基于實測復雜網(wǎng)絡模型的彈性研究
發(fā)布時間：2018-09-07 19:54
【摘要】：盡管網(wǎng)絡的發(fā)展迅速,每天都會有成千上萬的網(wǎng)絡服務器開啟或者是關閉,網(wǎng)絡在運行中還經(jīng)常受到干擾或破壞,從而導致網(wǎng)絡本身性能降低甚至是功能癱瘓。人們對于網(wǎng)絡的依賴程度日益劇增,但網(wǎng)絡事故對人們產(chǎn)生的打擊亦是隨著依賴的增加而增加。從北美大停電到20世紀爆發(fā)的金融危機,無不透漏著我們對網(wǎng)絡的依賴和網(wǎng)絡癱瘓對我們照成的巨大損失。對于互聯(lián)網(wǎng)絡而言,彈性結(jié)構是當下評價網(wǎng)絡體統(tǒng)的新想法。在之前很多研究中,很少有學者對實測復雜網(wǎng)絡的彈性進行深入的研究,對復雜網(wǎng)絡的研究也僅僅局限于網(wǎng)絡自身恢復能力的理論驗證,但這些問題對于實測復雜網(wǎng)絡如何抵御攻擊并減少故障有著重要意義,因此本文研究重點在于對復雜網(wǎng)絡結(jié)構模型及互聯(lián)網(wǎng)彈性進行深入探討。本文主要做了以下三個方面的工作:1.對復雜網(wǎng)絡的理論分析,首先通過對復雜網(wǎng)絡模型進行深入研究,分別對規(guī)則網(wǎng)絡、隨機網(wǎng)絡、小世界和無標度網(wǎng)絡進行構建并分析其特有性質(zhì)。隨后對網(wǎng)絡統(tǒng)計特性指標度分布、平均路徑長度和網(wǎng)絡聚類系數(shù)進行詳細介紹,并通過實驗模擬對不同網(wǎng)絡屬性進行分析。2.詳細介紹了網(wǎng)絡實際測量方法和測量指標,對現(xiàn)有國內(nèi)外的資料進行分析,選取性價比最高的測量方法對互聯(lián)網(wǎng)進行測量并為特性分析提供數(shù)據(jù)。通過引入網(wǎng)絡彈性定義,對測量數(shù)據(jù)進行實驗。實驗結(jié)果表明:ER隨機網(wǎng)絡對于惡意攻擊彈性要好于其他網(wǎng)絡;BA無標度網(wǎng)絡彈性恢復較好;規(guī)則網(wǎng)絡恢復彈性表現(xiàn)最差;WS小世界則特性并不明顯,其彈性介于ER隨機網(wǎng)絡和規(guī)則網(wǎng)絡之間。而在互聯(lián)網(wǎng)絡中,彈性恢復主要受恢復措施影響較大,彈性連接并不能夠使網(wǎng)絡完全恢復。3.考慮網(wǎng)絡靜態(tài)特性,從差異性角度分析網(wǎng)絡結(jié)構,并引入“熵”指標對規(guī)則網(wǎng)絡、隨機網(wǎng)絡、無標度網(wǎng)絡和小世界進行理論分析和仿真實驗。通過實驗數(shù)據(jù)得出熵在復雜網(wǎng)絡中更能反映出其結(jié)構特征。
[Abstract]:Despite the rapid development of the network, thousands of network servers are opened or shut down every day, and the network is often disturbed or destroyed in operation, which results in the performance of the network itself being degraded or even paralyzed. The degree of people's dependence on network is increasing rapidly, but the attack of network accident is also increasing with the increase of dependence. From the power outages in North America to the financial crisis that broke out in the 20th century, all of us have been exposed to the enormous losses caused by our dependence on the network and the collapse of the network. For the Internet, flexible structure is a new idea to evaluate the network system. In many previous studies, few scholars have carried out in-depth research on the elasticity of measured complex networks, and the research on complex networks is limited to the theoretical verification of the resilience of the networks themselves. However, these problems are of great significance to how to resist attacks and reduce faults in real complex networks. Therefore, the focus of this paper is to discuss the complex network structure model and Internet elasticity in depth. This paper mainly does the following three aspects of work: 1. Based on the theoretical analysis of complex networks, this paper studies the model of complex networks, constructs regular networks, random networks, small world networks and scale-free networks, and analyzes their special properties. Then, the distribution of network statistical characteristics, average path length and network clustering coefficient are introduced in detail, and the different network attributes are analyzed by experimental simulation. This paper introduces the network actual measurement method and measurement index in detail, analyzes the existing data at home and abroad, selects the best measurement method to measure the Internet and provides the data for the characteristic analysis. By introducing the definition of network elasticity, the measurement data are tested. The experimental results show that the resilience of the 10: ER random network to malicious attack is better than that of the other networks, and the resilience of the rule network is the worst, but the performance of the rule network is not obvious in the small world of WS. Its elasticity is between ER random network and regular network. In the Internet, the elastic recovery is mainly affected by the restoration measures, and the elastic connection can not make the network recover completely. 3. Considering the static characteristics of the network, the network structure is analyzed from the point of view of difference, and the "entropy" index is introduced to carry out theoretical analysis and simulation experiments on regular network, random network, scale-free network and small world. The experimental data show that entropy can better reflect the structural characteristics of complex networks.
【學位授予單位】：沈陽理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：O157.5
本文編號：2229260
[Abstract]:Despite the rapid development of the network, thousands of network servers are opened or shut down every day, and the network is often disturbed or destroyed in operation, which results in the performance of the network itself being degraded or even paralyzed. The degree of people's dependence on network is increasing rapidly, but the attack of network accident is also increasing with the increase of dependence. From the power outages in North America to the financial crisis that broke out in the 20th century, all of us have been exposed to the enormous losses caused by our dependence on the network and the collapse of the network. For the Internet, flexible structure is a new idea to evaluate the network system. In many previous studies, few scholars have carried out in-depth research on the elasticity of measured complex networks, and the research on complex networks is limited to the theoretical verification of the resilience of the networks themselves. However, these problems are of great significance to how to resist attacks and reduce faults in real complex networks. Therefore, the focus of this paper is to discuss the complex network structure model and Internet elasticity in depth. This paper mainly does the following three aspects of work: 1. Based on the theoretical analysis of complex networks, this paper studies the model of complex networks, constructs regular networks, random networks, small world networks and scale-free networks, and analyzes their special properties. Then, the distribution of network statistical characteristics, average path length and network clustering coefficient are introduced in detail, and the different network attributes are analyzed by experimental simulation. This paper introduces the network actual measurement method and measurement index in detail, analyzes the existing data at home and abroad, selects the best measurement method to measure the Internet and provides the data for the characteristic analysis. By introducing the definition of network elasticity, the measurement data are tested. The experimental results show that the resilience of the 10: ER random network to malicious attack is better than that of the other networks, and the resilience of the rule network is the worst, but the performance of the rule network is not obvious in the small world of WS. Its elasticity is between ER random network and regular network. In the Internet, the elastic recovery is mainly affected by the restoration measures, and the elastic connection can not make the network recover completely. 3. Considering the static characteristics of the network, the network structure is analyzed from the point of view of difference, and the "entropy" index is introduced to carry out theoretical analysis and simulation experiments on regular network, random network, scale-free network and small world. The experimental data show that entropy can better reflect the structural characteristics of complex networks.
【學位授予單位】：沈陽理工大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：O157.5
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