*Self-similar network traffic using Random Midpoint Displacement (RMD) algorithm / Jumaliah Saarini.*[Student Project] (Unpublished)

## Abstract

This project is to generate the self-similar network traffic. It is generally accepted

that self-similar or fractal process may provide better models for in modern network

traffic than Poisson process. Poisson arrival processes are not self-similar, regardless

of degree of aggregation. The way to solve this problem, we applied the existed

method in visual C++ programming with used the Random midpoint Displacement

(RMD) algorithm. That program we need the sequence of the random number as a

data. The data was generated depends on the power of two of data. The numbers of

data will be analyzed using the R/S Statistic program and Variance Time Plot

program. That analysis programs were running in MathCAD v12 platform. The graft

will be display after the data is running in the analysis programs as result. The new

values of Hurst will be appear as a results whether the self-similar or not. After the

analysis process, the result from the R/S Statistic and Variance Tome Plot were not

accurate. The new value of Hurst was not exactly same with the expected value of

Hurst. As a conclusion, using RMD algorithm the result are more satisfy compare

using the traditional process because the result are more accurate are more faster.

The RMD fastest in term of computational time but do not accurately reflect the

Hurst parameter.

## Metadata

Item Type: | Student Project |
---|---|

Creators: | Creators Email / ID Num. Saarini, Jumaliah UNSPECIFIED |

Subjects: | Q Science > QA Mathematics > Instruments and machines > Electronic Computers. Computer Science T Technology > TK Electrical engineering. Electronics. Nuclear engineering > Telecommunication > Computer networks. General works. Traffic monitoring |

Divisions: | Universiti Teknologi MARA, Shah Alam > Faculty of Computer and Mathematical Sciences |

Date: | 2006 |

URI: | https://ir.uitm.edu.my/id/eprint/853 |

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