Li, Ming and Lim, S. C. and Feng, Huamin
(2007)
*Generating traffic time series based on generalized cauchy process.*
In:
Computational Science – ICCS 2007.
Lecture Notes in Computer Science
(4487).
Springer Berlin Heidelberg, pp. 374-381.
ISBN 978-3-540-72583-1

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## Abstract

Generating traffic time series (traffic for short) is important in networking, e.g., simulating the Internet. In this aspect, it is desired to generate a time series according to a given correlation structure that may well reflect the statistics of real traffic. Recent research of traffic modeling exhibits that traffic is well modeled by a type of Gaussian process called the generalized Cauchy (GC) process indexed by two parameters that separately characterize the self-similarity (SS), which is local property described by fractal dimension D, and long-range dependence (LRD), which is a global feature that can be measured by the Hurst parameter H, instead of using the linear relationship D = 2 − H as that used in traditional traffic model with a single parameter such as fractional Gaussian noise (FGN). This paper presents a computational method to generate series based on the correlation form of GC process indexed by 2 parameters. Hence, the present model can be used to simulate realizations that flexibly capture the fractal phenomena of real traffic for both short-term lags and long-term lags.

Item Type: | Book Section |
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Additional Information: | Book Subtitle: 7th International Conference, Beijing, China, May 27 - 30, 2007, Proceedings, Part I |

Subjects: | T Technology > T Technology (General) |

Divisions: | Faculty of Engineering (FOE) |

Depositing User: | Ms Rosnani Abd Wahab |

Date Deposited: | 04 Feb 2014 04:23 |

Last Modified: | 04 Feb 2014 04:23 |

URI: | http://shdl.mmu.edu.my/id/eprint/5062 |

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