Proceedings of ICT for Sustainability 2016

Data Center Performance Model for Evaluating Load Dependent Energy Efficiency

Authors
Daniel Schlitt, Wolfgang Nebel
Corresponding Author
Daniel Schlitt
Available Online August 2016.
DOI
https://doi.org/10.2991/ict4s-16.2016.6How to use a DOI?
Keywords
Data center, performance modeling, load modeling, energy efficiency metric, benchmarks
Abstract
Energy efficiency metrics are important tools for data center operators to optimize their facilities and thereby decreasing operational expenses while strengthen competitiveness. However, commonly used metrics like Power Usage Effectiveness do not consider productivity or suitable proxy indicators, thus lacking the ability for correctly comparing energy efficiency between data centers. Also, other known metrics which consider productivity, do this in a subjective way, i.e. results are only comparable for the same definitions. In order to address these shortcomings we proposed the Load Dependent Energy Efficiency (LDEE) metric, which uses a combination of utilization, performance, and power models to provide detailed efficiency data. By using load dependent models the concrete workloads are abstracted realizing comparability. Furthermore, models are trained with public information such as hardware specifications and benchmark results to avoid disruption of operation and thereby increasing applicability. This paper focuses on the utilization and performance models of LDEE.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
ICT for Sustainability 2016
Part of series
Advances in Computer Science Research
Publication Date
August 2016
ISBN
978-94-6252-224-4
ISSN
2352-538X
DOI
https://doi.org/10.2991/ict4s-16.2016.6How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Daniel Schlitt
AU  - Wolfgang Nebel
PY  - 2016/08
DA  - 2016/08
TI  - Data Center Performance Model for Evaluating Load Dependent Energy Efficiency
BT  - ICT for Sustainability 2016
PB  - Atlantis Press
SN  - 2352-538X
UR  - https://doi.org/10.2991/ict4s-16.2016.6
DO  - https://doi.org/10.2991/ict4s-16.2016.6
ID  - Schlitt2016/08
ER  -