GREEN EDGE

Project Type Energy efficiency for edge computing platforms

Project Status Ongoing

Total project cost 4 040 686,08 €

Project website https://greenedge-itn.eu/

About the project

 

Modern communication networks are rapidly evolving into sophisticated systems combining communication and computing capabilities. Computation at the network edge is key to supporting many emerging applications, from extended reality to smart health, smart cities, smart factories and autonomous driving. Multi-access edge computing (MEC) technology is being developed to deliver the required computation functionalities closer to user devices, directly at mobile access points. 

While benefiting human productivity and efficiency, large-scale adoption of MEC technology will result in a surge of data and computation in mobile networks, and this, in turn, will exacerbate their energy consumption. 

The EU-funded GREENEDGE project is set out to tame the growing carbon footprint of MEC technology, devising highly energy-efficient communication and computing functionalities for the network edge, combining them with ambient energy sources and with new energy storage and supply paradigms. As a result, GREENEDGE technology will allow mobile systems to offer the much anticipated communication and computing services in a sustainable manner. 

Fifteen early stage researchers (ESRs) will be trained by a consortium of world-class leaders across the fields of energy harvesting and storage, edge computing, machine learning and wireless communications. Ample inter-sectoral opportunities will be offered thanks to secondments among academy/research centers, two network operators, and other prominent industrial partners operating in the domains of Internet of Things, smart cities, critical infrastructure management and data analytics. A carefully planned and coordinated training and research program will ensure excellent employability prospects for the ESRs after the project completion. 

Worldsensing role

Worldsensing will host and train an early stage researcher (ESR) within the Marie Skłodowska Curie Innovative Training Network (ITN) funded by the European Commission.

The ESR project will focus on edge operational intelligence for critical infrastructure management and have a dual scientific and industrial focus. New operational intelligence techniques for the management of industrial assets for the control and operation of critical infrastructures (e.g., mines, railroads) will be studied. Edge/fog data fusion algorithms exploiting Machine Learning techniques will be developed, targeting their efficient implementation on embedded IoT devices.

European Union flag

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 953775.