Automation of Network edge Infrastructure & Applications with Artificial Intelligence
Project Status: finished
Start Date: June 2021
End Date: January 2024
Budget (total): 11214 K€
Effort: 81.66 PY
Project-ID: C2019/3-2
Ericsson AB (EAB), Sweden
Arctoslabs AB, Sweden
Chalmers University of Technology (CTH), Sweden
Enoc System AB, Sweden
Royal Institute of Technology, KTH (Kungliga Tekniska Högskolan), Sweden
Hopsworks, Sweden
Qamcom Research and Technology AB, Sweden
RI.SE Research Institutes of Sweden AB, Sweden
Systemair AB, Sweden
Univrses AB, Sweden
Delta Electronics, Sweden
Kings College London, United Kingdom
HAL Robotics, United Kingdom
Konica-Minolta, United Kingdom
Opel Automobile GmbH, Germany
Technical University Braunschweig, Germany
Fraunhofer IPT, Germany
Fraunhofer IST, Germany
IconPro GmbH, Germany
Abstract
Digital transformation is ongoing in many areas of today’s society, which will impact many aspects of people’s lives via means such as smart cities, robotic, transportation, and next-generation industries. At the same time, the current centralized cloud infrastructure is not adequate to serve the transformation’s requirements. We believe that three technologies can come together to shape a new secure service and application platform; 5G, edge-centric compute & artificial intelligence. In this context, European industry has a good position in 5G networks, transportation and industrial applications, but need to strengthen the position in a secure cloud, data centre and artificial intelligence technologies to be at the front of the development.
The primary objective of the ANIARA project is to provide enablers and solutions for high-performance services deployed and operated at the network edge. To manage complexity, we need to take advantage of artificial intelligence to complement traditional optimisation algorithms. Currently, deep edge network nodes will be deployed at locations not prepared for the power requirements of edge-centric compute. To answer this, we need to analyse requirements and develop methods to minimize energy consumption.