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

Ayop, Nor Azura (2016) Adaptive policing and shaping algorithms on inbound traffic using generalized Pareto distribution: article / Nor Azura Ayop. pp. 1-9.

Abstract

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. The objective of this research is to characterize inbound internet traffic collected on real live IP-based campus network. 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. Open Distribution Fitting application is fitted to the collected data to identifying the best distribution and the results presents Generalized Pareto shows the highest value for best fitted traffic model. Log likelihood estimation technique is used to fitted the best 2-parameter CDF compared to WeibuII, 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.

Metadata

Item Type: Article
Creators:
Creators
Email / ID Num.
Ayop, Nor Azura
azuraayop@gmail.com
Subjects: T Technology > TK Electrical engineering. Electronics. Nuclear engineering
Divisions: Universiti Teknologi MARA, Shah Alam > Faculty of Electrical Engineering
Page Range: pp. 1-9
Related URLs:
Keywords: Internet traffic, bandwidth management, time processing, policing, shaping, algorithm, Generalized Pareto, Weibull, Normal, Rician, distribution
Date: 2016
URI: https://ir.uitm.edu.my/id/eprint/13000
Edit Item
Edit Item

Download

[thumbnail of 13000.pdf] Text
13000.pdf

Download (743kB)

ID Number

13000

Indexing

Statistic

Statistic details