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Pricing based MEC resource allocation for 5g heterogeneous network access

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Autor
Passas V., Makris N., Miliotis V., Korakis T.
Datum
2019
Language
en
DOI
10.1109/GLOBECOM38437.2019.9014154
Schlagwort
Costs
Economics
Energy efficiency
Heterogeneous networks
Internet service providers
Mobile telecommunication systems
Resource allocation
Unmanned aerial vehicles (UAV)
Computational resources
Cyclic recharging and reshuffling strategy (CRRS)
Efficient allocations
Multiple technology
Multiple wireless technologies
Resource allocation problem
Testbed experimentations
Wireless technologies
Next generation networks
Institute of Electrical and Electronics Engineers Inc.
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Zusammenfassung
Multi-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.
URI
http://hdl.handle.net/11615/77961
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