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Analysis of power consumption in heterogeneous virtual machine environments

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Abstract

Reduction of energy consumption in Cloud computing datacenters today is a hot a research topic, as these consume large amounts of energy. Furthermore, most of the energy is used inefficiently because of the improper usage of computational resources such as CPU, storage and network. A good balance between the computing resources and performed workload is mandatory. In the context of data-intensive applications, a significant portion of energy is consumed just to keep alive virtual machines or to move data around without performing useful computation. Moreover, heterogeneity of resources increases the difficulty degree, when trying to achieve energy efficiency. Power consumption optimization requires identification of those inefficiencies in the underlying system and applications. Based on the relation between server load and energy consumption, we study the efficiency of data-intensive applications, and the penalties, in terms of power consumption, that are introduced by different degrees of heterogeneity of the virtual machines characteristics in a cluster.

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Acknowledgments

The work has been funded by the projects: DataWay: Real-time Data Processing Platform for Smart Cities: Making sense of Big Data, PN-II-RU-TE-2014-4-2731; CyberWater grant of the Romanian National Authority for Scientific Research, CNDI-UEFISCDI, project number 47/2012.

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Authors and Affiliations

  1. Computer Science and Engineering Department, University “Politehnica” of Bucharest, Bucharest, Romania

    Catalin Negru, Mariana Mocanu & Valentin Cristea

  2. The Edward Rogers Sr. Department of Electrical and Computer Engineering, University of Toronto, Toronto, Canada

    Stelios Sotiriadis

  3. Department of Computing, Edge Hill University, Ormskirk, UK

    Nik Bessis

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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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  4. Stelios Sotiriadis
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  5. Nik Bessis
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Correspondence to Stelios Sotiriadis.

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The authors of this paper Catalin Negru, Mariana Mocanu, Valentin Cristea, Stelios Sotiriadis and Nik Bessis declare that they have no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by F. Pop, C. Dobre and A. Costan.

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Negru, C., Mocanu, M., Cristea, V. et al. Analysis of power consumption in heterogeneous virtual machine environments. Soft Comput 21, 4531–4542 (2017). https://doi.org/10.1007/s00500-016-2129-7

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  • DOI: https://doi.org/10.1007/s00500-016-2129-7

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