Energy-efficient data centres: model-based analysis of power-performance trade-offs

Björn Frits Postema

    Research output: ThesisPhD Thesis - Research UT, graduation UT

    1209 Downloads (Pure)


    Nowadays businesses, governments and industries rely heavily on ICT solutions. Since these ICT solutions often have high space, security, availability and performance requirements, data centres provide physical locations to facilitate networks of servers for processing and storage purposes of these ICT solutions. The increasing worldwide energy consumption of data centres has a significant impact on the world's ecosystem through an increase in greenhouse gases for the generation of necessary electricity. This has led to an increased attention in the global political agenda. Moreover, the high energy consumption in data centres has also led to high operational costs with the consequence that even the smallest improvements in currently active systems could significantly ease the financial burden. These reasons have led to a greater need for energy-efficient data centres.

    In this thesis, we propose that model-based analysis of power and performance can assist energy saving techniques with meaningful insights in data centres that strive for energy-efficiency. Therefore, two sets of power and performance models for energy-efficient data centres are proposed and analysed. We show that exchanging power at the expense of performance caused by energy saving techniques can lead to so-called power-performance trade-offs, which offers additional flexibility to data centre design. Consequently, power management is studied by modelling this feature and proposing an evaluation method for power management strategies. Also, the potential of combining power management with advanced cooling is analysed, in order to save even more energy. To determine the degree to which the models correspond to the real world, our models are experimentally validated. For this reason, the simulation models are calibrated with parameters obtained through workload modelling using workload traces from a real data centre. Moreover, a cross-model validation is used to compare power and performance estimates of the same system with two different modelling and analysis techniques. Furthermore, we propose an experimental micro data centre and compare it with a real data centre and apply the experimental setup for validation purposes.
    Original languageEnglish
    Awarding Institution
    • University of Twente
    • Haverkort, Boudewijn R.H.M., Supervisor
    Award date21 Dec 2018
    Place of PublicationEnschede
    Print ISBNs978-90-365-4688-1
    Publication statusPublished - 21 Dec 2018


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