Energy accounting for shared virtualized environments under DVFS using PMC-based power models
Autor: | Jordi Torres, Marc Gonzílez, David Carrera, Nacho Navarro, Vicenç Beltran, Yolanda Becerra, Ramon Bertran, Xavier Martorell, Eduard Ayguadé |
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Rok vydání: | 2012 |
Předmět: |
Flexibility (engineering)
Computer Networks and Communications Computer science business.industry Distributed computing Energy consumption Virtualization computer.software_genre Energy accounting Hardware and Architecture Virtual machine Embedded system Central processing unit Frequency scaling business computer Software |
Zdroj: | Future Generation Computer Systems. 28:457-468 |
ISSN: | 0167-739X |
DOI: | 10.1016/j.future.2011.03.007 |
Popis: | Virtualized infrastructure providers demand new methods to increase the accuracy of the accounting models used to charge their customers. Future data centers will be composed of many-core systems that will host a large number of virtual machines (VMs) each. While resource utilization accounting can be achieved with existing system tools, energy accounting is a complex task when per-VM granularity is the goal. In this paper, we propose a methodology that brings new opportunities to energy accounting by adding an unprecedented degree of accuracy on the per-VM measurements. We present a system - which leverages CPU and memory power models based in performance monitoring counters (PMCs) - to perform energy accounting in virtualized systems. The contribution of this paper is threefold. First, we show that PMC-based power modeling methods are still valid on virtualized environments. Second, we show that the Dynamic Voltage and Frequency Scaling (DVFS) mechanism, which commonly is used by infrastructure providers to avoid power and thermal emergencies, does not affect the accuracy of the models. And third, we introduce a novel methodology for accounting of energy consumption in virtualized systems. Accounting is done on a per-VM basis, even in the case where multiple VMs are deployed on top of the same physical hardware, bypassing the limitations of per-server aggregated power metering. Overall, the results for an Intel^(R) Core(TM) 2 Duo show errors in energy estimations |
Databáze: | OpenAIRE |
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