Project description
Cooling on the edge! Future of data centre cooling
The heart of digitisation beats in the data centres. Emerging digital trends – from artificial intelligence (AI), augmented reality (AR), and virtual reality (VR) to the Internet of Things (IoT) – are boosting average power density while forcing data centres to be located closer to end users. Consequently, data centres are challenged to keep up with efficient cooling measures. The EU-funded ECO-Qube project will develop an AI augmented holistic management system for data centres that connects cooling systems, IT loads, and electrical infrastructure with the aim of dynamically enhancing energy efficiency regarding the instant cooling requirements. It will provide a zonal heat management system that benefits from computational fluid dynamics simulations to adapt cooling systems with maximum performance and minimum energy consumption.
Objective
Artificial-Intelligence-Augmented Cooling System for Small Data Centres “ECO-Qube”; is a holistic management system which aims to enhance energy efficiency and cooling performance by orchestrating both hardware and software components in edge computing applications.
ECO-Qube is a data driven approach which utilizes valuable unused data from active data centre components. Created big data is being used by an artificial intelligence augmented system which detects cooling and energy requirements instantaneously.
ECO-Qube differentiates from conventional cooling systems which keep operating temperatures within a strict interval and do not evaluate measurable cooling performance. Unmeasured cooling performance leads underperformed airflow, thermal disequilibrium, and high energy consumption. On the contrary, ECO-Qube offers a zonal heat management system which benefits from Computational Fluid Dynamics (CFD) simulations to adapt cooling system for the best airflow and cooling performance with minimum energy consumption. Moreover, ECO-Qube realizes smart workload orchestration to keep the CPUs at their most energy efficient state and maintain the thermal equilibrium to reduce overheating risk.
Sustainability is another priority for ECO-Qube’s smart energy management system (EMS), which is designed to track the energy demand and operate the energy supply in cooperation with building/district’s EMS. This synergy maximizes the energy supplied from renewable energy sources and minimizes the energy supplied from sources with big carbon footprint.
ECO-Qube solution will be assessed in three different pilots from different climatic conditions to validate energy efficiency under different external variables.
Fields of science
- natural sciencescomputer and information sciencesartificial intelligence
- engineering and technologyenvironmental engineeringenergy and fuelsrenewable energy
- engineering and technologymechanical engineeringthermodynamic engineering
- natural sciencescomputer and information sciencesdata sciencebig data
- natural sciencesphysical sciencesclassical mechanicsfluid mechanicsfluid dynamicscomputational fluid dynamics
Keywords
Programme(s)
Funding Scheme
IA - Innovation actionCoordinator
34791 Istanbul
Türkiye
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.