本文選題：網絡斷層掃描　切入點：深度優(yōu)先搜索　出處：《蘭州交通大學》2014年碩士論文

【摘要】：現如今網絡規(guī)模和網絡復雜性日益增長，在互聯網的研究中，準確和及時的識別路由器級互聯網的拓撲結構是目前研究的熱點和難點。運用網絡斷層掃描技術來推斷網絡拓撲結構，是一種極具吸引力的方法。 網絡斷層掃描(Network Tomography,NT)是一種采用全新思想的網絡測量技術,它是基于醫(yī)學透視的概念提出來的。該技術是一種基于端到端的測量方法，通過反演推斷獲取網絡的內部特性，并運用統(tǒng)計和推斷的原理進行拓撲結構的推測。網絡斷層掃描技術不需要網絡內部的節(jié)點的合作，只需要選擇一組接收節(jié)點即可完成對網絡內部特性的推斷，解決了網絡內部節(jié)點不協作的問題。然而，目前斷層掃描技術有一定的限制性，不能及時推斷出大規(guī)模的網絡拓撲結構，因為推斷大規(guī)模網絡拓撲結構需要的測量工程較大，難以實現。本文對基于時延特性的網絡拓撲推斷技術進行研究，描述了一種基于葉節(jié)點深度優(yōu)先搜索(DFS)序列的網絡拓撲推斷算法，首先使用遞歸二分法找出葉節(jié)點DFS序列，然后運用葉節(jié)點FS序列推斷網絡拓撲結構。該算法能夠高效的發(fā)現網絡的邏輯拓撲樹結構。通過大量的仿真實驗表明，該方法所需要的成對探測包的數量低于傳統(tǒng)聚類算法的15%，可以更準確、更快速的推斷出網絡的拓撲結構，進而更大程度的提高了網絡拓撲推斷的效率。論文具體工作如下： 前三章介紹了課題的研究背景、研究現狀以及研究內容，并介紹了本課題研究中用到的網絡測量技術和網絡斷層掃描技術的相關內容，并且對現有的較成熟的網絡拓撲推斷算法進行了概括和總結。 第四章為本文核心內容，主要介紹了基于葉節(jié)點DFS序列的網絡拓撲推斷算法，，并且詳細描述了使用該算法推斷網絡拓撲結構的整個過程。 第五章仿真實驗，使用NS2仿真平臺，對第四章提出的基于葉節(jié)點DFS序列的網絡拓撲推斷算法進行了有效驗證，證明了該算法的高效性和可行性。
[Abstract]:Nowadays, network scale and network complexity are increasing day by day. In the research of Internet, accurate and timely identification of router level Internet topology is a hot and difficult point.It is an attractive method to infer the network topology by using the network tomographic technique.Network Tomography (NT) is a new network measurement technology based on the concept of medical perspective.This technique is an end-to-end measurement method, which obtains the internal characteristics of the network by inversion inference, and uses the principles of statistics and inference to infer the topology of the network.The network tomography technology does not need the cooperation of the nodes in the network, but only needs to select a group of receiving nodes to complete the inference of the internal characteristics of the network, which solves the problem of the nodes in the network not cooperating.However, at present, the technique of tomographic scanning is too restrictive to infer the large-scale network topology in time, because it is difficult to realize the large scale network topology because the measurement engineering is needed to infer the large-scale network topology structure.In this paper, the network topology inference technology based on delay characteristic is studied, and a network topology inference algorithm based on the leaf node depth first search sequence is described. Firstly, the DFS sequence of the leaf node is found by recursive dichotomy.Then the topological structure of the network is inferred by using the leaf node FS sequence.The algorithm can efficiently discover the logical topology tree of the network.A large number of simulation experiments show that the number of pairwise detection packets in this method is lower than that of the traditional clustering algorithm, and the topology of the network can be inferred more accurately and quickly.Furthermore, the efficiency of network topology inference is improved to a greater extent.The specific work of the thesis is as follows:The first three chapters introduce the research background, research status and research content, and introduce the network measurement technology and network tomography technology used in this research.The existing network topology inference algorithms are summarized and summarized.The fourth chapter is the core of this paper, mainly introduces the network topology inference algorithm based on the leaf node DFS sequence, and describes the whole process of using the algorithm to infer the network topology structure in detail.In the fifth chapter, using the NS2 simulation platform, the network topology inference algorithm based on the leaf node DFS sequence is validated, and the efficiency and feasibility of the algorithm are proved.
【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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