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Building Realistic Experimentation Environments for AI-enhanced Management and Orchestration (MANO) of 5G and beyond V2X systems

Authors: Slamnik-Kriještorac, Nina; Camelo, Miguel; Cominardi, Luca; Latré, Steven; Marquez-Barja, Johann M.;

Building Realistic Experimentation Environments for AI-enhanced Management and Orchestration (MANO) of 5G and beyond V2X systems

Abstract

The plethora of heterogeneous and diversified services in 5G and beyond requires from networks to be flexible, adaptable, and programmable, i.e., to be able to correspondingly adapt to changes. As human intervention might significantly increase delays in MANagement and Orchestration (MANO) operations, automation and intelligence become imperative for orchestrating services and resources, especially the ones with stringent requirements for latency and capacity, such as Vehicle-to-Everything (V2X) services. As virtualization and Artificial Intelligence (AI) promise to mitigate those challenges towards enabling true automation in MANO operations, in this paper we present our effort towards building and fully utilizing the reallife testbeds, such as Smart Highway and Virtual Wall, located in Belgium, to conduct realistic experimentation and validation of distributed orchestration intelligence in a dynamic network such as V2X system.

This work has been performed in the framework of the European Union's Horizon 2020 project DAEMON co-funded by the EU under grant agreement No. 101017109, the Horizon 2020 Fed4FIRE+ project, Grant Agreement No. 723638, and the Horizon 2020 5G-Blueprint project under Agreement No. 952189.

Country
Belgium
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Keywords

NFV, testbeds, experimentation, AI, zenoh, mangement and orchestration, ML

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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