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Soft Computing
Erschienen in: Soft Computing 16/2017

28.04.2016 | Focus

Analysis of power consumption in heterogeneous virtual machine environments

verfasst von: Catalin Negru, Mariana Mocanu, Valentin Cristea, Stelios Sotiriadis, Nik Bessis

Erschienen in: Soft Computing | Ausgabe 16/2017

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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.
Vorheriger Artikel An evaluation of cloud-based mobile services with limited capacity: a linear approach
Nächster Artikel A simple model to exploit reliable algorithms in cloud federations

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Metadaten
Titel
Analysis of power consumption in heterogeneous virtual machine environments
verfasst von
Catalin Negru
Mariana Mocanu
Valentin Cristea
Stelios Sotiriadis
Nik Bessis
Publikationsdatum
28.04.2016
Verlag
Springer Berlin Heidelberg
Erschienen in
Soft Computing / Ausgabe 16/2017
Print ISSN: 1432-7643
Elektronische ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-016-2129-7

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