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dc.contributor.author | Hernández-Orallo, Enrique | es_ES |
dc.contributor.author | Murillo Arcila, Marina | es_ES |
dc.contributor.author | Cano, Juan-Carlos | es_ES |
dc.contributor.author | Tavares De Araujo Cesariny Calafate, Carlos Miguel | es_ES |
dc.contributor.author | Conejero, J. Alberto | es_ES |
dc.contributor.author | Manzoni, Pietro | es_ES |
dc.date.accessioned | 2020-10-07T03:35:40Z | |
dc.date.available | 2020-10-07T03:35:40Z | |
dc.date.issued | 2018 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/151318 | |
dc.description | (c) 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. | es_ES |
dc.description.abstract | [EN] The scarcity of bandwidth due to the explosive growth of mobile devices in 5G makes the offloading messaging workload to Wi-Fi devices that use opportunistic connections, a very promising solution. Communications in mobile opportunistic networks take place upon the establishment of ephemeral contacts among mobile nodes using direct communication. In this paper, we propose an analytical model based on population processes to evaluate data dissemination considering several parameters, such as user density, contact rate, and the number of fixed nodes. From this model, we obtain closed-form expressions for determining the diffusion time, the network coverage, and the waiting time. Newer 5G wireless technologies, such as WiGig, can offer multi-gigabit speeds, low latency, and security-protected connectivity between nearby devices. We therefore focus our work on the impact of high-speed and short-range wireless communications technologies for data dissemination in mobile opportunistic networks. Moreover, we test whether the coexistence with a fixed infrastructure can improve content dissemination, and thus justify its additional cost. Our results show that, when user density is high, the diffusion is mainly performed through the opportunistic contacts between mobile nodes, and that the diffusion coverage is close to 100%. Moreover, the diffusion is fast enough to dynamically update the information among all the participating members, so users do not need to get closer to fixed spots for receiving updated information. | es_ES |
dc.description.sponsorship | This work was supported in part by the Ministerio de Economa y Competitividad, Spain, under Grant TEC2014-52690-R, Grant MTM 2016-75963-P, and Grant SEV-2013-0323, in part by Generalitat Valenciana, Spain, under Grant AICO/2015/108 and Grant ACOMP/2015/005. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Institute of Electrical and Electronics Engineers | es_ES |
dc.relation.ispartof | IEEE Access | es_ES |
dc.rights | Reserva de todos los derechos | es_ES |
dc.subject | 5G mobile communication | es_ES |
dc.subject | Analytical models | es_ES |
dc.subject | Opportunistic networks | es_ES |
dc.subject | Contact-based messaging | es_ES |
dc.subject | Performance evaluation | es_ES |
dc.subject.classification | MATEMATICA APLICADA | es_ES |
dc.subject.classification | ARQUITECTURA Y TECNOLOGIA DE COMPUTADORES | es_ES |
dc.title | An Analytical Model Based on Population Processes to Characterize Data Dissemination in 5G Opportunistic Networks | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1109/ACCESS.2017.2779748 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//MTM2016-75963-P/ES/DINAMICA DE OPERADORES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//SEV-2013-0323/ES/-/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//TEC2014-52690-R/ES/INTEGRACION DEL SMARTPHONE Y EL VEHICULO PARA CONECTAR CONDUCTORES, SENSORES Y ENTORNO A TRAVES DE UNA ARQUITECTURA DE SERVICIOS FUNCIONALES/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//AICO%2F2015%2F108/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/GVA//ACOMP%2F2015%2F005/ | es_ES |
dc.rights.accessRights | Abierto | 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. Departamento de Informática de Sistemas y Computadores - Departament d'Informàtica de Sistemes i Computadors | es_ES |
dc.description.bibliographicCitation | Hernández-Orallo, E.; Murillo Arcila, M.; Cano, J.; Tavares De Araujo Cesariny Calafate, CM.; Conejero, JA.; Manzoni, P. (2018). An Analytical Model Based on Population Processes to Characterize Data Dissemination in 5G Opportunistic Networks. IEEE Access. 6:1603-1615. https://doi.org/10.1109/ACCESS.2017.2779748 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1109/ACCESS.2017.2779748 | es_ES |
dc.description.upvformatpinicio | 1603 | es_ES |
dc.description.upvformatpfin | 1615 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 6 | es_ES |
dc.identifier.eissn | 2169-3536 | es_ES |
dc.relation.pasarela | S\352946 | es_ES |
dc.contributor.funder | Generalitat Valenciana | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |