Hybrid Multi-Scale Modeling of Network Traffic
This paper presents a hybrid multi-scale modeling of network traffic based on wavelet transform, Poisson process and fractal geometry. It demonstrates that network traffic has statistical properties and self-similarity at different scales. Both sharp time behavior and long-range dependence of network traffic can be well simulated by our model. A classic algorithm is improved to calculate the Hurst parameters and a new algorithm is also presented to calculate the Holder index based on the space characterization properties of wavelet basis. Comparing to former works our model provides several more parameters to characterize network traffic. The efficiency of this model is verified by using DARPA Intrusion Detection Evaluation dataset. The result shows that our model is effective to simulate network traffic.
multi-scale network traffic wavelet Poisson process multi-fractal
Jicheng Hu Ying Wang Rensheng Dou
State Key Lab of Software Engineering, Wuhan University C.J.Huang Institute of Information Technology, Wuhan University
国际会议
武汉
英文
987-990
2005-09-23（万方平台首次上网日期，不代表论文的发表时间）