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Enhancing Resilience and Flexibility of Reconfigurable Data Centre Networks

Objective

The rapid growth of Data Centres is driven by the surge in demand for online storage and Machine Learning (ML) applications. Based on fixed electronic switches and packet-level protocols, traditional data centre networks effectively handle general-purpose, uniform traffic but struggle with bursty, skewed ML workloads. Reconfigurable Data Centre Networks (RDCNs), employing Optical Circuit Switches (OCSs) that can dynamically alter the network topology, have emerged to address this challenge. These flexible, high-speed networks can efficiently adapt to changing traffic patterns, with improved Quality of Service and energy efficiency for advanced digital services.
Despite their promise, critical knowledge gaps remain in the scientific literature. ReFlexRDCN (Enhancing Resilience and Flexibility of Reconfigurable Data Centre Networks) aims to address these by targeting two major goals. First, it will engineer advanced tools for rapid identification, localisation, and failover in RDCNs, tackling challenges specific to OCSs. Second, it will design forecasting-driven failure-resilient control algorithms for ML inference requests. By leveraging real-world ML workload traces and advanced forecasting, the project will optimise the allocation and adjustment of network resources, ensuring high efficiency and resilience under dynamic, real-time inference requests. These objectives will be addressed by integrating interdisciplinary methodologies, including network optimisation, optical communications, queuing theory, parallelisation of ML workloads, and validated with simulations and real data.
The project outcome is a set of rigorously tested frameworks and algorithms that fill crucial gaps in current research, directly enabling scalable, high-performance, and reliable digital services. These advances will support next-generation ML applications and promote European priorities for trustworthy and efficient digital infrastructures.

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Keywords

Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)

Programme(s)

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Topic(s)

Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.

Funding Scheme

Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.

HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships

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Call for proposal

Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.

(opens in new window) HORIZON-MSCA-2025-PF

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Coordinator

TECHNISCHE UNIVERSITAT BERLIN
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 202 125,12
Address
STRASSE DES 17 JUNI 135
10623 Berlin
Germany

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Region
Berlin Berlin Berlin
Activity type
Higher or Secondary Education Establishments
Links
Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

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