Published December 21, 2022
| Version 1.0
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D5.2 Preliminary integration for AI-based E2E network slicing control and MANO
Creators
- Kazmierowski, Alexandre1
- Kodjabachian, Jerome1
- Salva Garcia, Pablo2
- Matencio Escolar, Antonio2
- Sanchez Navarro, Ignacio2
- Khadmaoui-Bichouna, Mohamed2
- Alselek, Mohammed2
- Alcaraz Calero, Jose M.2
- Wang, Qi2
- Chen, Chieh-Chun3
- Ta Dang Khoa Le3
- Duarte, Paulo4
- Mendes, Bruno4
- Agbebiyi4
- Cosmas, John5
- Abbod, Maysam5
- Gavras, Anastasius6
- 1. Thales
- 2. University West of Scotland
- 3. Eurecom
- 4. CAP
- 5. University Brunel
- 6. Eurescom
Description
This document reports the up-to-date progress towards achieving smart E2E network slicing. It focuses on the prototyping of enabling technologies for E2E network slicing across network segments, their intent-based Management and Orchestration, and AI-based RAN resource allocation enabled with the Cognitive Plane’s Multi-Agent Deep Reinforcement Learning platform. Moreover, it covers preliminary integration work between different network slicing enablers over the E2E data path, with the MANO plane, and with the MA-DRL platform. Together, these technological enablers, algorithmic advances and initial integration work lay down the foundation for implementing the targeting E2E slicing system.
Files
D5.2 Preliminary integration for AI-based E2E network slicing control and MANO.pdf
Files
(5.9 MB)
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