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    Analysis of power consumption in heterogeneous virtual machine environments

    Negru, C. and Mocanu, M. and Cristea, V. and Sotiriadis, Stelios and Bessis, N. (2017) Analysis of power consumption in heterogeneous virtual machine environments. Soft Computing 21 (16), pp. 4531-4542. ISSN 1432-7643.

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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.

    Metadata

    Item Type: Article
    Additional Information: The final publication is available at Springer via the link above.
    Keyword(s) / Subject(s): Cloud computing, Data intensive-applications, Energy-efficiency, Virtualization
    School: Birkbeck Schools and Departments > School of Business, Economics & Informatics > Computer Science and Information Systems
    Research Centres and Institutes: Birkbeck Knowledge Lab
    Depositing User: Stelios Sotiriadis
    Date Deposited: 09 Apr 2018 14:19
    Last Modified: 24 Jun 2020 17:04
    URI: http://eprints.bbk.ac.uk/id/eprint/21784

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