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

Publications

2021

Network automation: challenges, enablers, and benefits

Other conference contribution

More information

Latest update

2021-09-28