Research Area: Cloud Computing
Since the development of data centers, power management (i.e., assessment, consumption and monitoring) has been a great challenge among scientists and engineers. By emerging a new generation of data center in the form of Hyperscale cloud data centers (HCDC), this concern has become more devastating than ever. The huge physical scale and the high level of system utilization through large power compensating system are some of the main characteristics of todays HCDC. The lack of appropriate power assessment from available power estimation models, prevents professionals from designing an accurate HCDCcapacity planning. In particular, during steady state workload processing at the high utilization rate of HCDCtechnology, the inlet cold temperature level rises up and this trace can be effect to the computable power consumption. In this article, we show how the ambient temperature have significant negative impact on power consumption and for an accurate and proper estimation of the power consumption of HCDC, we propose a temperature-aware power consumption model. The model is evaluated by SimWare for various server types and configurations and results prove the effectiveness and accuracy of the proposed model. At the end, we show the proposed model can be applicable for both homogeneous and heterogeneous HCDCs.
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Author(s) Name: MehdiRezaei-Mayahi,MostafaRezazad and HamidSarbazi-Azadc
Journal name: Future Generation Computer Systems
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Publisher name: ELSEVIER
DOI: 10.1016/j.future.2018.11.029
Volume Information: Volume 94, May 2019, Pages 130-139
