PREDICTING INTERNET TRAFFIC BURSTS USING EXTREME VALUE THEORY

Computer networks play an important role in today’s organization and people life. These interconnected devices share a common medium and they tend to compete for it. Quality of Service (QoS) comes into play as to define what level of services users get. Accurately defining the QoS metrics is thus...

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Main Author: YOUSSOUF DAHAB, ABDELMAHAMOUD YOUSSOUF DAHAB
Format: Thesis
Language:English
Published: 2011
Online Access:http://utpedia.utp.edu.my/2834/1/Abdelmahamoud_Youssouf_Dahab_PhD_Thesis_%28Predicting_Internet_Traffic_Bursts_using_Extreme_Value_Theory%29.pdf
http://utpedia.utp.edu.my/2834/
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spelling my-utp-utpedia.28342017-01-25T09:42:27Z http://utpedia.utp.edu.my/2834/ PREDICTING INTERNET TRAFFIC BURSTS USING EXTREME VALUE THEORY YOUSSOUF DAHAB, ABDELMAHAMOUD YOUSSOUF DAHAB Computer networks play an important role in today’s organization and people life. These interconnected devices share a common medium and they tend to compete for it. Quality of Service (QoS) comes into play as to define what level of services users get. Accurately defining the QoS metrics is thus important. Bursts and serious deteriorations are omnipresent in Internet and considered as an important aspects of it. This thesis examines bursts and serious deteriorations in Internet traffic and applies Extreme Value Theory (EVT) to their prediction and modelling. EVT itself is a field of statistics that has been in application in fields like hydrology and finance, with only a recent introduction to the field of telecommunications. Model fitting is based on real traces from Belcore laboratory along with some simulated traces based on fractional Gaussian noise and linear fractional alpha stable motion. QoS traces from University of Napoli are also used in the prediction stage. Three methods from EVT are successfully used for the bursts prediction problem. They are Block Maxima (BM) method, Peaks Over Threshold (POT) method, and RLargest Order Statistics (RLOS) method. Bursts in internet traffic are predicted using the above three methods. A clear methodology was developed for the bursts prediction problem. New metrics for QoS are suggested based on Return Level and Return Period. Thus, robust QoS metrics can be defined. In turn, a superior QoS will be obtained that would support mission critical applications. 2011-05 Thesis NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/2834/1/Abdelmahamoud_Youssouf_Dahab_PhD_Thesis_%28Predicting_Internet_Traffic_Bursts_using_Extreme_Value_Theory%29.pdf YOUSSOUF DAHAB, ABDELMAHAMOUD YOUSSOUF DAHAB (2011) PREDICTING INTERNET TRAFFIC BURSTS USING EXTREME VALUE THEORY. PhD thesis, UNIVERSITI TEKNOLOGI PETRONAS.
institution Universiti Teknologi Petronas
building UTP Resource Centre
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Petronas
content_source UTP Electronic and Digitized Intellectual Asset
url_provider http://utpedia.utp.edu.my/
language English
description Computer networks play an important role in today’s organization and people life. These interconnected devices share a common medium and they tend to compete for it. Quality of Service (QoS) comes into play as to define what level of services users get. Accurately defining the QoS metrics is thus important. Bursts and serious deteriorations are omnipresent in Internet and considered as an important aspects of it. This thesis examines bursts and serious deteriorations in Internet traffic and applies Extreme Value Theory (EVT) to their prediction and modelling. EVT itself is a field of statistics that has been in application in fields like hydrology and finance, with only a recent introduction to the field of telecommunications. Model fitting is based on real traces from Belcore laboratory along with some simulated traces based on fractional Gaussian noise and linear fractional alpha stable motion. QoS traces from University of Napoli are also used in the prediction stage. Three methods from EVT are successfully used for the bursts prediction problem. They are Block Maxima (BM) method, Peaks Over Threshold (POT) method, and RLargest Order Statistics (RLOS) method. Bursts in internet traffic are predicted using the above three methods. A clear methodology was developed for the bursts prediction problem. New metrics for QoS are suggested based on Return Level and Return Period. Thus, robust QoS metrics can be defined. In turn, a superior QoS will be obtained that would support mission critical applications.
format Thesis
author YOUSSOUF DAHAB, ABDELMAHAMOUD YOUSSOUF DAHAB
spellingShingle YOUSSOUF DAHAB, ABDELMAHAMOUD YOUSSOUF DAHAB
PREDICTING INTERNET TRAFFIC BURSTS USING EXTREME VALUE THEORY
author_facet YOUSSOUF DAHAB, ABDELMAHAMOUD YOUSSOUF DAHAB
author_sort YOUSSOUF DAHAB, ABDELMAHAMOUD YOUSSOUF DAHAB
title PREDICTING INTERNET TRAFFIC BURSTS USING EXTREME VALUE THEORY
title_short PREDICTING INTERNET TRAFFIC BURSTS USING EXTREME VALUE THEORY
title_full PREDICTING INTERNET TRAFFIC BURSTS USING EXTREME VALUE THEORY
title_fullStr PREDICTING INTERNET TRAFFIC BURSTS USING EXTREME VALUE THEORY
title_full_unstemmed PREDICTING INTERNET TRAFFIC BURSTS USING EXTREME VALUE THEORY
title_sort predicting internet traffic bursts using extreme value theory
publishDate 2011
url http://utpedia.utp.edu.my/2834/1/Abdelmahamoud_Youssouf_Dahab_PhD_Thesis_%28Predicting_Internet_Traffic_Bursts_using_Extreme_Value_Theory%29.pdf
http://utpedia.utp.edu.my/2834/
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score 13.18916