E-mc2: A formal framework for energy modelling in cloud computing |
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| Affiliation: | 1. Department of Computer Science and Information Engineering, School of Electrical and Computer Engineering, College of Engineering, Chang Gung University, Taiwan;2. Department of Computer Science and Engineering, Pennsylvania State University, USA;3. Genesys Logic, No.205, Sec. 2, Beixin Rd., Xindian Dist., New Taipei City, Taiwan;1. Duke University School of Medicine, Durham, NC 27710, United States of America;2. Division of Gynecologic Oncology, Department of Obstetrics & Gynecology, Duke University Medical Center, Durham, NC 27710, United States of America;2. Division of Biostatistics and Epidemiology, Cincinnati Children''s Hospital Medical Center, Cincinnati, Ohio;3. Neuroscience Institute, University of Cincinnati College of Medicine, Cincinnati, Ohio;4. Department of Neurology and Rehabilitation Medicine, University of Cincinnati College of Medicine, Cincinnati, Ohio;6. Institute for Policy Research, University of Cincinnati, Cincinnati, Ohio;5. Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana;11. Department of Emergency Medicine, University of Cincinnati College of Medicine, Cincinnati, Ohio |
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| Abstract: | Due to energy crisis of the last years, energy waste and sustainability have been brought both into public attention, and under industry and scientific scrutiny. Thus, obtaining high-performance at a reduced cost in cloud environments as reached a turning point where computing power is no longer the most important concern. However, the emphasis is shifting to manage energy efficiently, whereas providing techniques for measuring energy requirements in cloud systems becomes of capital importance.Currently there are different methods for measuring energy consumption in computer systems. The first consists in using power meter devices, which measure the aggregated power use of a machine. Another method involves directly instrumenting the motherboard with multimeters in order to obtain each power connector’s voltage and current, thus obtaining real-time power consumption. These techniques provide a very accurate results, but they are not suitable for large-scale environments. On the contrary, simulation techniques provide good scalability for performing experiments of energy consumption in cloud environments. In this paper we propose E-mc2, a formal framework integrated into the iCanCloud simulation platform for modelling the energy requirements in cloud computing systems. |
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| Keywords: | Cloud computing systems Energy aware models Modelling cloud systems |
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