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An Admission Control Mechanism for Web Servers using Neural Network

by Lahcene Aid, Malik Loudini, Walid-Khaled Hidouci
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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).

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Index Terms

Computer Science
Information Sciences

Keywords

Web server Admission control QoS Neural networks

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