Research Area

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.