GREENEDGE · Taming the environmental impact of mobile networks through GREEN EDGE computing platforms

Taming the environmental impact of mobile networks through GREEN EDGE computing platforms

Mobile applications and services along with fifth generation (5G) and beyond 5G networks have led to a digital revolution, enabling ubiquitous and enhanced broadband services, smart/autonomous vehicles, intelligent transport, and complex human machine interactions. Hence, our connected society generates a vast amount of data, which has to be transmitted, processed and analysed, often at runtime. Such a data surge demands a massive use of computing services based on artificial intelligence (AI) and machine learning (ML) algorithms at the network edge, which have a large, unsustainable, carbon footprint. GREENEDGE aimed at mitigating the carbon footprint of Information and Communication Technology (ICT), including mobile networks and AI-based computing systems, being aligned with mitigation policies for climate change at EU and UN levels (reduction of carbon emissions and achievement of carbon neutrality of human activities by 2050). Sustainable development of ICT is essential for achieving these objectives. In fact, ICT was used extensively during the last decade and it is estimated to be consuming around 20% of electricity worldwide by 2030. GREENEDGE tamed the growing carbon footprint of ML/AI based edge computing services with a twofold approach: - First, renewable energy resources were utilised to sustain the communication and computing tasks that run at the mobile network edge. - Second, green-by-design computing and communication paradigms were developed, to wisely exploit the available communication, AI/ML/computing and energy resources across the mobile edge network. Particular attention was paid to distributed computing approaches (federated learning). In conclusion, the project has successfully achieved the planned objectives, developing new technologies for green edge computing and training highly qualified researchers through six training schools, local- and secondment-based actions. One final workshop was organised and 40 scientific publications were published. Among the major achievements, we underline the development of prototype edge nodes powered by light and with very high energy efficiency. Other notable results include new algorithms and theories, with strategies that led to substantial energy savings against the state-of-the-art. The project set a solid basis for future developments on green energy ICT systems, and contributed to increasing the awareness around green ICT.

Data: CORDIS, © European Union