Performance Models for Virtualized Applications

  • Fabrício Benevenuto
  • César Fernandes
  • Matheus Santos
  • Virgílio Almeida
  • Jussara Almeida
  • G. (John) Janakiraman
  • José Renato Santos
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4331)

Abstract

This paper develops a series of performance models for predicting performance of applications on virtualized systems. It introduces the main ideas of performance modeling and presents a complete case study of an application running on Linux that is migrated to a virtualized environment consisting of Linux and Xen. The paper describes the models, the process of obtaining measurements for the models and calculates performance metrics for the two environments. A validation of the results is also discussed in the paper.

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References

  1. 1.
    Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., Neugebauer, R., Pratt, I., Warfield, A.: Xen and the Art of Virtualization. In: Proc. of 19th ACM Symposium on Operating Systems Principles (October 2003)Google Scholar
  2. 2.
    Cherkasova, L., Gardner, R.: Measuring CPU overhead for I/O processing in the Xen virtual machine monitor. In: Proc. of USENIX Annual Technical Conference (April 2005)Google Scholar
  3. 3.
    Menascé, D.: Virtualization: Concepts, Applications, and Performance. In: Proc. of The Computer Measurement Group’s 2005 International Conference, Orlando, FL, USA (December 2005)Google Scholar
  4. 4.
    Gupta, D., Gardner, R., Cherkasova, L.: XenMon: QoS Monitoring and Performance Profiling Tool. Technical Report HPL-2005-187, HP Labs (October 2005)Google Scholar
  5. 5.
    Jain, R.: The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling, 1st edn. John Wiley and Sons, Inc., Chichester (1991)MATHGoogle Scholar
  6. 6.
    Menasce, D., Almeida, V., Dowdy, L.: Capacity Planning and Performance Modeling: From Mainframes to Client-Server Systems. Prentice-Hall, Inc., Upper Saddle River (1994)Google Scholar
  7. 7.
    Menasce, D.A., Dowdy, L.W., Almeida, V.A.F.: Performance by Design: Computer Capacity Planning By Example. Prentice Hall PTR, Englewood Cliffs (2004)Google Scholar
  8. 8.
    Menon, A., Santos, J.R., Turner, Y., Janakiraman, G., Zwaenepoel”, W.: Diagnosing Performance Overheads in the Xen Virtual Machine Environment. In: Proc. of First ACM/USENIX Conference on Virtual Execution Environments (VEE 2005), Chicago, IL (June 2005)Google Scholar
  9. 9.
    Mosberger, D., Jin”, T.: httperf: A Tool for Measuring Web Server Performance. In: Proc. of First Workshop on Internet Server Performance, Madison, WI, June 1998, pp. 59–67 (1998)Google Scholar
  10. 10.
  11. 11.
    VMWare Web Site, http://www.vmware.com
  12. 12.
    Whitaker, A., Shaw, M., Gribble, S.: Scale and Performance in the Denali Isolation Kernel. In: Proc. of Operating Systems Design and Implementation (OSDI) (December 2002)Google Scholar
  13. 13.
    Bard, Y.: Performance Analysis of Virtual Memory Time-Sharing Systems. Proc. of IBM Systems Journal 14(4), 366–384 (1975)CrossRefGoogle Scholar
  14. 14.
    Bard, Y.: An analytic Model of the VM / 370 System. Proc. of IBM Journal of Research and Development 22(5), 498–508 (1978)MATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Fabrício Benevenuto
    • 1
  • César Fernandes
    • 1
  • Matheus Santos
    • 1
  • Virgílio Almeida
    • 1
  • Jussara Almeida
    • 1
  • G. (John) Janakiraman
    • 2
  • José Renato Santos
    • 2
  1. 1.Computer Science DepartmentFederal University of Minas GeraisBrazil
  2. 2.HP LabsPalo AltoUSA

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