DocumentCode
3079667
Title
Study of the KVM CPU Performance of Open-Source Cloud Management Platforms
Author
Gomez-Folgar, F. ; Garcia-Loureiro, A.J. ; Pena, T.F. ; Zablah, J.I. ; Seoane, N.
Author_Institution
Centro Singular de Investig. en Tecnoloxias da Informacion, Univ. de Santiago de Compostela, Santiago de Compostela, Spain
fYear
2015
fDate
4-7 May 2015
Firstpage
1225
Lastpage
1228
Abstract
Nowadays, there are several open-source solutions for building private, public and even hybrid clouds such as Eucalyptus, Apache Cloud Stack and Open Stack. KVM is one of the supported hypervisors for these cloud platforms. Different KVM configurations are being supplied by these platforms and, in some cases, a subset of CPU features are being presented to guest systems, providing a basic abstraction of the underlying CPU. One of the reasons for limiting the features of the Virtual CPU is to guarantee the guest compatibility with different hardware in heterogeneous environments. However, in a large number of situations, the cloud is deployed on an homogeneous set of hosts. In these cases, this limitation can affect the performance of applications being executed in guest systems. In this paper, we have analyzed the architecture, the KVM setup, and the performance of the Virtual Machines deployed by three popular cloud management platforms: Eucalyptus, Apache Cloud Stack and Open Stack, employing a representative set of applications.
Keywords
cloud computing; data privacy; public domain software; virtual machines; Apache CloudStack; CPU features; Eucalyptus; KVM CPU performance; OpenStack; cloud management platforms; guest compatibility; heterogeneous environments; hybrid clouds; hypervisors; open-source cloud management platforms; open-source solutions; private clouds; public clouds; virtual CPU; virtual machines; Cloud computing; Clouds; Graphics; Open source software; Streaming media; Three-dimensional displays; Virtual machine monitors; KVM; cloud; performance;
fLanguage
English
Publisher
ieee
Conference_Titel
Cluster, Cloud and Grid Computing (CCGrid), 2015 15th IEEE/ACM International Symposium on
Conference_Location
Shenzhen
Type
conf
DOI
10.1109/CCGrid.2015.103
Filename
7152627
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