Cover Image

Application of extreme value theory to bursts prediction

Bursts and extreme events in quantities such as connection durations, file sizes, throughput, etc. may produce undesirable consequences in computer networks. Deterioration in the quality of service is a major consequence. Predicting these extreme events and burst is important. It helps in reserving...

Full description

Saved in:
Bibliographic Details
Main Authors: Youssouf Dahab, Abdelmahamoud, Md Said, Abas, Hasbullah, Halabi
Format: Citation Index Journal
Published: CSC Publishers, vol.3, no.4, pp.55-63, 2009 2009
Subjects:
T Technology (General)
Online Access:http://eprints.utp.edu.my/4581/2/SPIJ-28.pdf
http://www.cscjournals.org/csc/manuscript/Journals/SPIJ/volume3/Issue4/SPIJ-28.pdf
http://eprints.utp.edu.my/4581/
Tags: Add Tag
No Tags, Be the first to tag this record!
id my.utp.eprints.4581
record_format eprints
spelling my.utp.eprints.45812017-01-19T08:25:18Z Application of extreme value theory to bursts prediction Youssouf Dahab, Abdelmahamoud Md Said, Abas Hasbullah, Halabi T Technology (General) Bursts and extreme events in quantities such as connection durations, file sizes, throughput, etc. may produce undesirable consequences in computer networks. Deterioration in the quality of service is a major consequence. Predicting these extreme events and burst is important. It helps in reserving the right resources for a better quality of service. We applied Extreme value theory (EVT) to predict bursts in network traffic. We took a deeper look into the application of EVT by using EVT based Exploratory Data Analysis. We found that traffic is naturally divided into two categories, Internal and external traffic. The internal traffic follows generalized extreme value (GEV) model with a negative shape parameter, which is also the same as Weibull distribution. The external traffic follows a GEV with positive shape parameter, which is Frechet distribution. These findings are of great value to the quality of service in data networks, especially when included in service level agreement as traffic descriptor parameters. CSC Publishers, vol.3, no.4, pp.55-63, 2009 2009-08 Citation Index Journal PeerReviewed application/pdf http://eprints.utp.edu.my/4581/2/SPIJ-28.pdf http://www.cscjournals.org/csc/manuscript/Journals/SPIJ/volume3/Issue4/SPIJ-28.pdf Youssouf Dahab, Abdelmahamoud and Md Said, Abas and Hasbullah, Halabi (2009) Application of extreme value theory to bursts prediction. [Citation Index Journal] http://eprints.utp.edu.my/4581/
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Institutional Repository
url_provider http://eprints.utp.edu.my/
topic T Technology (General)
spellingShingle T Technology (General)
Youssouf Dahab, Abdelmahamoud
Md Said, Abas
Hasbullah, Halabi
Application of extreme value theory to bursts prediction
description Bursts and extreme events in quantities such as connection durations, file sizes, throughput, etc. may produce undesirable consequences in computer networks. Deterioration in the quality of service is a major consequence. Predicting these extreme events and burst is important. It helps in reserving the right resources for a better quality of service. We applied Extreme value theory (EVT) to predict bursts in network traffic. We took a deeper look into the application of EVT by using EVT based Exploratory Data Analysis. We found that traffic is naturally divided into two categories, Internal and external traffic. The internal traffic follows generalized extreme value (GEV) model with a negative shape parameter, which is also the same as Weibull distribution. The external traffic follows a GEV with positive shape parameter, which is Frechet distribution. These findings are of great value to the quality of service in data networks, especially when included in service level agreement as traffic descriptor parameters.
format Citation Index Journal
author Youssouf Dahab, Abdelmahamoud
Md Said, Abas
Hasbullah, Halabi
author_facet Youssouf Dahab, Abdelmahamoud
Md Said, Abas
Hasbullah, Halabi
author_sort Youssouf Dahab, Abdelmahamoud
title Application of extreme value theory to bursts prediction
title_short Application of extreme value theory to bursts prediction
title_full Application of extreme value theory to bursts prediction
title_fullStr Application of extreme value theory to bursts prediction
title_full_unstemmed Application of extreme value theory to bursts prediction
title_sort application of extreme value theory to bursts prediction
publisher CSC Publishers, vol.3, no.4, pp.55-63, 2009
publishDate 2009
url http://eprints.utp.edu.my/4581/2/SPIJ-28.pdf
http://www.cscjournals.org/csc/manuscript/Journals/SPIJ/volume3/Issue4/SPIJ-28.pdf
http://eprints.utp.edu.my/4581/
_version_ 1738655354321895424
score 13.211869

Similar Items