AI-driven Zero Touch Network and Service Management in 5G and Beyond: Challenges and Research Directions
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A1 Alkuperäisartikkeli tieteellisessä aikakauslehdessä
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2020-02
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Language
en
Pages
9
186 - 194
186 - 194
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IEEE NETWORK, Volume 34, issue 2
Abstract
The 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.Description
| openaire: EC/H2020/871808/EU//INSPIRE-5Gplus
Keywords
5G, ZSM, Artificial intelligence, Machine learning, Network management
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Citation
Benzaid, C & Taleb, T 2020, ' AI-driven Zero Touch Network and Service Management in 5G and Beyond: Challenges and Research Directions ', IEEE Network, vol. 34, no. 2, pp. 186 - 194 . https://doi.org/10.1109/MNET.001.1900252