Skip to main content

Memory Performance Prediction of Web Server Applications Based on Grey System Theory

  • Conference paper
Web Technologies and Applications (APWeb 2012)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7235))

Included in the following conference series:

Abstract

With the success of internet, recently more and more companies start to run web-based business. While running e-business sites, many companies have encountered unexpected degeneration of their web server applications performance, which may lead to loss of customers. Many managers wish to have a decision-support tool that cancan answer such questions, such as “will my web server applications performance degenerate?”, and “what are the main reasons of the degenerations?”. In this paper we first propose a new memory performance prediction model of web server applications based on grey system theory. And then, a software system “Memory Performance Manager” (MPM) is developed for predicting memory performance of the web server applications. Massive experiments demonstrate that the effectiveness of MPM’s in predicting web server memory performances.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Liu, Y., Zhu, L., Gorton, I.: Performance assessment for e-government services: an experience report. In: CBSE 2007, pp. 74–89 (2007)

    Google Scholar 

  2. Hao, W., Fu, J., Yen, I.-L., et al.: Achieving high performance web applications by service and database replications at edge servers. In: IPCCC 2009, pp. 153–160 (2009)

    Google Scholar 

  3. Magalhães, J.P., Silva, L.M.: Root-cause analysis of performance anomalies in web-based applications. In: SAC 2011, pp. 209–216 (2011)

    Google Scholar 

  4. Deng, J.: Introduction to grey system theory. J. Grey Syst. (1), 1–24 (1989)

    Google Scholar 

  5. Huang, K., Jane, C.-J.: A hybrid model for stock market forecasting and portfolio selection based on ARX, grey system and RS theories. Expert. Syst. Appl. 36(3), 5387–5392 (2009)

    Article  Google Scholar 

  6. Zhu, S., Wang, J., Zhao, W.: A seasonal hybrid procedure for electricity demand forecasting in China. Applied Energy 88(11), 3807–3815 (2011)

    Article  Google Scholar 

  7. Song, Q., Martin, S.: Predicting software project effort: A grey relational analysis based method. Expert Syst. Appl. 38(6), 7302–7316 (2011)

    Article  Google Scholar 

  8. Zhao, J., Wang, W., Liu, Y.: A Two-Stage Online Prediction Method for a Blast Furnace Gas System and Its Application. IEEE T. Contr. Syst. T. 19(3), 507–520 (2011)

    Article  Google Scholar 

  9. Mosberger, D., Jin, T.: httperf—A Tool for Measuring Web Server Performance. In: Proceedings of the First Workshop on Internet Server Performance, Madison, WI (1998)

    Google Scholar 

  10. Schroeder, B., Harchol-Balter, M.: Web servers under overload: How scheduling can help. ACM Trans. on Internet Technology 6(1), 20–52 (2006)

    Article  Google Scholar 

  11. Ma, L., Luo, T., Song, J., et al.: Web performance testing and prediction. Journal of the Graduate School of the Chinese Academy of Sciences 22(4), 472–479 (2005)

    Google Scholar 

  12. Tan, G.J.: The structure method and application of background value in grey system GM(1,1) Model (I). J. Theor. Pract. Syst. Eng. 20(4), 98–103 (2000)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2012 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Huang, F., Zhang, S., Yuan, C., Zhong, Z. (2012). Memory Performance Prediction of Web Server Applications Based on Grey System Theory. In: Sheng, Q.Z., Wang, G., Jensen, C.S., Xu, G. (eds) Web Technologies and Applications. APWeb 2012. Lecture Notes in Computer Science, vol 7235. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29253-8_62

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-29253-8_62

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29252-1

  • Online ISBN: 978-3-642-29253-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics