MoKa: A System for Modeling and Capacity Planning of Multi-Tier Systems

Jean Arnaud; Sara Bouchenak

inria-00340772, version 1

MoKa: A System for Modeling and Capacity Planning of Multi-Tier Systems

Jean Arnaud ()^a^, 1, Sara Bouchenak () ^1, 2

N° RR-6730 (2008)

a – MENRT
1 : SARDES (INRIA Grenoble Rhône-Alpes / LIG Laboratoire d'Informatique de Grenoble)
http://sardes.inrialpes.fr/
INRIA – Institut polytechnique de Grenoble (Grenoble INP) – Université Joseph Fourier - Grenoble I – Université Pierre-Mendès-France - Grenoble II – CNRS : UMR5217 655 avenue de l'Europe, Inovallée Montbonnot Saint-Martin 38334 Saint-Ismier Cedex, France France
2 : Université Joseph Fourier (Grenoble 1 UJF)
http://www.ujf-grenoble.fr/
Université Joseph Fourier - Grenoble I Université Joseph Fourier - BP 53 - 38041 Grenoble Cedex 9 France

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Contributeur : Sara Bouchenak <>
Soumis le : Mardi 25 Novembre 2008, 14:56:35
Dernière modification le : Vendredi 12 Décembre 2008, 17:14:58

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%% http://hal.inria.fr/inria-00340772
@techreport{arnaud:inria-00340772,
    hal_id = {inria-00340772},
    url = {http://hal.inria.fr/inria-00340772},
    title = {{MoKa: A System for Modeling and Capacity Planning of Multi-Tier Systems}},
    author = {Arnaud, Jean and Bouchenak, Sara},
    abstract = {{Although cluster-based multi-tier data centers provide a means for supporting scalable web applications, their ad-hoc configuration poses significant challenges to the performance and economical costs of multi-tier applications. This paper presents the design and implementation of MoKa - a utility-aware framework for modeling multi-tier data centers and planning their capacity and optimal configuration. The contribution of the paper is threefold. First, we identify two levels of configuration of cluster-based multi-tier data centers, local configuration that applies at server's level and architectural configuration that relates to the clusters of servers in a multi-tier architecture. The combination of these two levels of configuration improves the overall performance and cost of cluster-based multi-tier data centers. Second, we present a utility function for characterizing the impact of local and architectural configurations on the performance and cost of multi-tier systems. Third, we develop a utility-aware capacity planning algorithm for efficiently calculating the optimal local and architecural configuration of multi-tier data centers to provide guarantees on performance while minimizing the cost. Our experiments on a multi-tier e-commerce auction site show the effectiveness of MoKa Moreover, the experiments show that the combination of local and architectural configurations provides a 100\% accurate utility for the multi-tier system, while with a single level of optimization (local or architectural) accuracy is limited between 20\% and 90\%.}},
    keywords = {Multi-tier systems, Data centers, Modeling, Capacity planning, QoS, Optimization.},
    language = {Anglais},
    affiliation = {SARDES - INRIA Grenoble Rh{\^o}ne-Alpes / LIG Laboratoire d'Informatique de Grenoble , Universit{\'e} Joseph Fourier - Grenoble 1 UJF},
    pages = {36},
    type = {Rapport de recherche},
    institution = {INRIA},
    number = {RR-6730},
    year = {2008},
    pdf = {http://hal.inria.fr/inria-00340772/PDF/RR-6730.pdf},
}

%F inria-00340772, version 1
%0 Report
%U http://hal.inria.fr/inria-00340772
%2 INFO:INFO_DC
%T MoKa: A System for Modeling and Capacity Planning of Multi-Tier Systems
%A Arnaud, Jean
%A Bouchenak, Sara
%+ SARDES - INRIA Grenoble Rhône-Alpes / LIG Laboratoire d'Informatique de Grenoble , Université Joseph Fourier - Grenoble 1 UJF
%X Although cluster-based multi-tier data centers provide a means for supporting scalable web applications, their ad-hoc configuration poses significant challenges to the performance and economical costs of multi-tier applications. This paper presents the design and implementation of MoKa - a utility-aware framework for modeling multi-tier data centers and planning their capacity and optimal configuration. The contribution of the paper is threefold. First, we identify two levels of configuration of cluster-based multi-tier data centers, local configuration that applies at server's level and architectural configuration that relates to the clusters of servers in a multi-tier architecture. The combination of these two levels of configuration improves the overall performance and cost of cluster-based multi-tier data centers. Second, we present a utility function for characterizing the impact of local and architectural configurations on the performance and cost of multi-tier systems. Third, we develop a utility-aware capacity planning algorithm for efficiently calculating the optimal local and architecural configuration of multi-tier data centers to provide guarantees on performance while minimizing the cost. Our experiments on a multi-tier e-commerce auction site show the effectiveness of MoKa Moreover, the experiments show that the combination of local and architectural configurations provides a 100% accurate utility for the multi-tier system, while with a single level of optimization (local or architectural) accuracy is limited between 20% and 90%.
%G Anglais
%2 Rapport de recherche
%P 36
%8 2008-00-00
%K Multi-tier systems, Data centers, Modeling, Capacity planning, QoS, Optimization.
%2 2008
%Z RR-6730

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