Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop

This paper present an analysis of inbound internet traffic and development of Adaptive Policing and Shaping Algorithms on inbound internet traffic and fitted to traffic model. Network "bursting" is a normal event in internet traffic engineering, but the bustiness of throughput data will vi...

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Main Author: Ayop, Nor Azura
Format: Thesis
Language:English
Published: 2016
Subjects:
Online Access:https://ir.uitm.edu.my/id/eprint/80926/1/80926.pdf
https://ir.uitm.edu.my/id/eprint/80926/
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spelling my.uitm.ir.809262024-07-28T07:26:55Z https://ir.uitm.edu.my/id/eprint/80926/ Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop Ayop, Nor Azura Telecommunication This paper present an analysis of inbound internet traffic and development of Adaptive Policing and Shaping Algorithms on inbound internet traffic and fitted to traffic model. Network "bursting" is a normal event in internet traffic engineering, but the bustiness of throughput data will violent the committed rate that provided by ISP. The objective of this research is to characterize inbound internet traffic collected on real live IP-based campus network, to develop Adaptive Policing and Shaping Algorithms with percentage level on Inbound Traffic based on traffic characterization and to compare the policing and shaping performance on bandwidth used, processing time and packet loss. Then, traffic is fitted to best traffic model and percentage level Policing and Shaping algorithm is developed to control the bandwidth used. The research scope is based on collected of internet traffic on IP-based network real live traffic at 16 Mbps speed line. By using MATLAB software, the Open Distribution Fitting application is fitted to the collected data to identifying the best distribution and the results presents GPD shows the highest value for best fitted traffic model. Log likelihood estimation technique is used to fit the best 2-parameter CDF compared to Weibull, Normal and Rician distribution model. The percentage level 5% under original bandwidth used is developed on policing and shaping algorithms to control bandwidth used. Result present performances upgraded around 3% of time processing and approximately 73% of bandwidth saved. This result help to expand the view of new idea in modelling the tele-traffic algorithm based on bandwidth management and time processing improvement. The most important matter is the understanding about the internet traffic's flow and characteristic. 2016 Thesis NonPeerReviewed text en https://ir.uitm.edu.my/id/eprint/80926/1/80926.pdf Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop. (2016) Masters thesis, thesis, Universiti Teknologi MARA (UiTM).
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Telecommunication
spellingShingle Telecommunication
Ayop, Nor Azura
Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
description This paper present an analysis of inbound internet traffic and development of Adaptive Policing and Shaping Algorithms on inbound internet traffic and fitted to traffic model. Network "bursting" is a normal event in internet traffic engineering, but the bustiness of throughput data will violent the committed rate that provided by ISP. The objective of this research is to characterize inbound internet traffic collected on real live IP-based campus network, to develop Adaptive Policing and Shaping Algorithms with percentage level on Inbound Traffic based on traffic characterization and to compare the policing and shaping performance on bandwidth used, processing time and packet loss. Then, traffic is fitted to best traffic model and percentage level Policing and Shaping algorithm is developed to control the bandwidth used. The research scope is based on collected of internet traffic on IP-based network real live traffic at 16 Mbps speed line. By using MATLAB software, the Open Distribution Fitting application is fitted to the collected data to identifying the best distribution and the results presents GPD shows the highest value for best fitted traffic model. Log likelihood estimation technique is used to fit the best 2-parameter CDF compared to Weibull, Normal and Rician distribution model. The percentage level 5% under original bandwidth used is developed on policing and shaping algorithms to control bandwidth used. Result present performances upgraded around 3% of time processing and approximately 73% of bandwidth saved. This result help to expand the view of new idea in modelling the tele-traffic algorithm based on bandwidth management and time processing improvement. The most important matter is the understanding about the internet traffic's flow and characteristic.
format Thesis
author Ayop, Nor Azura
author_facet Ayop, Nor Azura
author_sort Ayop, Nor Azura
title Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
title_short Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
title_full Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
title_fullStr Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
title_full_unstemmed Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution / Nor Azura Ayop
title_sort adaptive policing and shaping algorithms on inbound traffic using generalized pareto distribution / nor azura ayop
publishDate 2016
url https://ir.uitm.edu.my/id/eprint/80926/1/80926.pdf
https://ir.uitm.edu.my/id/eprint/80926/
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score 13.211869