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Experimental evaluation of a Follow-me MEC Cloud-Native 5G network

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Auteur
Tsourdinis T., Makris N., Korakis T.
Date
2021
Language
en
DOI
10.1109/5GWF52925.2021.00076
Sujet
Base stations
Mobile edge computing
Queueing networks
Radio access networks
Cloud-native
Edge computing
Follow-me multi-access edge computing
Kubernetes
Low latency
Multi-access edge computing
Multiaccess
Openairinterface
5G mobile communication systems
Institute of Electrical and Electronics Engineers Inc.
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Résumé
Cloud-native approaches for network functions In the 5G context have been embraced by the community, as they allow flexible management, reconfiguration and monitoring of the network in an end-to-end manner. As network softwarization extends to the RAN, empowered through the cellular stack disaggregation, even base station components can be executed as a cloud-native service. As low latency access is needed in the 5G and beyond networks for serving ultra Reliable Low Latency Communications, Multi-Access Edge Computing (MEC) needs to be integrated in the overall architecture. As the user moves among different RANs, the latency of accessing the service needs to be preserved for providing users with a seamless experience. To accomplish such behavior, migrations of the hosted services are needed, though not fully compatible with the cloud-native approach, and placing them closer to the network access point of the user. In this work, we experiment with a cloud-native end-to-end network, enhanced with Follow-me MEC functionalities. Heterogeneous access is provided at the RAN level, using disaggregated base stations, and MEC is integrated on the fronthaul of the network, ensuring low-latency access to services. The entire network is instantiated in a cloud-native manner, using a widely adopted container orchestration solution. Our results show that the scheme is able to provide low latency access to the hosted services, while the UE remains agnostic of the entire process and without any drops of the already established connections. © 2021 IEEE.
URI
http://hdl.handle.net/11615/80180
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