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European Conference on Parallel Processing

Euro-Par 2011: Euro-Par 2011: Parallel Processing Workshops pp 407–415Cite as

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Coexisting Scheduling Policies Boosting I/O Virtual Machines

Coexisting Scheduling Policies Boosting I/O Virtual Machines

  • Dimitris Aragiorgis30,
  • Anastassios Nanos30 &
  • Nectarios Koziris30 
  • Conference paper
  • 1092 Accesses

  • 1 Citations

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

Abstract

Deploying multiple Virtual Machines (VMs) running various types of workloads on current many-core cloud computing infrastructures raises an important issue: The Virtual Machine Monitor (VMM) has to efficiently multiplex VM accesses to the hardware. We argue that altering the scheduling concept can optimize the system’s overall performance.

Currently, the Xen VMM achieves near native performance multiplexing VMs with homogeneous workloads. Yet having a mixture of VMs with different types of workloads running concurrently, it leads to poor I/O performance. Taking into account the complexity of the design and implementation of a universal scheduler, let alone the probability of being fruitless, we focus on a system with multiple scheduling policies that coexist and service VMs according to their workload characteristics. Thus, VMs can benefit from various schedulers, either existing or new, that are optimal for each specific case.

In this paper, we design a framework that provides three basic coexisting scheduling policies and implement it in the Xen paravirtualized environment. Evaluating our prototype we experience 2.3 times faster I/O service and link saturation, while the CPU-intensive VMs achieve more than 80% of current performance.

Keywords

  • Virtual Machine
  • Schedule Policy
  • Link Utilization
  • Virtual Machine Monitor
  • Physical Core

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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References

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Author information

Authors and Affiliations

  1. Computing Systems Laboratory, National Technical University of Athens, Greece

    Dimitris Aragiorgis, Anastassios Nanos & Nectarios Koziris

Authors
  1. Dimitris Aragiorgis
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  2. Anastassios Nanos
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  3. Nectarios Koziris
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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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© 2012 Springer-Verlag Berlin Heidelberg

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Cite this paper

Aragiorgis, D., Nanos, A., Koziris, N. (2012). Coexisting Scheduling Policies Boosting I/O Virtual Machines. 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_46

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  • DOI: https://doi.org/10.1007/978-3-642-29740-3_46

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29739-7

  • Online ISBN: 978-3-642-29740-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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