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dc.contributor.authorQadir, Junaid
dc.contributor.authorSainz de Abajo, Beatriz 
dc.contributor.authorKhan, Anwar
dc.contributor.authorGarcía Zapirain, Begoña
dc.contributor.authorTorre Díez, Isabel de la 
dc.contributor.authorMahmood, Hasan
dc.date.accessioned2024-06-01T19:48:33Z
dc.date.available2024-06-01T19:48:33Z
dc.date.issued2020
dc.identifier.citationIEEE Access, Septiembre 2020, vol. 8, p. 189129-189162.es
dc.identifier.issn2169-3536es
dc.identifier.urihttps://uvadoc.uva.es/handle/10324/67948
dc.descriptionProducción Científicaes
dc.description.abstractThe realm of cloud computing has revolutionized access to cloud resources and their utilization and applications over the Internet. However, deploying cloud computing for delay critical applications and reducing the delay in access to the resources are challenging. The Mobile Edge Computing (MEC) paradigm is one of the effective solutions, which brings the cloud computing services to the proximity of the edge network and leverages the available resources. This paper presents a survey of the latest and state-of-the-art algorithms, techniques, and concepts of MEC. The proposed work is unique in that the most novel algorithms are considered, which are not considered by the existing surveys. Moreover, the chosen novel literature of the existing researchers is classified in terms of performance metrics by describing the realms of promising performance and the regions where the margin of improvement exists for future investigation for the future researchers. This also eases the choice of a particular algorithm for a particular application. As compared to the existing surveys, the bibliometric overview is provided, which is further helpful for the researchers, engineers, and scientists for a thorough insight, application selection, and future consideration for improvement. In addition, applications related to the MEC platform are presented. Open research challenges, future directions, and lessons learned in area of the MEC are provided for further future investigation.es
dc.format.mimetypeapplication/pdfes
dc.language.isoenges
dc.publisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC.es
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subject.classificationMobile edge computinges
dc.subject.classificationSmart citieses
dc.titleTowards mobile edge computing: taxonomy, challenges, applications and future realmses
dc.typeinfo:eu-repo/semantics/articlees
dc.rights.holder"© Todos los derechos reservados". Propietario de los derechos: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC.es
dc.identifier.doi10.1109/ACCESS.2020.3026938es
dc.relation.publisherversionhttps://ieeexplore.ieee.org/document/9206025es
dc.identifier.publicationfirstpage189129es
dc.identifier.publicationlastpage189162es
dc.identifier.publicationtitleIEEE Accesses
dc.identifier.publicationvolume8es
dc.peerreviewedSIes
dc.description.projectEste trabajo ha sido financiado por el grupo de investigación eVida, de la Universidad de Deusto, como parte del proyecto de investigación: Grant IT 905-16.es
dc.identifier.essn2169-3536es
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones


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