隨著復(fù)雜網(wǎng)絡(luò)研究的興起,復(fù)雜網(wǎng)絡(luò)的安全問題變得越來越重要。特別是隨著互聯(lián)網(wǎng)的廣泛應(yīng)用,如何提供一個安全可靠的網(wǎng)絡(luò)是國家和社會共同關(guān)心的問題。研究發(fā)現(xiàn),無標(biāo)度網(wǎng)絡(luò)的尺度分布具有冪律性質(zhì),網(wǎng)絡(luò)具有相似的性質(zhì)�！棒敯粜院痛嗳跣浴笔菑�(fù)雜網(wǎng)絡(luò)的一個重要特征,它是由網(wǎng)絡(luò)度值分布不均所引起的。從網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)看,這是研究網(wǎng)絡(luò)特性的關(guān)鍵。如何提高網(wǎng)絡(luò)的靈活性和健壯性,減少故障造成的損失也是本文的重點(diǎn)。本文的主要工作如下:1、研究了具有大規(guī)模拓?fù)浣Y(jié)構(gòu)的復(fù)雜網(wǎng)絡(luò)建模方法,并給出了一個網(wǎng)絡(luò)拓?fù)浣?shí)例。首先,如frequency-degree冪律的數(shù)學(xué)工具,秩冪律,和CCDF冪律(D)進(jìn)行了描述網(wǎng)絡(luò)的冪律特性。然后,改進(jìn)BA模型等模型,利用遺傳算法建立網(wǎng)絡(luò)拓?fù)淠Ｐ汀Ｗ詈蠼o出了該算法。用matlab仿真分析了BA無標(biāo)度網(wǎng)絡(luò)和互聯(lián)網(wǎng)拓?fù)涞膬缏商匦浴?、無標(biāo)度BA網(wǎng)絡(luò)與Internet網(wǎng)絡(luò)在碰撞攻擊中的魯棒性分析與比較。實(shí)驗(yàn)表明,BA網(wǎng)絡(luò)和互聯(lián)網(wǎng)對隨機(jī)攻擊具有較強(qiáng)的魯棒性,易受攻擊。此外,規(guī)模較小的網(wǎng)絡(luò)和因特網(wǎng)更容易受到高負(fù)載的影響,而在高冗余的情況下,減少規(guī)模網(wǎng)絡(luò)和提高因特網(wǎng)的健壯性。在隨機(jī)攻擊和確定攻擊過程BA...

【文章頁數(shù)】：75 頁

【學(xué)位級別】：碩士

【文章目錄】：
摘要
abstract
Chapter 1 Introduction
    1.1 Motivation
    1.2 Objectives of this thesis
    1.3 Expectation
    1.4 Limitations
    1.5 Structure
Chapter 2 Research background of complex networks
    2.1 Backgrounds of complex networks
    2.2 Research status and significance of complex networks
        2.2.1 Research status of robustness and cascading failures in complex networks
        2.2.2 Research status of Internet
Chapter 3 Complex network topology model and feature analysis
    3.1 Statistical properties of complex networks
        3.1.1 Average path length
        3.1.2 Clustering coefficient
        3.1.3 Node degree and its distribution characteristics
    3.2 Basic model of complex network topology
        3.2.1 Rule network
            1.Global coupling network
            2.Nearest neighbor coupling network
            3.Star coupled network
        3.2.2 Stochastic network
        3.2.3 Small world network
            1.WS small world model
            2.NW small world model
        3.2.4 Scale free network model
    3.3 Internet network model
        3.3.1 Topological modeling of Internet
        3.3.2 Power law property
        3.3.3 Rich club features
        3.3.4 Kernel number
        3.3.5 Betweenness
    3.4 Summary of this chapter
Chapter 4 Power law analysis
    4.1 Power law distribution form
        4.1.1 Frequency-degree of power law distribution
        4.1.2 Degree-rank power law distribution
        4.1.3 Power law distribution of CCDF(d)-degree
    4.2 Power law analysis of BA networks
        4.2.1 Continuity method for the degree distribution of BA model
        4.2.2 Power law simulation of BA scale-free network
    4.3 Power law analysis of the Internet
    4.4 Summary
Chapter 5 Robustness analysis of Complex networks
    5.1. Identification parameters of robustness
    5.2. Analysis of networks examples
        5.2.1. Attacks on BA scale-free networks
        5.2.2. Attacks on NW small-world networks
        5.2.3. Attacks on router-level Internet
        5.2.4. Comparisons among the complex networks examples
Concluding Remarks
References
Scientific research published during the master degree study
Thank



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