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Impact of Virtual Machines Heterogeneity on Data Center Power Consumption in Data-Intensive Applications

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Adaptive Resource Management and Scheduling for Cloud Computing (ARMS-CC 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9438))

Abstract

Cloud computing data centers consume large amounts of energy. Furthermore, most of the energy is used inefficiently. Computational resources such as CPU, storage, and network consume a lot of power. A good balance between the computing resources is mandatory. In the context of data-intensive applications, a significant portion of energy is consumed just to keep virtual machines or to move data around without performing useful computation. Power consumption optimization requires identification of the inefficiencies in the underlying system. Based on the relation between server load and energy consumption, in this paper we study the energy efficiency, and the penalties in terms of power consumption that are introduced by different degrees of heterogeneity for a cluster of heterogeneous virtual machines.

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Acknowledgement

The research presented in this paper is supported by the projects: CyberWater grant of the Romanian National Authority for Scientific Research, CNDI-UEFISCDI, project number 47/2012; clueFarm: Information system based on cloud services accessible through mobile devices, to increase product quality and business development farms - PN-II-PTPCCA-2013-4-0870. We would like to thank the reviewers for their time and expertise, constructive comments and valuable insight.

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Authors and Affiliations

  1. Computer Science Department, University Politehnica of Bucharest, Bucharest, Romania

    Catalin Negru, Mariana Mocanu & Valentin Cristea

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  1. Catalin Negru
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  2. Mariana Mocanu
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  3. Valentin Cristea
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Correspondence to Catalin Negru .

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Editors and Affiliations

  1. University Politehnica of Bucharest, Bucharest, Romania

    Florin Pop

  2. Université Pierre et Marie CURIE, Paris, France

    Maria Potop-Butucaru

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Negru, C., Mocanu, M., Cristea, V. (2015). Impact of Virtual Machines Heterogeneity on Data Center Power Consumption in Data-Intensive Applications. In: Pop, F., Potop-Butucaru, M. (eds) Adaptive Resource Management and Scheduling for Cloud Computing. ARMS-CC 2015. Lecture Notes in Computer Science(), vol 9438. Springer, Cham. https://doi.org/10.1007/978-3-319-28448-4_7

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  • DOI: https://doi.org/10.1007/978-3-319-28448-4_7

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-28448-4

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