6G hyper-distributed edge-to-cloud continuum
hyper-distributed edge-to-cloud continuum, co2-aware, disaggregated ran, intelligence workload placement, digital twinning
The world economy is increasingly reliant on digital systems, leading to the emergence of new services. The 6G hyper-distributed edge-to-cloud continuum research aims to address these challenges using AI-based techniques. The goal is to create an energy-efficient, fully distributed, AI-powered platform that can manage thousands of multi-domain edge nodes. This research activity has three main sub-directions.
1) Energy-aware disaggregated radio access. Aims at developing an energy-aware disaggregated radio access network. It leverages strategies like network-based decision making, resource allocation, and energy-efficient hardware to reduce energy consumption. This leads to cost savings and environmental benefits.
2) Digital twinning for 6G. The research focuses on real-world data and synthetic traffic traces will be used to create accurate digital twins. Standardized approaches will be explored to enhance scalability and reliability, while the hyper-distributed edge-to-cloud continuum will ensure security and privacy of digital twin data.
3) Energy-efficient provision of AI-driven applications. The research focuses on AI-enabled application service orchestration, aiming to maximize its potential across multiple domains. The process also addresses environmental impact by reducing carbon footprint through CO2-aware deployment.
Research centers: University of Antwerp (BE), University of Ghent (BE), TU Berlin (DE), TU Munich (DE), University of Avignone (FR), Politecnico di Milano (IT), TU Wien (AS), IMEC (BE), TU delft (NE), University of Waterloo (CA), University of Campinas (BR), CNAM (FR), INRIA (FR), RISE (SK) – Compannies: Safran (DE), Italtel S.p.A. (IT), TIM S.p.A (IT), 8BELLS (CY), ATOS (ES), TurkCell (TU), Deutsche Telekom (DE), Ericsson (SK)
H2020 AI@EDGE (2021-2023)