Simulation of Self-similarFlow Based on Fractal Gaussian Noise Method
- 10.2991/icsnce-18.2018.27How to use a DOI?
- Self-similarity; Traffic Flow; FGN; R/S
The conventional network traffic flow models are mostly based on Poisson model . With the continuous development of network services, studies found that the actual network traffic has a long-range dependence (LRD) now and in a very long time , which is a kind of self-similarity. In this paper, RMD and Fourier algorithm were adopted to simulate and analyze a self-similar model of FGN. They generated the necessary sequence of self-similar traffic. Then the article uses R/S method to verify H value of the generated sequence of self-similar traffic in order to verify the self-similarity of the self-similar traffic sequence. The existence of self-similarity is verified by experiments, and the advantage and disadvantage of RMD and Fourier algorithm are analyzed.
- © 2018, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Li Jie AU - Lu Ying AU - Tang Junyong PY - 2018/04 DA - 2018/04 TI - Simulation of Self-similarFlow Based on Fractal Gaussian Noise Method BT - Proceedings of the 2018 Second International Conference of Sensor Network and Computer Engineering (ICSNCE 2018) PB - Atlantis Press SP - 133 EP - 137 SN - 2352-538X UR - https://doi.org/10.2991/icsnce-18.2018.27 DO - 10.2991/icsnce-18.2018.27 ID - Jie2018/04 ER -