AI-Driven Orchestration of 6G-Enabled Services Across the Computing Continuum
The emergence of 6G mobile communications promises transformative advancements powered by Artificial Intelligence (AI) and Machine Learning (ML). However, these capabilities introduce significant challenges, mainly due to the heterogeneous nature of 6G-enabled environments. This paper presents an AI-driven orchestration framework designed to address the complexities of future 6G infrastructures. The proposed framework orchestrates microservice-based applications across diverse layers of the computing continuum and performs key tasks such as service placement, computation offloading, horizontal scaling, and live migration, leveraging AI to enhance performance, energy efficiency, and automation. Additionally, it incorporates Distributed Ledger Technology (DLT) to enable federated service management when centralized control is impractical. We validate this approach through experimental trials with a latency-sensitive 6G application, analyzing intra- and interdomain orchestration, proactive extreme edge migration, and inter-cluster communication technologies. A set of representative workflows are provided as open-source implementations.
Institutions
- National Technical University of Athens (GR)
- Atos (Spain) (ES)
- Gemeente Den Haag (NL)
- Institute of Communication and Computer Systems (GR)
- Universidad Carlos III de Madrid (ES)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-05-01
- DOI
- https://doi.org/10.5281/zenodo.15790204
- Primary Topic
- Software-Defined Networks and 5G
- Type
- article
- Field-Weighted Citation Impact
- 0.00