Εμφάνιση απλής εγγραφής

dc.creatorPassas V., Makris N., Miliotis V., Korakis T.en
dc.date.accessioned2023-01-31T09:46:04Z
dc.date.available2023-01-31T09:46:04Z
dc.date.issued2019
dc.identifier10.1109/GLOBECOM38437.2019.9014154
dc.identifier.isbn9781728109626
dc.identifier.urihttp://hdl.handle.net/11615/77961
dc.description.abstractMulti-access Edge Computing (MEC) is expected to play an important role in next generation networks, as it is able to provide resources accessible through multiple wireless technologies located close to the network edge. MEC is therefore an enabler for low-latency applications, allowing novel time critical services to be offered through mobile networks. Nevertheless, hosting multiple service providers over the same physical infrastructure shall carefully consider the needs of the MEC enabled applications. Moreover, different suggested placements for the MEC service provide fertile ground for the differentiation of the hosted service providers. In the meantime, the integration of multiple technologies in the wireless access of the MEC concept is increasing the complexity for efficient allocation of network and computational resources among the involved stakeholders. In this work, we model the MEC resource allocation problem for different service providers by using a pricing scheme. We consider two different deployments for the MEC services when considering a multi-technology Cloud-RAN base station: either at the fronthaul interface or located at the Core Network. We integrate intelligence to the MEC enabled framework, by considering the available links through which each client is served. We employ testbed experimentation in order to illustrate the efficiency of our scheme and demonstrate how we achieve efficient allocation of the MEC resources and wireless technologies used for the system under consideration. © 2019 IEEE.en
dc.language.isoenen
dc.source2019 IEEE Global Communications Conference, GLOBECOM 2019 - Proceedingsen
dc.source.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85081967501&doi=10.1109%2fGLOBECOM38437.2019.9014154&partnerID=40&md5=e01ced8c99e2d51d0a6803691c0a6b70
dc.subjectCostsen
dc.subjectEconomicsen
dc.subjectEnergy efficiencyen
dc.subjectHeterogeneous networksen
dc.subjectInternet service providersen
dc.subjectMobile telecommunication systemsen
dc.subjectResource allocationen
dc.subjectUnmanned aerial vehicles (UAV)en
dc.subjectComputational resourcesen
dc.subjectCyclic recharging and reshuffling strategy (CRRS)en
dc.subjectEfficient allocationsen
dc.subjectMultiple technologyen
dc.subjectMultiple wireless technologiesen
dc.subjectResource allocation problemen
dc.subjectTestbed experimentationsen
dc.subjectWireless technologiesen
dc.subjectNext generation networksen
dc.subjectInstitute of Electrical and Electronics Engineers Inc.en
dc.titlePricing based MEC resource allocation for 5g heterogeneous network accessen
dc.typeconferenceItemen


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