Web server's reliability improvements using recurrent neural networks

Henrik Madsen; Rǎzvan-Daniel Albu; Ioan Felea; Albeanu Grigore; Florin Popentiu; Radu Catalin Ţarcǎ

Web server's reliability improvements using recurrent neural networks

Henrik Madsen
, Rǎzvan-Daniel Albu
, Ioan Felea
, Albeanu Grigore
, Florin Popentiu
, Radu Catalin Ţarcǎ

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Abstract

In this paper we describe an interesting approach to error prediction illustrated by experimental results. The application consists of monitoring the activity for the web servers in order to collect the specific data. Predicting an error with severe consequences for the performance of a server (the result of which is that its functionality becomes totally inaccessible or hard to access for clients) requires measuring the capacity of a server at any given time. This measurement is highly complex, if not impossible. There are several variables which we can measure on a running system, such as: CPU usage, network usage and memory usage. We collect different data sets from monitoring the web server's activity and for each one we predict the server's reliability with the proposed recurrent neural network. © 2012 Taylor & Francis Group

Original language	English
Title of host publication	Advances in Safety, Reliability and Risk Management : Proceedings Of The European Safety And Reliability Conference, Esrel 2011, Troyes, France, 18–22 September 2011
Editors	Christophe Bérenguer, Antoine Grall, C. Guedes Soares
Place of Publication	London
Publisher	Taylor & Francis
Publication date	2012
Pages	441-444
ISBN (Print)	978-0-415-68379-1
Publication status	Published - 2012
Event	European Safety and Reliability Conference 2011 - Troyes, France Duration: 18 Sept 2011 → 22 Sept 2011 Conference number: 20 http://www1.utt.fr/esrel2011/

Conference

Conference	European Safety and Reliability Conference 2011
Number	20
Country/Territory	France
City	Troyes
Period	18/09/2011 → 22/09/2011
Internet address	http://www1.utt.fr/esrel2011/

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Madsen, H., Albu, R.-D., Felea, I., Grigore, A., Popentiu, F., & Ţarcǎ, R. C. (2012). Web server's reliability improvements using recurrent neural networks. In C. Bérenguer, A. Grall, & C. Guedes Soares (Eds.), Advances in Safety, Reliability and Risk Management: Proceedings Of The European Safety And Reliability Conference, Esrel 2011, Troyes, France, 18–22 September 2011 (pp. 441-444). Taylor & Francis.

Madsen, Henrik ; Albu, Rǎzvan-Daniel ; Felea, Ioan et al. / Web server's reliability improvements using recurrent neural networks. Advances in Safety, Reliability and Risk Management: Proceedings Of The European Safety And Reliability Conference, Esrel 2011, Troyes, France, 18–22 September 2011. editor / Christophe Bérenguer ; Antoine Grall ; C. Guedes Soares. London : Taylor & Francis, 2012. pp. 441-444

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title = "Web server's reliability improvements using recurrent neural networks",

abstract = "In this paper we describe an interesting approach to error prediction illustrated by experimental results. The application consists of monitoring the activity for the web servers in order to collect the specific data. Predicting an error with severe consequences for the performance of a server (the result of which is that its functionality becomes totally inaccessible or hard to access for clients) requires measuring the capacity of a server at any given time. This measurement is highly complex, if not impossible. There are several variables which we can measure on a running system, such as: CPU usage, network usage and memory usage. We collect different data sets from monitoring the web server's activity and for each one we predict the server's reliability with the proposed recurrent neural network. {\textcopyright} 2012 Taylor \& Francis Group",

author = "Henrik Madsen and R{\v a}zvan-Daniel Albu and Ioan Felea and Albeanu Grigore and Florin Popentiu and {\c T}arc{\v a}, \{Radu Catalin\}",

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language = "English",

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booktitle = "Advances in Safety, Reliability and Risk Management",

publisher = "Taylor \& Francis",

note = "European Safety and Reliability Conference 2011, ESREL 2011 ; Conference date: 18-09-2011 Through 22-09-2011",

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Madsen, H, Albu, R-D, Felea, I, Grigore, A, Popentiu, F & Ţarcǎ, RC 2012, Web server's reliability improvements using recurrent neural networks. in C Bérenguer, A Grall & C Guedes Soares (eds), Advances in Safety, Reliability and Risk Management: Proceedings Of The European Safety And Reliability Conference, Esrel 2011, Troyes, France, 18–22 September 2011. Taylor & Francis, London, pp. 441-444, European Safety and Reliability Conference 2011, Troyes, France, 18/09/2011.

Web server's reliability improvements using recurrent neural networks. / Madsen, Henrik; Albu, Rǎzvan-Daniel; Felea, Ioan et al.
Advances in Safety, Reliability and Risk Management: Proceedings Of The European Safety And Reliability Conference, Esrel 2011, Troyes, France, 18–22 September 2011. ed. / Christophe Bérenguer; Antoine Grall; C. Guedes Soares. London: Taylor & Francis, 2012. p. 441-444.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

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AU - Grigore, Albeanu

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AU - Ţarcǎ, Radu Catalin

N1 - Conference code: 20

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AB - In this paper we describe an interesting approach to error prediction illustrated by experimental results. The application consists of monitoring the activity for the web servers in order to collect the specific data. Predicting an error with severe consequences for the performance of a server (the result of which is that its functionality becomes totally inaccessible or hard to access for clients) requires measuring the capacity of a server at any given time. This measurement is highly complex, if not impossible. There are several variables which we can measure on a running system, such as: CPU usage, network usage and memory usage. We collect different data sets from monitoring the web server's activity and for each one we predict the server's reliability with the proposed recurrent neural network. © 2012 Taylor & Francis Group

M3 - Article in proceedings

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EP - 444

BT - Advances in Safety, Reliability and Risk Management

A2 - Bérenguer, Christophe

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PB - Taylor & Francis

CY - London

T2 - European Safety and Reliability Conference 2011

Y2 - 18 September 2011 through 22 September 2011

ER -

Madsen H, Albu RD, Felea I, Grigore A, Popentiu F, Ţarcǎ RC. Web server's reliability improvements using recurrent neural networks. In Bérenguer C, Grall A, Guedes Soares C, editors, Advances in Safety, Reliability and Risk Management: Proceedings Of The European Safety And Reliability Conference, Esrel 2011, Troyes, France, 18–22 September 2011. London: Taylor & Francis. 2012. p. 441-444

Web server's reliability improvements using recurrent neural networks

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