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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/67226

    Título
    Joint fiber and MEC deployment for sparsely populated areas
    Autor
    Anzola Rojas, CamiloAutoridad UVA Orcid
    Miguel Jiménez, Ignacio deAutoridad UVA Orcid
    Aguado Manzano, Juan CarlosAutoridad UVA Orcid
    Merayo Álvarez, NoemíAutoridad UVA Orcid
    Fernández Reguero, PatriciaAutoridad UVA Orcid
    Durán Barroso, Ramón JoséAutoridad UVA Orcid
    Año del Documento
    2024
    Editorial
    Optica Publishing Group
    Descripción
    Producción Científica
    Documento Fuente
    Journal of Optical Communications and Networking, January 2024, vol. 16, no. 1, pp. 45-58
    Zusammenfassung
    The deployment of multi-access edge computing (MEC) networks gives rise to the MEC placement problem, which deals with finding the right server locations to reduce the cost and guarantee network performance. Multiple papers have been presented to solve this problem, but they are usually oriented to urban areas where short distances and high-quality network infrastructure are assumed. When this problem must be solved for sparsely populated areas, like rural environments, the connectivity is not always granted and the deployment of such connectivity using fiber technologies should be included in the problem. In contrast to urban areas, where the density of users is high and therefore the main problem is capacity, in sparsely populated areas, the problem lies in how to cost-effectively plan the MEC sites and the interconnecting network while meeting the delay constraints of the services offered through that network. This paper proposes a technique to solve the MEC placement problem considering the joint deployment of the optical network required to interconnect the base stations and the MEC servers. It consists of a three-phase scheme, which combines a spanning tree topology, for fiber deployment, with the use of mixed integer linear programming (MILP) formulations to minimize MEC servers and MEC data centers (MEC-DCs).We have applied the technique in a case study for a province in Spain (Valladolid, 8110 km2), obtaining a reduction of around 50% of the total cost when compared to a previous work. In addition, a clustering method is proposed to improve the scalability of the model for large scenarios. A simulation study is also presented to demonstrate the performance of the proposal assuming a 94;226 km2 region (Castilla y León) with 1576 base stations.
    ISSN
    1943-0620
    Revisión por pares
    SI
    DOI
    10.1364/JOCN.500429
    Patrocinador
    Ministerio de Ciencia e Innovación y Agencia Estatal de Investigación (Proyecto PID2020-112675RB-C42 financiado por MCIN/AEI/10.13039/501100011033)
    Consejería de Educación de la Junta de Castilla y León y FEDER (VA231P20)
    Version del Editor
    https://opg.optica.org/jocn/fulltext.cfm?uri=jocn-16-1-45&id=544821
    Propietario de los Derechos
    © 2024 Optica Publishing Group. Users may use, reuse, and build upon the article, or use the article for text or data mining, so long as such uses are for non-commercial purposes and appropriate attribution is maintained. All other rights are reserved.
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/67226
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
    Aparece en las colecciones
    • DEP71 - Artículos de revista [358]
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    Dateien zu dieser Ressource
    Nombre:
    202401_canzola_JOCN.pdf
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    13.39Mb
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