A. Boudi, M. Bagaa, P. Pöyhönen, T. Taleb and H. Flinck, "AI-Based Resource Management in Beyond 5G Cloud Native Environment," in IEEE Network, vol. 35, no. 2, pp. 128-135, March/April 2021, doi: 10.1109/MNET.011.2000392
AI-based resource management in beyond 5G cloud native environment
|Author:||Boudi, Abderrahmane1; Bagaa, Miloud1; Pöyhönen, Petteri2;|
1Aalto University, Finland
2Nokia Bell Labs, FI-02610 Espoo, Finland
3University of Oulu, 90570 Oulu, Finland
4Sejong University, Seoul, Korea
|Online Access:||PDF Full Text (PDF, 1.7 MB)|
|Persistent link:|| http://urn.fi/urn:nbn:fi-fe2021053132254
Institute of Electrical and Electronics Engineers,
|Publish Date:|| 2021-05-31
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.
|Pages:||128 - 135|
|Type of Publication:||
A1 Journal article – refereed
|Field of Science:||
213 Electronic, automation and communications engineering, electronics
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.
|Academy of Finland Grant Number:||
318927 (Academy of Finland Funding decision)
311654 (Academy of Finland Funding decision)
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