AI-Based Resource Management in beyond 5G Cloud Native Environment

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Journal ISSN
Volume Title
A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
Date
2021-03
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Mcode
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Language
en
Pages
8
128-135
Series
IEEE NETWORK, Volume 35, issue 2
Abstract
5G system and beyond targets a large number of emerging applications and services that will create extra overhead on network traffic. These industrial verticals have aggressive, contentious, and conflicting requirements that make the network have an arduous mission for achieving the desired objectives. It is expected to get requirements with close to zero time latency, high data rate, and network reliability. Fortunately, a ray of hope comes shining the way of telecom providers with the new progress and achievements in machine learning, cloud computing, micro-services, and the ETSI ZSM era. For this reason there is a colossal impetus from industry and academia toward applying these techniques by creating a new concept called CCN environment that can cohabit and adapt according to the network and resource state, and perceived KPIs. In this article, we pursue the aforementioned concept by providing a unified hierarchical closed-loop network and service management framework that can meet the desired objectives. We propose a cloud-na-tive simulator that accurately mimics cloud-native environments, and enables us to quickly evaluate new frameworks and ideas. The simulation results demonstrate the efficiency of our simulator for parroting the real testbeds in various metrics.
Description
Funding Information: AcknoWledgment s The research leading to these results received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement n°101016509 (project CHARITY). The article reflects only the authors’ views. The Commission is not responsible for any use that may be made of the information it contains. The research work is also partially funded by the Academy of Finland 6Genesis project under Grant No. 318927, and by the Academy of Finland CSN project under Grant No. 311654. Publisher Copyright: © 1986-2012 IEEE. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.
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Citation
Boudi, A, Bagaa, M, Pöyhönen, P, Taleb, T & Flinck, H 2021, ' AI-Based Resource Management in beyond 5G Cloud Native Environment ', IEEE Network, vol. 35, no. 2, 9373016, pp. 128-135 . https://doi.org/10.1109/MNET.011.2000392