Self-similar network traffic using Successive Random Addition (SRA) algorithm / Hani Hamira Harun

Self-similar traffic has an underlying dependence structure which exhibits long-range dependence. This is in contrast to classical traffic models, such as Poisson, which exhibit short-range dependence. Self-similar traffic may also exhibit short-range dependence, but this is on its own insufficie...

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第一著者: Harun, Hani Hamira
フォーマット: 学位論文
言語:English
出版事項: 2006
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オンライン・アクセス:http://ir.uitm.edu.my/id/eprint/850/1/TB_HANI%20HAMIRA%20HARUN%20%20CS%2006_5%20P01.pdf
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spelling my.uitm.ir.8502018-10-30T02:25:56Z http://ir.uitm.edu.my/id/eprint/850/ Self-similar network traffic using Successive Random Addition (SRA) algorithm / Hani Hamira Harun Harun, Hani Hamira Electronic Computers. Computer Science Self-similar traffic has an underlying dependence structure which exhibits long-range dependence. This is in contrast to classical traffic models, such as Poisson, which exhibit short-range dependence. Self-similar traffic may also exhibit short-range dependence, but this is on its own insufficient to accurately parametric the traffic. Studying self-similar traffic requires models for analytical work and generators for simulation. Having generating algorithms that close to reflect real traffic is important as they allow us to perform simulations that are similar to the real network traffic. Without this, the results from simulations would not accurately reflect the results that would be expected in the real world. In this project, we have used the Successive random algorithm (SRA). Then, we have decided to use Variance time plot and R/S statistics as our statistical analysis tools. We have test the sample path between 0.5<H<1. After we test on the SRA algorithm, we found that the results are not accurate. But compares to RMD, the SRA samples result be more accurate. In term data generation, SRA be slower than dFGN. COPYRIGHT 2006 Thesis NonPeerReviewed text en http://ir.uitm.edu.my/id/eprint/850/1/TB_HANI%20HAMIRA%20HARUN%20%20CS%2006_5%20P01.pdf Harun, Hani Hamira (2006) Self-similar network traffic using Successive Random Addition (SRA) algorithm / Hani Hamira Harun. Degree thesis, Universiti Teknologi MARA.
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 Electronic Computers. Computer Science
spellingShingle Electronic Computers. Computer Science
Harun, Hani Hamira
Self-similar network traffic using Successive Random Addition (SRA) algorithm / Hani Hamira Harun
description Self-similar traffic has an underlying dependence structure which exhibits long-range dependence. This is in contrast to classical traffic models, such as Poisson, which exhibit short-range dependence. Self-similar traffic may also exhibit short-range dependence, but this is on its own insufficient to accurately parametric the traffic. Studying self-similar traffic requires models for analytical work and generators for simulation. Having generating algorithms that close to reflect real traffic is important as they allow us to perform simulations that are similar to the real network traffic. Without this, the results from simulations would not accurately reflect the results that would be expected in the real world. In this project, we have used the Successive random algorithm (SRA). Then, we have decided to use Variance time plot and R/S statistics as our statistical analysis tools. We have test the sample path between 0.5<H<1. After we test on the SRA algorithm, we found that the results are not accurate. But compares to RMD, the SRA samples result be more accurate. In term data generation, SRA be slower than dFGN. COPYRIGHT
format Thesis
author Harun, Hani Hamira
author_facet Harun, Hani Hamira
author_sort Harun, Hani Hamira
title Self-similar network traffic using Successive Random Addition (SRA) algorithm / Hani Hamira Harun
title_short Self-similar network traffic using Successive Random Addition (SRA) algorithm / Hani Hamira Harun
title_full Self-similar network traffic using Successive Random Addition (SRA) algorithm / Hani Hamira Harun
title_fullStr Self-similar network traffic using Successive Random Addition (SRA) algorithm / Hani Hamira Harun
title_full_unstemmed Self-similar network traffic using Successive Random Addition (SRA) algorithm / Hani Hamira Harun
title_sort self-similar network traffic using successive random addition (sra) algorithm / hani hamira harun
publishDate 2006
url http://ir.uitm.edu.my/id/eprint/850/1/TB_HANI%20HAMIRA%20HARUN%20%20CS%2006_5%20P01.pdf
http://ir.uitm.edu.my/id/eprint/850/
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score 13.250246