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European Conference on Parallel Processing

Euro-Par 2011: Euro-Par 2011: Parallel Processing Workshops pp 457–466Cite as

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Cooperative Dynamic Scheduling of Virtual Machines in Distributed Systems

Cooperative Dynamic Scheduling of Virtual Machines in Distributed Systems

  • Flavien Quesnel30 &
  • Adrien Lèbre30 
  • Conference paper
  • 1146 Accesses

  • 5 Citations

  • 1 Altmetric

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 7156)

Abstract

Cloud Computing aims at outsourcing data and applications hosting and at charging clients on a per-usage basis. These data and applications may be packaged in virtual machines (VM), which are themselves hosted by nodes, i.e. physical machines.

Consequently, several frameworks have been designed to manage VMs on pools of nodes. Unfortunately, most of them do not efficiently address a common objective of cloud providers: maximizing system utilization while ensuring the quality of service (QoS). The main reason is that these frameworks schedule VMs in a static way and/or have a centralized design.

In this article, we introduce a framework that enables to schedule VMs cooperatively and dynamically in distributed systems. We evaluated our prototype through simulations, to compare our approach with the centralized one. Preliminary results showed that our scheduler was more reactive. As future work, we plan to investigate further the scalability of our framework, and to improve reactivity and fault-tolerance aspects.

Keywords

  • Cloud Computing
  • Virtual Machine
  • IEEE Computer Society
  • Overlay Network
  • Cloud Provider

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Author information

Authors and Affiliations

  1. ASCOLA Research Group, Ecole des Mines de Nantes/INRIA/LINA, Nantes, France

    Flavien Quesnel & Adrien Lèbre

Authors
  1. Flavien Quesnel
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  2. Adrien Lèbre
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Editor information

Editors and Affiliations

  1. Scilytics, Koellnerhofgasse 3/15A, 1010, Vienna, Austria

    Michael Alexander

  2. ICAR-CNR, Via P. Castellino, 111, 80131, Napoli, Italy

    Pasqua D’Ambra

  3. University of Amsterdam, 1090, Amsterdam, Netherlands

    Adam Belloum

  4. Innovative Computing Laboratory, The University of Tennessee, US

    George Bosilca

  5. Department of Experimental Medicine and Clinic, University Magna Græcia, 88100, Catanzaro, Italy

    Mario Cannataro

  6. Computer Science Department, University of Pisa, Italy

    Marco Danelutto

  7. Second University of Naples, Italy

    Beniamino Di Martino

  8. TUMünchen,, Boltzmannstr. 3, ,, 85748, Garching, Germany

    Michael Gerndt

  9. Equipe Runtime, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Emmanuel Jeannot & Raymond Namyst & 

  10. Equipe HIEPACS, INRIA Bordeaux Sud-Ouest, 33405, Talence Cedex, France

    Jean Roman

  11. Computer Science and Mathematics Division, Oak Ridge National Laboratory, 37831-6164, Oak Ridge, TN, USA

    Stephen L. Scott

  12. Department of Scientific Computing, University of Vienna, Nordbergstr. 15/3C, 1090, Vienna, Austria

    Jesper Larsson Traff

  13. Computer Science and Mathematics Division, Oak Ridge National Laboratory, 37831, Oak Ridge, TN, USA

    Geoffroy Vallée

  14. Technische Universität München, Germany

    Josef Weidendorfer

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Quesnel, F., Lèbre, A. (2012). Cooperative Dynamic Scheduling of Virtual Machines in Distributed Systems. In: Alexander, M., et al. Euro-Par 2011: Parallel Processing Workshops. Euro-Par 2011. Lecture Notes in Computer Science, vol 7156. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29740-3_51

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  • DOI: https://doi.org/10.1007/978-3-642-29740-3_51

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  • Print ISBN: 978-3-642-29739-7

  • Online ISBN: 978-3-642-29740-3

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