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Data center self-assessment framework standardizes efficiency evaluation

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Research area:computer-science-ainetworks-cloud

What the study found

The authors present a Self-Assessment Tool (SAT) for evaluating data center thermal and energy performance. The tool uses IT and cooling data from monitoring systems, and it can also use historical data imported from external sensors.

Why the authors say this matters

The study suggests the tool addresses the difficulty of collecting data and calculating key performance indicators, or KPIs, within a reporting period. The authors conclude that a transparent and reproducible workflow can support independent implementation and assessment reporting.

What the researchers tested

The researchers developed a unified, modular, and extensible framework for data center assessment. They validated it on two pilot data centers in Denmark and Switzerland, using both real-time and historical datasets.

What worked and what didn't

The SAT calculates standardized thermal metrics, including RCI, RHI, RTI, RI, and LI, and energy metrics, including PUE and COP. In the pilot data centers, it automatically generated assessment reports with time-series visualizations, rack-level thermal maps, and energy-efficiency classifications based on the KPIs.

What to keep in mind

The abstract does not describe detailed limitations or failures. It also does not provide numerical performance comparisons, so the summary here is limited to what was stated.

Key points

  • The paper introduces a Self-Assessment Tool for data center thermal and energy evaluation.
  • The tool can use monitoring-system data or imported historical data from external sensors.
  • It calculates standardized thermal metrics and energy metrics, including PUE and COP.
  • The framework was validated on two pilot data centers in Denmark and Switzerland.
  • It automatically produced assessment reports with visualizations, thermal maps, and KPI-based classifications.

Disclosure

Research title:
Data center self-assessment framework standardizes efficiency evaluation
Authors:
Mustafa Kuzay, Ender Demirel, Basak Bayraktar, Josef Vilestad, Axel Kärnebro, Cagatay Yilmaz, Simon Pommerencke Melgaard, Thomas Juul, Jesper Ellerbæk Nielsen, Reto Fricker, Sascha Stoller, Gabriele Humbert, Binod Prasad Koirala
Institutions:
Aalborg University, Aalborg University, Aalborg University, Eskisehir Technical University, Eskisehir Technical University, Eskisehir Technical University, RISE Research Institutes of Sweden, RISE Research Institutes of Sweden, RISE Research Institutes of Sweden, Swiss Federal Laboratories for Materials Science and Technology, Swiss Federal Laboratories for Materials Science and Technology, Swiss Federal Laboratories for Materials Science and Technology, Swiss Federal Laboratories for Materials Science and Technology
Publication date:
2026-02-26
DOI:
10.1186/s42162-026-00652-7
OpenAlex record:
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AI provenance: This post was generated by gpt-5.4-mini (OpenAI). The original authors did not write or review this post.

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