A Method for Experimental Analysis and Modeling of Virtualization Performance Overhead

  • Nikolaus HuberEmail author
  • Marcel von Quast
  • Fabian Brosig
  • Michael Hauck
  • Samuel Kounev
Part of the Service Science: Research and Innovations in the Service Economy book series (SSRI)


Nowadays, virtualization solutions are gaining increasing importance. By enabling the sharing of physical resources, thus making resource usage more efficient, they promise energy and cost savings. Additionally, virtualization is the key enabling technology for cloud computing and server consolidation. However, resource sharing and other factors have direct effects on system performance, which are not yet well-understood. Hence, performance prediction and performance management of services deployed in virtualized environments like public and private clouds is a challenging task. Because of the large variety of virtualization solutions, a generic approach to predict the performance overhead of services running on virtualization platforms is highly desirable. In this paper, we present a methodology to quantify the influence of the identified performance-relevant factors based on an empirical approach using benchmarks. We show experimental results on two popular state-of-the-art virtualization platforms, Citrix XenServer 5.5 and VMware ESX 4.0, as representatives of the two major hypervisor architectures. Based on these results, we propose a basic, generic performance prediction model for the two different types of hypervisor architectures. The target is to predict the performance overhead for executing services on virtualized platforms.


Performance Overhead Performance Drop Performance Isolation Virtualization Platform 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.



This work was funded by the German Research Foundation (DFG) under grant No. 3445/6-1.


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Copyright information

© Springer Science+Business Media New York 2012

Authors and Affiliations

  • Nikolaus Huber
    • 1
    Email author
  • Marcel von Quast
    • 1
  • Fabian Brosig
    • 1
  • Michael Hauck
    • 2
  • Samuel Kounev
    • 1
  1. 1.Software Design and QualityKarlsruhe Institute of Technology (KIT)KarlsruheGermany
  2. 2.FZI Forschungszentrum InformatikKarlsruheGermany

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