流量矩陣分析的新方法研究
發(fā)布時間：2018-11-18 21:48
【摘要】：互聯(lián)網(wǎng)技術作為21世紀發(fā)展最快的技術之一,已經(jīng)廣泛的應用于我們的生產(chǎn)生活當中,并且對社會的進步、經(jīng)濟的發(fā)展做出了巨大的貢獻。然而,隨著互聯(lián)網(wǎng)技術進一步成熟,近年來也涌現(xiàn)出了大量的新型網(wǎng)絡應用和服務,它們給人們帶來方便娛樂的同時,也給網(wǎng)絡運營商的管理維護帶來了巨大的壓力。與此同時,數(shù)量眾多的異構網(wǎng)絡的接入,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)絡則顯得尤為必要。 網(wǎng)絡流量工程中的一個重要的參數(shù)就是流量矩陣,它對流量工程的重要性使得它廣受研究人員的關注,并成為Internet的一個重要研究方向。流量矩陣的研究分為兩個方面,流量矩陣的估計和流量矩陣的分析。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,并以此實現(xiàn)對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方面： 1)算子的選擇。經(jīng)過實驗分析,不同的擴散小波算子將對小波系數(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。所以本文的第一個工作將是設計實驗,并分析對比兩個常用的擴散小波算子,RandomWalk算子和I-L算子,然后選一個作為本文異常檢測實驗的擴散小波算子。文中設計了3個方向的對比實驗來凸顯兩個算子各自的優(yōu)劣。 2)異常檢測。在完成擴散小波算子的對比實驗后,本文將展開流量矩陣的異常檢測實驗。在異常檢測實驗中,本文將從異常檢測算法設計和異常實驗數(shù)據(jù)選擇兩方面展開,并給出最終的異常檢測結果。 3)異常定位。在文章的最后,本文通過實驗及統(tǒng)計,分析了擴散小波系數(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)點的位置。作為對這個規(guī)律的應用,本文設計實驗完成了流量矩陣的斷路檢測。 基于擴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算量,還能使分析變得更加準確有效。擴散小波算子的應用,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)系對于網(wǎng)路工程中的應用都具備極大的研究價值。
[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.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.06
本文編號：2341360
[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.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.06
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，本文編號：2341360
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