Network Traffic Hurst Parameter Estimation And GUI System Design Based On Golden Section Search Algorithm

Network traffic has always been one of the focuses in the field of network research,which has important significance for understanding network behavior,improving network performance,and ensuring network security.Network traffic is a typical long-range dependence signal.Many models have been applied to the study of it,and these models have common core parameters,namely Hurst exponent.Hurst exponent is not only important for modeling,but also has important reference for studying the characteristics of network traffic.Many Hurst exponent estimation methods have been put forward by experts.However,some of these methods have limitation in computational efficiency,which seriously affect the demand for Hurst exponential calculation in certain fields and occasions.Therefore,an algorithm with high computational efficiency and accuracy is of great significance for the study of network traffic.In Chapter 1,we introduce the significance of the Hurst exponent estimation algorithm for network traffic and the research status at home and abroad.In Chapter 2,we introduce the traditional Hurst exponent estimation method and analyze shortcomings of these methods.The third and fourth chapter propose the golden section search algorithm and the random search algorithm for the shortcomings of traditional algorithms.In Chapter 5,we use the actual network traffic data to apply the algorithms mentioned in this paper to experiment and then compare the differences in computing efficiency.In chapter 6,we build a network traffic Hurst exponent estimation software based on GUI platform of MATLAB.The main contributions of this paper are as follows:(1)Apply the golden section search algorithm and random search algorithm for the shortcomings of traditional algorithms(2)Using local mean decomposition algorithm to estimate Hurst exponent(3)Hurst exponent estimation system built on GUI platform ofMATLAB.