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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/67948

    Título
    Towards mobile edge computing: taxonomy, challenges, applications and future realms
    Autor
    Qadir, Junaid
    Sainz de Abajo, BeatrizAutoridad UVA Orcid
    Khan, Anwar
    García Zapirain, Begoña
    Torre Díez, Isabel de laAutoridad UVA
    Mahmood, Hasan
    Año del Documento
    2020
    Editorial
    IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC.
    Descripción
    Producción Científica
    Documento Fuente
    IEEE Access, Septiembre 2020, vol. 8, p. 189129-189162.
    Resumo
    The 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.
    Palabras Clave
    Mobile edge computing
    Smart cities
    ISSN
    2169-3536
    Revisión por pares
    SI
    DOI
    10.1109/ACCESS.2020.3026938
    Patrocinador
    Este 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.
    Version del Editor
    https://ieeexplore.ieee.org/document/9206025
    Propietario de los Derechos
    "© Todos los derechos reservados". Propietario de los derechos: IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC.
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/67948
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
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