Automation of Network edge Infrastructure & Applications with aRtificiAl intelligence, ANIARA
Research Project, 2020
– 2023
Purpose and goal: The objective of the project, is to provide enablers and solutions for high-performance services deployed and operated at the network edge. The integrated edge cloud need to take advantage of artificial intelligence to complement traditional optimisation algorithms and have edge-specific platform enablers in place to take advantage of running services close to end users. Edge network nodes will be placed at locations not prepared for the power requirements of cloud infrastructure. Hence, we need to analyse requirements and develop methods to minimize energy consumption.
Expected results and effects: The project is expected to develop enablers and solutions that can be used by Swedish and European industry to streamline and enable the use of edge clouds. The results come in the form of published papers, patents, demonstrations, student examinations (Masters and PhDs), new and improved products and services.
Approach and implementation: The project is divided into five work packages, with a number of identified tasks in each. The various parts of the project are loosely coupled for maximum efficiency. Results will be spread between project parts and analysis to identify coordination gains will be performed. Once integration benefits have been identified, this will be described and in some cases implemented. A project management group with the project manager, and the work package managers meet regularly and are responsible for reporting and disseminating the results.
Participants
Paolo Monti (contact)
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Carlos Natalino Da Silva
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Federico Tonini
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Lena Wosinska
Chalmers, Electrical Engineering, Communication, Antennas and Optical Networks
Collaborations
ArctosLabs Scandinavia AB
Luleå, Sweden
Eltek Power Sweden AB
Sollentuna, Sweden
Enoc System AB
Anderstorp, Sweden
Ericsson
Stockholm, Sweden
Fraunhofer Heinrich Hertz Institute
Goslar, Germany
HAL Robotics
London, United Kingdom
IconPro GmbH
Aachen, Germany
King's College London
London, United Kingdom
Konica Minolta Global R&D
London, United Kingdom
Logical Clocks AB
Stockholm, Sweden
Opel
Rüsselsheim, Germany
Qamcom Research & Technology
Göteborg, Sweden
RISE Research Institutes of Sweden
Göteborg, Sweden
Royal Institute of Technology (KTH)
Stockholm, Sweden
Systemair AB
Skinnskatteberg, Sweden
Technische Universität Braunschweig
Braunschweig, Germany
Univrses AB
Stockholm, Sweden
Funding
VINNOVA
Project ID: 2020-00763
Funding Chalmers participation during 2020–2023
Related Areas of Advance and Infrastructure
Information and Communication Technology
Areas of Advance