Abstract
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 AI-driven intent-based networking for autonomous robots is 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.
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Acknowledgments
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Grant Agreement No 101016681.
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Sophocleous, M. et al. (2022). AI-Driven Intent-Based Networking for 5G Enhanced Robot Autonomy. In: Maglogiannis, I., Iliadis, L., Macintyre, J., Cortez, P. (eds) Artificial Intelligence Applications and Innovations. AIAI 2022 IFIP WG 12.5 International Workshops. AIAI 2022. IFIP Advances in Information and Communication Technology, vol 652. Springer, Cham. https://doi.org/10.1007/978-3-031-08341-9_6
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