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Other literature type . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Presentation . 2025
License: CC BY
Data sources: Datacite
ZENODO
Presentation . 2025
License: CC BY
Data sources: Datacite
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Measurement-based Research, Sustainability and Research Data Management

Authors: Hoßfeld, Tobias;

Measurement-based Research, Sustainability and Research Data Management

Abstract

This presentation was given at the 6G Conference in Berlin on July 2, 2025, during the session on large-scale experimentation facilities. The presentation showed the benefits of large-scale experimental facilities in research and of shared infrastructures as an enabler of effective research, including specialized hardware setups. This is particularly important in the context of power consumption and sustainability measurements. The presentation demonstrates that realism at scale, stress testing, scalability, and diversity of environments are important factors since many networking phenomena only appear in large, heterogeneous topologies. Consequently, large-scale experimental facilities will advance networking research. At the same time, they will allow reproducibility across sites. Research data management frameworks like NFDIxCS complement the facilities by allowing the organization, storage, preservation, and sharing of research data, particularly research software, in execution environments through the FAIR principle (findable, accessible, interoperable, and reusable). The talk shows that researchers need to address several issues to conduct controlled, repeatable experiments. A large-scale shared experimental facility, combined with research data management, is essential for reproducibility, sustainability, and the long-term value of research, enabling novel experiments in distributed systems and driving scientific and societal progress. 

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Keywords

Computer Communication Networks, large scale experimental facility

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green