一种视频会议业务流的Gamma-Beta多重分形模型

针对计算机网络中的视频会议业务流,提出了一种新的Gamma Beta多重分形模型。这种模型基于视频会议业务流的Gamma分布特性,采用Beta分布产生多重分形的乘子。与普通的多重分形模型不同的是,新模型充分考虑了视频业务流在各个不同时间尺度的概率分布特性,确保其在不同的时间尺度上都能拟合源数据的分布。由于决定网络业务流排队分析特性的关键时间尺度是随着缓冲区的容量和节点传输速率而变化的,提出的模型能描述几乎各个时间尺度上的业务流特性,因此能适应各种不同情况的缓冲区的排队分析。最后,通过对视频业务流的仿真实验与排队分析验证了模型的有效性。

Gamma-Beta based multifractal model for video conference traffic

A new Gamma-Beta based multifractal model for video conference traffic in the computer networks is proposed. As the video traffic is almost Gamma distributed at every time-scales, the proposed model uses a Beta distributed multiplier to generate the multifractal process. Differed from the normal multifractal model, the new model can match the marginal distribution of the source traffic at all the time-scales. As the buffer overflow probability is determined by a critical time scale (CTS) which varies with the buffer size and the link rate, the proposed model can match the marginal distributions of all the time-scales, thus it can be used to analysis different buffers. Finally, the video traffic-driven simulation and queueing analysis show the effectiveness of the proposed model.