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Experimental Evaluation of the Performance-Influencing Factors of Virtualized Storage Systems

  • Qais Noorshams
  • Samuel Kounev
  • Ralf Reussner
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7587)

Abstract

Virtualized cloud environments introduce an additional abstraction layer on top of physical resources enabling their collective use by multiple systems to increase resource efficiency. In I/O-intensive applications, however, the virtualized storage of such shared environments can quickly become a bottleneck and lead to performance and scalability issues. In software performance engineering, application performance is analyzed to assess the non-functional properties taking into account the many performance-influencing factors. In current practice, however, virtualized storage is either modeled as a black-box or tackled with full-blown and fine-granular simulations. This paper presents a systematic performance analysis approach of I/O-intensive applications in virtualized environments. First, we systematically identify storageperformance- influencing factors in a representative storage environment. Second, we quantify them using a systematic experimental analysis. Finally, we extract simple performance analysis models based on regression techniques. Our approach is applied in a real world environment using the state-of-the-art virtualization technology of the IBM System z and IBM DS8700.

Keywords

I/O Storage Performance Virtualization 

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References

  1. 1.
    Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., Zaharia, M.: A view of cloud computing. Commun. ACM 53(4), 50–58 (2010)CrossRefGoogle Scholar
  2. 2.
    Kraft, S., Casale, G., Krishnamurthy, D., Greer, D., Kilpatrick, P.: Performance Models of Storage Contention in Cloud Environments. Springer Journal of Software and Systems Modeling (2012)Google Scholar
  3. 3.
    Gulati, A., Kumar, C., Ahmad, I.: Storage workload characterization and consolidation in virtualized environments. In: VPACT 2009 (2009)Google Scholar
  4. 4.
    Mell, P., Grance, T.: The nist definition of cloud computing. National Institute of Standards and Technology 53(6), 50 (2009)Google Scholar
  5. 5.
    Dufrasne, B., Bauer, W., Careaga, B., Myyrrylainen, J., Rainero, A., Usong, P.: Ibm system storage ds8700 architecture and implementation (2010), http://www.redbooks.ibm.com/abstracts/sg248786.html
  6. 6.
    Wang, M., Au, K., Ailamaki, A., Brockwell, A., Faloutsos, C., Ganger, G.R.: Storage device performance prediction with CART models. In: MASCOTS 2004, pp. 588–595 (2004)Google Scholar
  7. 7.
    Bucy, J.S., Schindler, J., Schlosser, S.W., Ganger, G.R., Contributors: The DiskSim Simulation Environment - Version 4.0 Reference Manual. Carnegie Mellon University, Pittsburgh (2008)Google Scholar
  8. 8.
    Lebrecht, A.S., Dingle, N.J., Knottenbelt, W.J.: Analytical and simulation modelling of zoned raid systems. The Computer Journal 54, 691–707 (2011)CrossRefGoogle Scholar
  9. 9.
    Ahmad, I., Anderson, J., Holler, A., Kambo, R., Makhija, V.: An analysis of disk performance in vmware esx server virtual machines. In: WWC-6, pp. 65–76 (2003)Google Scholar
  10. 10.
    Koh, Y., Knauerhase, R., Brett, P., Bowman, M., Wen, Z., Pu, C.: An analysis of performance interference effects in virtual environments. In: ISPASS 2007, pp. 200–209 (2007)Google Scholar
  11. 11.
    Kundu, S., Rangaswami, R., Dutta, K., Zhao, M.: Application performance modeling in a virtualized environment. In: HPCA 2010, pp. 1–10 (2010)Google Scholar
  12. 12.
    Hauck, M., Kuperberg, M., Huber, N., Reussner, R.: Ginpex: deriving performance-relevant infrastructure properties through goal-oriented experiments. In: QoSA-ISARCS 2011, pp. 53–62. ACM, New York (2011)Google Scholar
  13. 13.
    Huber, N., von Quast, M., Hauck, M., Kounev, S.: Evaluating and modeling virtualization performance overhead for cloud environments. In: CLOSER 2011 (2011)Google Scholar
  14. 14.
    Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., Neugebauer, R., Pratt, I., Warfield, A.: Xen and the art of virtualization. SIGOPS Oper. Syst. Rev. 37, 164–177 (2003)CrossRefGoogle Scholar
  15. 15.
    Iyer, R., Illikkal, R., Tickoo, O., Zhao, L., Apparao, P., Newell, D.: Vm3: Measuring, modeling and managing vm shared resources. Computer Networks 53, 2873–2887 (2009)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Qais Noorshams
    • 1
  • Samuel Kounev
    • 1
  • Ralf Reussner
    • 1
  1. 1.Software Design and QualityKarlsruhe Institute of Technology (KIT)KarlsruheGermany

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