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5G-IANA: A 5G Experimentation Platform for Intelligent Automotive Network Applications

Authors: Sourlas, Vasilis; Katsaros, Konstantinos; Xirofotos, Athanasios; Klonidis, Dimitrios; Bonetto, Edoardo; Brevi, Daniele; Scopigno, Roberto; +7 Authors

5G-IANA: A 5G Experimentation Platform for Intelligent Automotive Network Applications

Abstract

This paper presents the development of an open 5G experimentation platform, on top of which third-party experimenters (i.e., SMEs) in the Automotive sector will have the opportunity to develop, deploy and test their services. An Automotive Open Experimental Platform (AOEP) is specified, as a set of hardware and software resources that provides the compute and communication/transport infrastructure as well as the management and orchestration components, coupled with an enhanced Network Application (NetApp) Toolkit tailored to the Automotive sector. The platform exposes secure and standardized APIs to experimenters, to facilitate the different steps towards the production stage of a new automotive service. The platform, being part of the H2020 5G-IANA project, targets different MANO solutions integrating a range of virtualization technologies for enabling the deployment of the end-to-end network services across domains (vehicles, road infrastructure, MEC nodes and cloud resources). The NetApp toolkit is linked with a new Automotive VNFs Repository equipped with an extended list of ready-to-use, open, accessible Automotive-related VNFs and NetApp templates, that forms a repository for SMEs to use and develop new applications. A distributed AI/ML (DML) framework as part of the platform provides functionalities for simplified management and orchestration of collections of AI/ML service components allowing ML-based applications to penetrate the Automotive world.

Keywords

#5GIANA #AOEP #Netapp #DML #automotive

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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).
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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.
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