimate inter-contact times and contact duration in opportunistic networks. Ad Hoc Networks. 93:1-11. https://doi.org/10.1016/j.adhoc.2019.101927 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.adhoc.2019.101927 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 11 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 93 | es_ES |
dc.relation.pasarela | S\390296 | es_ES |
dc.contributor.funder | Universidade de Lisboa, Portugal | es_ES |
dc.contributor.funder | Agencia de Gestión de Ayudas Universitarias y de Investigación | es_ES |
dc.contributor.funder | Agencia Estatal de Investigación | es_ES |