Prediction of the Performance of Web Based Systems

  • Dariusz CabanEmail author
  • Tomasz Walkowiak
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 307)


Complex Web based information systems are organized as a set of component services, communicating using the client-server paradigm. The performance prediction of such systems is complicated by the fact that the service components are strongly inter-dependent. To overcome this issue, it is proposed to use simulation techniques. Extensions to the available network simulation tools are proposed to support this. The authors present the results of multiple experiments with web-based systems, which were conducted to develop a model of client-server interactions adequately describing the relationship between the server response time and resource utilization. This model was implemented in the simulation tools and its accuracy verified against a testbed system configuration.


complex information systems Web based systems performance assessment network simulation 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Barlow, R.E.: Engineering Reliability. ASA-SIAM Series on Statistics and Applied Probability (1998)Google Scholar
  2. 2.
    Caban, D., Walkowiak, T.: Service availability model to support reconfiguration. In: Zamojski, W., Mazurkiewicz, J., Sugier, J., Walkowiak, T., Kacprzyk, J. (eds.) Complex Systems and Dependability. AISC, vol. 170, pp. 87–101. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  3. 3.
    Caban, D., Walkowiak, T.: Preserving continuity of services exposed to security incidents. In: Proc. The Sixth International Conference on Emerging Security Information, Systems and Technologies, SECURWARE 2012, Rome, August 19-24, pp. 72–78 (2012)Google Scholar
  4. 4.
    Jacobson, V.: Congestion avoidance and control. ACM CCR 18(4), 314–329 (1988)CrossRefGoogle Scholar
  5. 5.
    Lavenberg, S.S.: A perspective on queueing models of computer performance. Performance Evaluation 10(1), 53–76 (1989)CrossRefGoogle Scholar
  6. 6.
    Liu, J.: Parallel Real-time Immersive Modeling Environment (PRIME), Scalable Simulation Framework (SSF). User’s manual. Colorado School of Mines Dept. of Mathematical and Computer Sciences,
  7. 7.
    Lutteroth, C., Weber, G.: Modeling a Realistic Workload for Performance Testing. In: 12th International IEEE Enterprise Distributed Object Computing Conference (2008)Google Scholar
  8. 8.
    Miller, L.C.: Application Performance Management for Dummies, Riverbed Special edn. John Wiley & Sons, Hoboken (2013)Google Scholar
  9. 9.
    Mondal, A., Kuzmanovic, A.: Removing Exponential Backoff from TCP. ACM SIGCOMM Computer Communication Review 38(5), 19–28 (2008)CrossRefGoogle Scholar
  10. 10.
    Nielsen, J.: Usability Engineering. Morgan Kaufmann, San Francisco (1994)Google Scholar
  11. 11.
    Pasley, J.: How BPEL and SOA are changing Web services development. IEEE Internet Computing Magazine 9, 60–67 (2005)CrossRefGoogle Scholar
  12. 12.
    SPECweb2009 Release 1.20 Benchmark Design Document version 1.20. SPEC (2010),
  13. 13.
    Walkowiak, T.: Information systems performance analysis using task-level simulator. In: Proc. DepCoS – RELCOMEX 2009, pp. 218–225. IEEE Computer Society Press (2009)Google Scholar
  14. 14.
    Walkowiak, T., Michalska, K.: Functional based reliability analysis of web based information systems. In: Zamojski, W., Kacprzyk, J., Mazurkiewicz, J., Sugier, J., Walkowiak, T. (eds.) Dependable Computer Systems. AISC, vol. 97, pp. 257–269. Springer, Heidelberg (2011)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Wrocław University of TechnologyWrocławPoland

Personalised recommendations