本文選題：長(zhǎng)相關(guān) + 網(wǎng)絡(luò)流量��； 參考：《華東師范大學(xué)》2017年碩士論文

【摘要】：網(wǎng)絡(luò)流量一直是網(wǎng)絡(luò)研究領(lǐng)域的重點(diǎn)之一,網(wǎng)絡(luò)流量的研究對(duì)于了解網(wǎng)絡(luò)的行為,提高網(wǎng)絡(luò)的性能,以及保障網(wǎng)絡(luò)的安全具有重要意義。網(wǎng)絡(luò)流量具有自相似性,是典型的長(zhǎng)相關(guān)信號(hào),許多模型已經(jīng)被應(yīng)用于網(wǎng)絡(luò)流量的研究,而且這些模型都有共同的核心參數(shù),即赫斯特指數(shù)。赫斯特指數(shù)不僅對(duì)于網(wǎng)絡(luò)流量建模具有十分重要的意義,而且對(duì)于研究網(wǎng)絡(luò)流量的特性也具有很重要的參考價(jià)值。專家學(xué)者們已經(jīng)提出了許多赫斯特指數(shù)的估計(jì)方法,但有些方法在計(jì)算效率方面存在一些局限,嚴(yán)重影響某些領(lǐng)域和場(chǎng)合下對(duì)于赫斯特指數(shù)計(jì)算的高時(shí)效性的需求。因此,具有較高計(jì)算效率和準(zhǔn)確性的赫斯特指數(shù)估計(jì)算法對(duì)于網(wǎng)絡(luò)流量的研究具有重要意義。本文第一章介紹了網(wǎng)絡(luò)流量的赫斯特指數(shù)估計(jì)算法的研究意義以及國(guó)內(nèi)外的研究現(xiàn)狀;第二章介紹了傳統(tǒng)的赫斯特指數(shù)估計(jì)方法并分析了其中一些方法在計(jì)算效率上存在的不足;第三章和第四章針提出了黃金分割搜索算法和隨機(jī)搜索算法對(duì)傳統(tǒng)算法進(jìn)行改進(jìn);在第五章使用實(shí)際網(wǎng)絡(luò)流量應(yīng)用本文涉及到的算法進(jìn)行實(shí)驗(yàn)并比較這些算法在計(jì)算效率上的差異;第六章在MATLAB的GUI平臺(tái)上設(shè)計(jì)了 一款網(wǎng)絡(luò)流量赫斯特指數(shù)估計(jì)軟件,為網(wǎng)絡(luò)流量赫斯特指數(shù)的計(jì)算提供了一款方便快捷的科學(xué)計(jì)算工具。本文的主要貢獻(xiàn)有:(1)針對(duì)傳統(tǒng)方法的不足提出黃金分割搜索算法和隨機(jī)搜索算法進(jìn)行改進(jìn);(2)基于局部均值分解算法進(jìn)行赫斯特指數(shù)估計(jì);(3)在MATLAB的GUI平臺(tái)上設(shè)計(jì)了一款網(wǎng)絡(luò)流量赫斯特指數(shù)估計(jì)系統(tǒng)。
[Abstract]:Network traffic has always been one of the key points in the field of network research. The study of network traffic is of great significance to understand the behavior of the network, improve the performance of the network, and ensure the security of the network. Network traffic is self-similar, and it is a typical long correlation signal. Many models have been applied to the research of network traffic, and these models have a common core parameter, namely, Hurst index. Hurst exponent is not only of great significance for network traffic modeling, but also of great reference value for studying the characteristics of network traffic. Experts and scholars have put forward many estimation methods of Hurst exponent, but some methods have some limitations in computing efficiency, which seriously affect the demand for high time-efficiency of Hurst exponent calculation in some fields and situations. Therefore, the Hurst exponent estimation algorithm with high computational efficiency and accuracy is of great significance to the research of network traffic. The first chapter of this paper introduces the research significance of the Hurst exponent estimation algorithm of network traffic and the research status at home and abroad. The second chapter introduces the traditional Hurst index estimation method and analyzes the shortcomings of some of the methods in computing efficiency. Chapter 3 and chapter 4 propose golden section search algorithm and random search algorithm to improve the traditional algorithm. In the fifth chapter, we use the actual network traffic to use the algorithms mentioned in this paper to experiment and compare the computational efficiency of these algorithms. Chapter 6 designs a software for estimating the Hurst exponent of network traffic on the GUI platform of MATLAB. It provides a convenient and quick scientific calculation tool for calculating the Hurst index of network traffic. The main contributions of this paper are as follows: (1) the golden section search algorithm and random search algorithm are improved in view of the shortcomings of traditional methods; (2) the Hurst exponent estimation based on local mean decomposition algorithm; (3) designed on the GUI platform of MATLAB. A network traffic Hurst index estimation system.
【學(xué)位授予單位】：華東師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP393.06

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