D3.3 Release 2 of AI-driven inter-domain network control, management, and orchestration innovations

This document presents the advancements in the functional design of the AI-driven multi- stakeholder inter-domain control plane (AICP) under the PREDICT-6G framework. This release focuses on extending support for heterogeneous data planes, enabling the integration of multi-technology deterministic domains with seamless interoperability. AICP is empowered by four cornerstone enablers: i) AI/ML for dynamic resource optimization, ii) Digital Twins for predictive service performance and system modelling, iii) Enhanced data management for real-time monitoring and insights, and iv) Cross-domain orchestration for end-to-end lifecycle governance of deterministic services. Additionally, the document explores advanced methodologies to abstract and represent diverse underlying network technologies within the AICP framework, addressing a fundamental requirement for effective E2E service lifecycle management. You can read D3.1 here and D3.2 here.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-02-13
DOI
https://doi.org/10.5281/zenodo.14865229
Primary Topic
Cardiac Fibrosis and Remodeling
Type
article
Field-Weighted Citation Impact
0.00
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article

D3.3 Release 2 of AI-driven inter-domain network control, management, and orchestration innovations

Zenodo (CERN European Organization for Nuclear Research)
Cardiac Fibrosis and Remodeling
article

D3.3 Release 2 of AI-driven inter-domain network control, management, and orchestration innovations

article en

Abstract

This document presents the advancements in the functional design of the AI-driven multi- stakeholder inter-domain control plane (AICP) under the PREDICT-6G framework. This release focuses on extending support for heterogeneous data planes, enabling the integration of multi-technology deterministic domains with seamless interoperability. AICP is empowered by four cornerstone enablers: i) AI/ML for dynamic resource optimization, ii) Digital Twins for predictive service performance and system modelling, iii) Enhanced data management for real-time monitoring and insights, and iv) Cross-domain orchestration for end-to-end lifecycle governance of deterministic services. Additionally, the document explores advanced methodologies to abstract and represent diverse underlying network technologies within the AICP framework, addressing a fundamental requirement for effective E2E service lifecycle management. You can read D3.1 here and D3.2 here.

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 40%
Cardiac Fibrosis and Remodeling
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