A self-assessment framework for evaluating efficiency of data centers

Overview

The paper addresses computational challenges in periodic energy efficiency assessment of data centers by introducing the Self-Assessment Tool (SAT), a modular framework for evaluating thermal and energy performance. The framework integrates data from monitoring systems and external sensors to calculate standardized Key Performance Indicators (KPIs) including thermal metrics (RCI, RHI, RTI, RI, LI) and energy metrics (PUE, COP). The SAT provides transparent, reproducible KPI computation workflows with automated generation of assessment reports containing time-series visualizations, thermal mapping, and efficiency classifications.

Methods and approach

The SAT framework operates as a unified, extensible system capable of processing both real-time and historical datasets from data center monitoring infrastructure. The KPI calculation module implements standardized thermal and energy performance metrics derived from IT and cooling subsystem data. The framework supports data importation from external sensor networks and provides modular architecture enabling independent implementation of the computation workflow. Validation was conducted across two pilot installations in Denmark and Switzerland. The system generates comprehensive assessment reports with temporal visualizations and rack-level thermal analysis, deployable as either standalone or web-based service configurations.

Key Findings

Validation across the two pilot data centers demonstrated the framework's capacity to generate automated, comprehensive assessment reports that include time-series performance metrics, rack-level thermal distributions, and energy efficiency classifications. The SAT successfully calculated standardized thermal and energy KPIs from heterogeneous monitoring datasets, producing transparent and reproducible computational workflows. The framework's modular architecture enabled integration with existing data center monitoring infrastructure without requiring proprietary systems.

Implications

The SAT framework addresses a significant operational challenge in data center management by automating the collection and aggregation of performance metrics across heterogeneous monitoring systems. The transparent KPI computation workflow supports standardized assessment practices and enables independent verification of efficiency calculations, reducing the manual burden associated with periodic reporting compliance. The extensible architecture accommodates future additions of thermal and energy metrics as assessment standards evolve. Deployment flexibility as standalone or web-based service reduces implementation barriers for data center operators of varying technical capacity. The framework supports evidence-based decision-making regarding data center thermal and energy performance optimization through standardized measurement methodologies.

Scope and limitations

This summary is based on the study abstract and available metadata. It does not include a full analysis of the complete paper, supplementary materials, or underlying datasets unless explicitly stated. Findings should be interpreted in the context of the original publication.