CFP last date
22 April 2024
Call for Paper
May Edition
IJCA solicits high quality original research papers for the upcoming May edition of the journal. The last date of research paper submission is 22 April 2024

Submit your paper
Know more
The week's pick
Responsive image
Enhancing Privacy Preservation: Multi-Attribute Protection with P-Sensitive K-Anonymity

Twinkle Patel Kiran Amin
Random Articles
Reseach Article

An Admission Control Mechanism for Web Servers using Neural Network

by Lahcene Aid, Malik Loudini, Walid-Khaled Hidouci
journal cover thumbnail

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 15 - Number 5
Year of Publication: 2011
Authors: Lahcene Aid, Malik Loudini, Walid-Khaled Hidouci
10.5120/1946-2602

Lahcene Aid, Malik Loudini, Walid-Khaled Hidouci . An Admission Control Mechanism for Web Servers using Neural Network. International Journal of Computer Applications. 15, 5 ( February 2011), 14-19. DOI=10.5120/1946-2602

@article{ 10.5120/1946-2602,
author = { Lahcene Aid, Malik Loudini, Walid-Khaled Hidouci },
title = { An Admission Control Mechanism for Web Servers using Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { February 2011 },
volume = { 15 },
number = { 5 },
month = { February },
year = { 2011 },
issn = { 0975-8887 },
pages = { 14-19 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume15/number5/1946-2602/ },
doi = { 10.5120/1946-2602 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:03:20.777653+05:30
%A Lahcene Aid
%A Malik Loudini
%A Walid-Khaled Hidouci
%T An Admission Control Mechanism for Web Servers using Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 15
%N 5
%P 14-19
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Web sites are exposed to high rates of incoming requests. During temporary traffic peaks, web servers may become overloaded and their services deteriorate drastically. In this paper, we propose a method for admission control to prevent and control overloads in web servers by utilizing neural network (NN). The control decision is based on the desired web server performance criteria: average response time, blocking probability and throughput of web server. We have designed and developed a NN model able to predict web server performance metrics based on the parameters of the Apache server, the core of the Linux system and arrival traffic. The model predictor captures the complex relationship between web server performance and its configuration. This avoids an ad-hoc web server configuration, which poses significant challenges to the server performance and quality of service (QoS).

References
  1. Parekh S., Gandhi N., Hellerstein J., Tilbury D., Jayram T. and Bigus J. 2002. Using Control Theory to Achieve Service Level Objectives In Performance Management. Real-Time Syst., 23(1-2), 127–141.
  2. Diao Y., Gandhi N., Hellerstein J., Parekh S. and Tilbury D. 2002. Using MIMO feedback control to enforce policies for interrelated metrics with application to the Apache Web server. In Proceedings of the Network Operations and Management Symposium.
  3. Cao J. and Nyberg C. 2002. On overload control through queue length for web servers, in Proceedings of the 16th Nordic Teletraffic Seminar NTS16, Helsinki University of Technology, Espoo, Finland.
  4. Robertsson A., Wittenmark B., Kihl M. and Andersson M. 2004. Admission control for web server systems - design and experimental evaluation. In Proceedings of the 43rd IEEE Conference on Decision and Control, (Dec. 2004).
  5. Elnikety S., Nahum E., Tracey J. and Zwaenepoel W. 2004. Method for Transparent Admission Control and Request Scheduling in E-CommerceWeb Sites. In 13th international conference on World Wide Web, New York, NY, (May. 2004).
  6. Heiss H.-U. and Wagner R. 1991. Adaptive Load Control in Transaction Processing Systems. In 17th International Conference on Very Large Data Bases, San Francisco, CA, USA.
  7. Apache web server, http://www.apache.org.
  8. Stallings W. 2000. Data & Computer Communications. Prentice Hall, sixth Edition.
  9. December 2010 Web server survey by Netcraft, http://news.netcraft.com/.
  10. Linux manual page, http://linux.die.net/man/2/listen
  11. Du K. -L. and Swamy M. N. S. 2006. Neural Networks in a Softcomputing Framework, Springer-Verlag London Limited.
  12. Leondes C. T. 1998. Neural Network Systems Techniques and Applications. Vol. N°1. Academic Press, California.
  13. Rumelhart D. E., Hinton G. E. and Williams R. J. 1986. Learning internal representations by error propagation. In: Rumelhart DE, McClelland JL (eds) Parallel distributed processing: Explorations in the microstructure of cognition, 1:Foundation, 318–362. MIT Press, Cambridge, USA.
  14. HTTPerf – Mosberger D. and Jin T. 1998. A Tool for Measuring Web Server Performance. HP Research Labs. (December. 1998), volume 26 issue 3, ACM Sigmetrics Performance Evaluation Review.
  15. Tiaret university website, http://www.univ-tiaret.dz.
  16. Hastie T., Tibshirani R. and Friedman J. 2002. The Elements of Statistical Learning: Data Mining, Inference, and Prediction. Springer-Verlag, New York.
  17. Setiono R. 2001. Feedforward neural network construction using crossvalidation. Neural Comput. 13, 2865–2877.
  18. Purdy G. N. 2004. Linux iptables Pocket Reference, O’Reilly Media Inc, Sebastopol, California, USA.
Index Terms

Computer Science
Information Sciences

Keywords

Web server Admission control QoS Neural networks

Powered by PhDFocusTM