AI-driven zero touch network and service management in 5G and beyond : challenges and research directions |
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Author: | Benzaïd, Chafika1; Taleb, Tarik1,2,3 |
Organizations: |
1Aalto University, Espoo, Finland 2University of Oulu, Oulu, Finland 3Sejong University, Seoul, South Korea |
Format: | article |
Version: | accepted version |
Access: | open |
Online Access: | PDF Full Text (PDF, 0.8 MB) |
Persistent link: | http://urn.fi/urn:nbn:fi-fe2020110288926 |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers,
2020
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Publish Date: | 2020-11-02 |
Description: |
AbstractThe foreseen complexity in operating and managing 5G and beyond networks has propelled the trend toward closed-loop automation of network and service management operations. To this end, the ETSI Zero-touch network and Service Management (ZSM) framework is envisaged as a next-generation management system that aims to have all operational processes and tasks executed automatically, ideally with 100 percent automation. Artificial Intelligence (AI) is envisioned as a key enabler of self-managing capabilities, resulting in lower operational costs, accelerated time-tovalue and reduced risk of human error. Nevertheless, the growing enthusiasm for leveraging AI in a ZSM system should not overlook the potential limitations and risks of using AI techniques. The current paper aims to introduce the ZSM concept and point out the AI-based limitations and risks that need to be addressed in order to make ZSM a reality. see all
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Series: |
IEEE network |
ISSN: | 0890-8044 |
ISSN-E: | 1558-156X |
ISSN-L: | 0890-8044 |
Volume: | 34 |
Issue: | 2 |
Pages: | 186 - 194 |
Article number: | 8994961 |
DOI: | 10.1109/MNET.001.1900252 |
OADOI: | https://oadoi.org/10.1109/MNET.001.1900252 |
Type of Publication: |
A1 Journal article – refereed |
Field of Science: |
213 Electronic, automation and communications engineering, electronics |
Subjects: | |
Funding: |
This work was supported in part by the Academy of Finland Project 6Genesis Flagship (Grant No. 318927), CSN (Grant No. 311654) and the European Union’s Horizon 2020 research and innovation programme under the INSPIRE-5Gplus project (Grant No. 871808). |
EU Grant Number: |
(871808) INSPIRE-5Gplus - INtelligent Security and PervasIve tRust for 5G and Beyond |
Academy of Finland Grant Number: |
318927 |
Detailed Information: |
318927 (Academy of Finland Funding decision) |
Copyright information: |
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