【摘要】：互聯(lián)網(wǎng)技術(shù)作為21世紀(jì)發(fā)展最快的技術(shù)之一,已經(jīng)廣泛的應(yīng)用于我們的生產(chǎn)生活當(dāng)中,并且對(duì)社會(huì)的進(jìn)步、經(jīng)濟(jì)的發(fā)展做出了巨大的貢獻(xiàn)。然而,隨著互聯(lián)網(wǎng)技術(shù)進(jìn)一步成熟,近年來也涌現(xiàn)出了大量的新型網(wǎng)絡(luò)應(yīng)用和服務(wù),它們給人們帶來方便娛樂的同時(shí),也給網(wǎng)絡(luò)運(yùn)營商的管理維護(hù)帶來了巨大的壓力。與此同時(shí),數(shù)量眾多的異構(gòu)網(wǎng)絡(luò)的接入,更加使得互聯(lián)網(wǎng)變得難以掌控。如何有效的監(jiān)控和分析互聯(lián)網(wǎng)絡(luò)則顯得尤為必要。 網(wǎng)絡(luò)流量工程中的一個(gè)重要的參數(shù)就是流量矩陣,它對(duì)流量工程的重要性使得它廣受研究人員的關(guān)注,并成為Internet的一個(gè)重要研究方向。流量矩陣的研究分為兩個(gè)方面,流量矩陣的估計(jì)和流量矩陣的分析。本文將采用近年來新提出的一種分析方法來研究分析流量矩陣,并以此實(shí)現(xiàn)對(duì)流量矩陣異常的檢測分析。本文的研究內(nèi)容主要分為如下三個(gè)方面： 1)算子的選擇。經(jīng)過實(shí)驗(yàn)分析,不同的擴(kuò)散小波算子將對(duì)小波系數(shù)矩陣產(chǎn)生微妙的變化,而這些變化將在一定程度上影響流量矩陣不同情況下的分析。所以本文的第一個(gè)工作將是設(shè)計(jì)實(shí)驗(yàn),并分析對(duì)比兩個(gè)常用的擴(kuò)散小波算子,RandomWalk算子和I-L算子,然后選一個(gè)作為本文異常檢測實(shí)驗(yàn)的擴(kuò)散小波算子。文中設(shè)計(jì)了3個(gè)方向的對(duì)比實(shí)驗(yàn)來凸顯兩個(gè)算子各自的優(yōu)劣。 2)異常檢測。在完成擴(kuò)散小波算子的對(duì)比實(shí)驗(yàn)后,本文將展開流量矩陣的異常檢測實(shí)驗(yàn)。在異常檢測實(shí)驗(yàn)中,本文將從異常檢測算法設(shè)計(jì)和異常實(shí)驗(yàn)數(shù)據(jù)選擇兩方面展開,并給出最終的異常檢測結(jié)果。 3)異常定位。在文章的最后,本文通過實(shí)驗(yàn)及統(tǒng)計(jì),分析了擴(kuò)散小波系數(shù)矩陣與原始流量矩陣之間存在的一些規(guī)律,通過這個(gè)規(guī)律可以由系數(shù)矩陣的異常變化來推測出原始流量矩陣中出現(xiàn)異常的節(jié)點(diǎn)的位置。作為對(duì)這個(gè)規(guī)律的應(yīng)用,本文設(shè)計(jì)實(shí)驗(yàn)完成了流量矩陣的斷路檢測。 基于擴(kuò)散小波的多尺度流量矩陣分析能夠通過合適尺度的小波系數(shù)矩陣來解析原始流量矩陣信息。這樣不但減少了分析的計(jì)算量,還能使分析變得更加準(zhǔn)確有效。擴(kuò)散小波算子的應(yīng)用,使得流量矩陣的重要特征可以用小波系數(shù)矩陣來描述,兩者之間存在的潛在聯(lián)系對(duì)于網(wǎng)路工程中的應(yīng)用都具備極大的研究價(jià)值。
[Abstract]:As one of the fastest developing technologies in the 21st century, Internet technology has been widely used in our production and life, and has made a great contribution to social progress and economic development. However, with the further maturity of Internet technology, a large number of new network applications and services have emerged in recent years, which bring people convenient entertainment, but also bring great pressure to the management and maintenance of network operators. At the same time, a large number of heterogeneous networks access, making the Internet more difficult to control. How to effectively monitor and analyze the Internet is particularly necessary. Traffic matrix is an important parameter in network traffic engineering. Its importance to traffic engineering makes it widely concerned by researchers and becomes an important research direction of Internet. The research of the flow matrix is divided into two aspects: the estimation of the flow matrix and the analysis of the flow matrix. In this paper, a new analysis method proposed in recent years is used to study and analyze the flow matrix and to detect and analyze the anomaly of the flow matrix. The main contents of this paper are as follows: 1) selection of operators. Through experimental analysis, different diffusive wavelet operators will produce subtle changes to the wavelet coefficient matrix, and these changes will influence the analysis of the flow matrix under different conditions to some extent. Therefore, the first work of this paper will be to design experiments and compare two diffusive wavelet operators, RandomWalk operators and I-L operators, and then select one as the diffusive wavelet operator of anomaly detection experiment in this paper. A comparative experiment in three directions is designed to highlight the advantages and disadvantages of the two operators. 2) abnormal detection. After the contrast experiment of diffusive wavelet operator is completed, the anomaly detection experiment of flow matrix will be carried out in this paper. In the experiment of anomaly detection, the algorithm design of anomaly detection and the data selection of anomaly experiment are discussed in this paper, and the final results of anomaly detection are given. 3) abnormal location. At the end of the paper, some laws between the diffusion wavelet coefficient matrix and the original flow matrix are analyzed through experiments and statistics. According to this rule, the abnormal position of the node in the original flow matrix can be deduced from the abnormal change of the coefficient matrix. As an application of this rule, this paper designs experiments to complete the open circuit detection of the flow matrix. Multi-scale traffic matrix analysis based on diffusive wavelet can analyze the information of original flow matrix by wavelet coefficient matrix of appropriate scale. This not only reduces the calculation of the analysis, but also makes the analysis more accurate and effective. With the application of diffusive wavelet operator, the important characteristics of traffic matrix can be described by wavelet coefficient matrix. The potential relationship between them has great value for the application of network engineering.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.06

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