Network traffic data analysis based on DGX
Zou Dan, Jun Liu, Qing Wen Yan · 2017
Skewed data appear frequently in network traffic data, this paper focuses on modeling and analyzing these skewed data. The research on data distribution model plays an important role in data mining. In many fields of science, various models have been proposed to describe skewed data. Most of them only perform well for particular data sets, but fail with others. The purpose of this paper is to fit and analyze the skewed data in network traffic data with Discrete Gaussian Exponential (DGX), and to estimate the model parameters with genetic algorithm.