一种基于FGN和IDFT的自相似通信量生成算法

A new self-similar teletraffic generation arithmetic based on FGN and IDFT

对网络模拟中必需的自相似通信量生成方法进行了研究,提出了一种基于分数高斯噪声(FGN,fractionalGaussiannoise)过程和逆离散傅立叶变换(IDFF,inversediscreteFouriertransform)的自相似通信量生成算法--FGN-IDFT算法,并通过仿真实验和比较分析的方法对该算法的精度和计算复杂度进行了大量的实验和分析。研究结果表明,利用FGN-IDFT算法生成的自相似通信量的精度和速度都令人满意,为实际网络模拟的进一步深入研究提供了基础。

Necessary self-similar teletraffic generation methods of simulating network traffic were studied, and a new arithmetic for generating self-similar teletraffic, based on fractional Gaussian noise (FGN) and inverse discrete Fourier transform (IDFT), was proposed and analysed in this paper. The statistical accuracy and complexity and time required to produce sequences of a given length were experimentally studied and comparatively analysed. This arithmetic shows a high level of accuracy of the generated self-similar teletraffic and is fast, and it provides the foundation for real network simulation.