D2.2 - AI-EFFECT Infrastructural Layer Design

Zenodo (CERN European Organization for Nuclear Research)

Abstract

This document defines the key architectural concepts and building blocks that form the infrastructural layer of the AI-EFFECT ecosystem. Building blocks are modular and reusable hardware, software, or digital components that provide capabilities across the project's Testing and Experimentation Facilities (TEFs). The document outlines how these components are classified, integrated, and deployed to support interoperability, reusability, and collaboration across the AI-EFFECT network. It also describes the framework that enables communication and data exchange within individual TEF nodes, between the four AI-EFFECT nodes, and with external stakeholders. Through standardized integration profiles, adapters, deployment rules, and tools such as VILLASnode, the infrastructural layer supports interoperable use of resources while accommodating node-specific requirements. A catalogue of available building blocks and their key characteristics is included, with additional technical details provided in the appendix.

Authors 16

1. Levi Rodriguez Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

2. Alexandra Bach Aachen

   RWTH Aachen University

   Affiliation as printed

   RWTH Aachen University

3. Avery Hodges

   Electric Power Research Institute

   Affiliation as printed

   Electric Power Research Institute

4. Carlos Silva

   INESC TEC

   Affiliation as printed

   INESC TEC

5. Carlos Tarjano Santos

   INESC TEC

   Affiliation as printed

   INESC TEC

6. Carlos Pereira

   INESC TEC

   Affiliation as printed

   INESC TEC

7. Tobias Ritschel

   Technical University of Denmark

   Affiliation as printed

   Technical University of Denmark

8. Seyede Zahra Tajalli
9. Paul Bannmüller

   Delft University of Technology

   Affiliation as printed

   Delft University of Technology

10. Maosheng Yang

    Delft University of Technology

    Affiliation as printed

    Delft University of Technology

11. Anis Bkakria
12. Benedikt Schwalm
13. Amir Cicak
    Affiliation as printed

    IKIM

14. Adarsh Sunilkumar
15. Stefan Zahlner
16. Massimo Bolognesi