Projects

Science relies on knowledge, knowledge relies on data. However, not all data is necessary, nor is it always managed efficiently or effectively. This is witnessed by the rapid growth of energy use in data centres with unsustainable socio-environmental effects. Industry has started creating and adopting energy-aware data management tactics. Science must do the same.To this aim, we build upon the methods and results emerged from the pragmatism of industrial practice and the rigour of academic research. We create an integrated 'modeling-and-measurement' method coming from both worlds, with energy-aware tactics learned in industry, and adapted and measured in academic research.

To combat the increased energy demand of systems using machine learning (ML), especially modern ones based on large language models (LLMs), we take a holistic software architecture perspective to synthesize reusable software design guidance to improve environmental sustainability via green architectural tactics. We will provide a holistic collection of effective green tactics, a tool-supported methodology to guide the continuous synthesis of tactics for researchers, a tool-supported methodology to allow efficient tactic browsing and selection for practitioners, empirical evidence for the effectiveness and trade-offs for tactics, and guidelines for applying and implementing the tactics in real-world industry settings, including prototypical sample implementations.

This is an archive that captures reusable (software and not only) tactics, open for everybody to learn and contribute. It is an initiative of the VU Digital Sustainability Center and the S2 Research Group.

This is an inter-disciplinary collaboration between researchers of Vrije Universiteit Amsterdam and University of Twente

CloudStars provides the best cost, performance, and energy tradeoffs in Cloud Computing infrastructures.

Interconnect (Horizon2020) aims to achieve a relevant milestone in the democratization of efficient energy management, through a flexible and interoperable ecosystem.

GraphMassivizer (Horizon2020) aims at supporting extreme and sustainable graph processing for urgent societal challenges in Europe using serverless Cloud computing.

ExtremeXP (Horizon Europe) aims to provide accurate, energy-efficient, fit-for-purpose, and trustworthy data-driven insights via evaluating different complex analytics variants, considering end users’ preferences and feedback in an automated way.

This project researches the sustainability of cloud computing, by identifying the related social, technical and environmental risks and benefits, and complementing them with examples of possible countermeasures. It is funded by the Network Insitute of the VU as an Academy Project for 2022.