Publication:
Modeling Mobile Edge Computing Deployments for Low Latency Multimedia Services

Simple item page
dc.affiliation.dptoUC3M. Departamento de Ingeniería Telemáticaes
dc.affiliation.grupoinvUC3M. Grupo de Investigación: Network Technologieses
dc.contributor.authorMartín Pérez, Jorge
dc.contributor.authorCominardi, Luca
dc.contributor.authorBernardos Cano, Carlos Jesús
dc.contributor.authorOliva Delgado, Antonio de la
dc.contributor.authorAzcorra Saloña, Arturo
dc.contributor.funderEuropean Commissionen
dc.date.accessioned2019-04-03T09:50:59Z
dc.date.available2019-04-03T09:50:59Z
dc.date.issued2019-02-02
dc.description.abstractMulti-access edge computing (MEC) technologies bring important improvements in terms of network bandwidth, latency, and use of context information and critical for services like multimedia streaming, augmented, and virtual reality. In future deployments, operators will need to decide how many MEC points of presence (PoPs) are needed and where to deploy them, also considering the number of base stations needed to support the expected traffic. This paper presents an application of inhomogeneous Poisson point processes with hard-core repulsion to model feasible MEC infrastructure deployments. With the presented methodology a mobile network operator knows where to locate the MEC PoPs and associated base stations to support a given set of services. We evaluate our model with simulations in realistic scenarios, namely Madrid City Center, an industrial area and a rural area.en
dc.description.sponsorshipThis work was supported in part by EU H2020 5G-CORAL Project under Grant 761586, and in part by EU H2020 5G-TRANSFORMER Project under Grant 761536.en
dc.format.extent13
dc.format.mimetypeapplication/pdf
dc.identifier.bibliographicCitationMartín Pérez, J., Cominardi, L., Bernardos, C.J., Oliva, A. de la y Azcorra, A. (2019). Modeling Mobile Edge Computing Deployments for Low Latency Multimedia Services. IEEE Transactions on Broadcastingen
dc.identifier.doihttps://www.doi.org/10.1109/TBC.2019.2901406
dc.identifier.issn0018-9316
dc.identifier.publicationfirstpage1
dc.identifier.publicationlastpage11
dc.identifier.publicationtitleIEEE Transactions on Broadcastingen
dc.identifier.urihttps://hdl.handle.net/10016/28273
dc.identifier.uxxiAR/0000023249
dc.language.isoengen
dc.publisherIEEEen
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/761536
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/761586
dc.rights© 2019 IEEEen
dc.rights.accessRightsopen accessen
dc.subject.ecienciaTelecomunicacioneses
dc.subject.other5Gen
dc.subject.otherMecen
dc.subject.otherPoint Processen
dc.subject.otherDeploymenten
dc.subject.otherCharacterizationen
dc.subject.otherNetwork Slicingen
dc.subject.otherStreamingen
dc.subject.otherLow Latencyen
dc.subject.otherAugmented Realityen
dc.subject.otherVirtual Reality.en
dc.titleModeling Mobile Edge Computing Deployments for Low Latency Multimedia Servicesen
dc.typeresearch article*
dc.type.hasVersionAM*
dspace.entity.typePublication
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
modeling_IEEETB_2019_ps.pdf
Size:
1.26 MB
Format:
Adobe Portable Document Format
Download
Collections
DIT - RYSC - Artículos en Revistas Internacionales / International Journals
OpenAIRE: Open Access Infrastructure for Research in Europe