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基于丟包率的多播網(wǎng)絡拓撲推斷研究

發(fā)布時間:2018-10-08 19:31
【摘要】:現(xiàn)如今,計算機網(wǎng)絡已經(jīng)逐漸成為我們信息社會的支柱,因而網(wǎng)絡中存在的問題也日益顯現(xiàn)出來。尤其是在網(wǎng)絡安全領域中,對大型網(wǎng)絡的檢測和保護。由于網(wǎng)絡出現(xiàn)不良狀況的因素多樣,為了檢測不良狀況產(chǎn)生的原因,網(wǎng)絡管理員必須探測網(wǎng)絡中的元素即網(wǎng)絡設備來收集相關數(shù)據(jù)。但是網(wǎng)絡規(guī)模日益擴大,網(wǎng)絡管理員已無法直接獲取網(wǎng)絡中的元素,且傳統(tǒng)的拓撲推測方法已無法滿足管理員獲取網(wǎng)絡元素的需要,因此使用新興的技術——網(wǎng)絡斷層掃描(Network Tomography, NT)技術進行網(wǎng)絡拓撲推測。該技術在不需要內(nèi)部網(wǎng)絡設備協(xié)作的情況下,僅依靠在邊緣設備測量得到的性能屬性,利用兄弟節(jié)點的相關性原理來判斷已知網(wǎng)絡設備間的關系,然后推斷網(wǎng)絡內(nèi)部的連接情況。利用該方法可以彌補傳統(tǒng)網(wǎng)絡拓撲識別方法的不足,因此論文主要研究網(wǎng)絡斷層掃描技術在網(wǎng)絡拓撲推測方向的應用。 首先介紹了NT技術的研究背景、意義以及NT技術的原理、測量方法和推斷模型。 其次介紹了網(wǎng)絡拓撲結(jié)構推斷的方法,該部分內(nèi)容屬于文章的重點內(nèi)容,分析了傳統(tǒng)網(wǎng)絡推測方法的應用局限性以及基于NT技術的網(wǎng)絡拓撲推斷方法的優(yōu)勢。論文使用的基于NT技術的推斷方法將網(wǎng)絡丟包率作為推斷的參數(shù),使用多播測量的方法獲取終端節(jié)點的丟包率,利用丟失率作為參數(shù)進行拓撲推測,剖析并比較現(xiàn)有多播網(wǎng)絡拓撲推斷算法的優(yōu)勢及不足之處,在此基礎上,提出一種更優(yōu)的拓撲推斷算法——HTIP算法。該算法根據(jù)節(jié)點的丟包情況去計算兩兩節(jié)點間的海明碼距,利用兄弟節(jié)點間相似性較大的特點對拓撲結(jié)構進行合理的推斷。 隨后介紹了網(wǎng)絡仿真模擬軟件NS2的仿真模擬原理,使用NS2模擬多播網(wǎng)絡發(fā)包,測量獲取節(jié)點性能參數(shù),并對HTIP算法和BFHC算法進行分析比較,結(jié)果顯示HTIP算法具有更優(yōu)的性能。 在文章的最后,講解了信息可視化在基于NT技術的拓撲推斷方向的運用以及目前常用的信息可視化的布局算法,選擇合適的方法對網(wǎng)絡設備及鏈路等進行存儲以及對拓撲推斷過程進行可視化的動態(tài)顯示,使用C#語言對可視化軟件進行編寫,以一種整齊、美觀的方式展現(xiàn)拓撲推斷的過程。
[Abstract]:Nowadays, the computer network has gradually become the pillar of our information society. Especially in the field of network security, the detection and protection of large networks. In order to detect the causes of the bad condition, the network administrator must detect the element in the network, that is, the network equipment, to collect the relevant data. However, with the increasing scale of the network, the network administrator has been unable to directly obtain the elements in the network, and the traditional topology speculation method can no longer meet the needs of the administrator to obtain the network elements. Therefore, network tomographic (Network Tomography, NT) technology is used to speculate the network topology. Under the condition of not requiring the cooperation of internal network devices, the technology only depends on the performance attributes measured in edge devices, and uses the correlation principle of brother nodes to judge the known relationships between network devices. The connection inside the network is then inferred. This method can make up for the shortcomings of the traditional network topology identification method, so this paper mainly studies the application of network tomography technology in network topology estimation. Firstly, the research background, significance, principle, measurement method and inference model of NT technology are introduced. Secondly, the paper introduces the method of network topology inference, which belongs to the main content of this paper. The limitations of traditional network inference methods and the advantages of network topology inference methods based on NT technology are analyzed. The inference method based on NT technology takes the network packet loss rate as the inferential parameter, uses the multicast measurement method to obtain the terminal node packet loss rate, and uses the loss rate as the parameter to carry on the topological inference. This paper analyzes and compares the advantages and disadvantages of the existing multicast network topology inference algorithms. On this basis, a better topology inference algorithm, HTIP algorithm, is proposed. The algorithm calculates the distance between two nodes according to the loss of packets, and deduces the topological structure reasonably by using the characteristics of the similarity between the two nodes. Then the paper introduces the simulation principle of network simulation software NS2, uses NS2 to simulate multicast network delivery, measures and acquires node performance parameters, and analyzes and compares the HTIP algorithm and BFHC algorithm. The results show that HTIP algorithm has better performance. At the end of the paper, the application of information visualization in topology inference based on NT technology and the layout algorithm of information visualization are explained. Choosing the appropriate method to store network equipment and link and visualize the process of topological inference, we use C # language to write the visualization software, and show the process of topological inference in a neat and beautiful way.
【學位授予單位】:蘭州交通大學
【學位級別】:碩士
【學位授予年份】:2014
【分類號】:TP393.02

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