AI-driven intent-based networking for 5G enhanced robot autonomy

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F22%3APU147263" target="_blank" >RIV/00216305:26230/22:PU147263 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-031-08341-9_6" target="_blank" >http://dx.doi.org/10.1007/978-3-031-08341-9_6</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-08341-9_6" target="_blank" >10.1007/978-3-031-08341-9_6</a>

Jazyk výsledku

angličtina

Název v původním jazyce

AI-driven intent-based networking for 5G enhanced robot autonomy

Popis výsledku v původním jazyce

Innovative 5G orchestration architectures so far, have been mainly designed and optimized for Quality of Service (QoS), but are not aware of Quality of Experience (QoE). This makes intent recognition and End-to-End interpretability an inherited problem for orchestration systems, leading to possible creation of ineffective control policies. In this paper, an intent-based networking for autonomous robots is being proposed and demonstrated through the 5G-ERA project. In particular, to map an intent from individual vertical action to a global OSM control policy, a workflow of four tools is proposed: i) Action Sequence Generation, ii) Network Intent Estimation, iii) Resource Usage Forecasting, and iv) OSM Control Policy Generation. All of these tools are described in the paper with specific function descriptions, inputs, outputs and the semantic models/Machine Learning tools that have been used. Finally, the paper presents the developed intent-based dashboard for the visualization of the tools outputs, whilst taking QoE into consideration.

Název v anglickém jazyce

AI-driven intent-based networking for 5G enhanced robot autonomy

Popis výsledku anglicky

Innovative 5G orchestration architectures so far, have been mainly designed and optimized for Quality of Service (QoS), but are not aware of Quality of Experience (QoE). This makes intent recognition and End-to-End interpretability an inherited problem for orchestration systems, leading to possible creation of ineffective control policies. In this paper, an intent-based networking for autonomous robots is being proposed and demonstrated through the 5G-ERA project. In particular, to map an intent from individual vertical action to a global OSM control policy, a workflow of four tools is proposed: i) Action Sequence Generation, ii) Network Intent Estimation, iii) Resource Usage Forecasting, and iv) OSM Control Policy Generation. All of these tools are described in the paper with specific function descriptions, inputs, outputs and the semantic models/Machine Learning tools that have been used. Finally, the paper presents the developed intent-based dashboard for the visualization of the tools outputs, whilst taking QoE into consideration.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2022

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

AIAI 2022 IFIP WG 12.5 International Workshops

ISBN

—

ISSN

1868-4238

e-ISSN

1868-422X

Počet stran výsledku

10

Strana od-do

61-70

Název nakladatele

Springer Nature Switzerland AG

Místo vydání

Cham

Místo konání akce

Kréta

Datum konání akce

17. 6. 2022

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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