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

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
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

AI-Driven Orchestration of 6G-Enabled Services Across the Computing Continuum

Zenodo (CERN European Organization for Nuclear Research)
Software-Defined Networks and 5G
article

AI-Driven Orchestration of 6G-Enabled Services Across the Computing Continuum

article en

Abstract

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.

Zenodo (CERN European Organization for Nuclear Research)
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)
Affordable and clean energy
Openalex Percentile: Top 52%
Software-Defined Networks and 5G
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

AI-Driven Orchestration of 6G-Enabled Services Across the Computing Continuum · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS