Abstract
In recent work, we proposed a new specification language for power management strategies as an extension to our AnyLogic-based simulation framework for the trade-off analysis of power and performance in data centres. In this paper, we study the quality of such advanced power management strategies based on both power and performance measurement data collected during system operation. These strategies take a wide variety of state variables into account. In order to ensure the quality of new strategies, they are studied for stability, efficiency, adaptability and robustness; these qualities will be formally defined. This paper presents an evaluation approach for these qualities for several power management strategies inspired by strategies presented in the literature (and extensions thereof). We show that the choice of power management strategy depends both on which qualities are given the highest priority and on the used state information. The new power management strategies show significant reductions in energy consumption in our case of up to 54% energy (compared to an “always on” strategy) for a typical data centre workload for a small 30-server cluster.
Highlights
One way to reduce overall energy consumption in data centres is Power Management (PM)
To illustrate the full evaluation of the qualities of a power management strategy, a data centre configuration and its job characteristics are described in Section 4.1 as the first step of the three-step approach from Section 2
We consider a data centre in which jobs arrive according to a Poisson process such that the inter-arrival times distribution is exponential with rate λ
Summary
One way to reduce overall energy consumption in data centres is Power Management (PM). PM allows to switch between power states of servers to reduce power consumption, while trying to keep the performance intact [5]. I.e., power consumption is proportional to utilisation, has proven to be one of the three main areas of improvement on data centre energy-efficiency in the last years [4,14]. Since PM software and hardware has been improving, scaling back. 174 B.F. Postema, B.R. Haverkort / Electronic Notes in Theoretical Computer Science 337 (2018) 173–191 idle servers, as a consequence of no power proportionality, has become a reasonable practice nowadays
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