本文選題：流量識別　切入點：內(nèi)容提取　出處：《電子科技大學》2014年碩士論文　論文類型：學位論文

【摘要】：多媒體業(yè)務和P2P業(yè)務等的蓬勃發(fā)展,使得在網(wǎng)絡上傳輸?shù)臉I(yè)務數(shù)據(jù)越來越多元化,不同的業(yè)務由于服務的類型和對象不同,所以對網(wǎng)絡的要求也有明顯差異,比如對傳輸時延的要求,對丟包率的要求以及各種各樣的QoS需求,為了更好地控制網(wǎng)絡流量,提高網(wǎng)絡利用率,以及更好地為不同的業(yè)務按需服務,首先要解決的問題就是網(wǎng)絡流量識別。網(wǎng)絡流量識別技術是進行網(wǎng)絡報文分類的基礎,本文的主要研究工作就是實現(xiàn)對網(wǎng)絡流量的識別和對網(wǎng)絡關鍵內(nèi)容的提取。本文首先通過閱讀網(wǎng)絡流量識別和關鍵內(nèi)容提取相關領域的國內(nèi)外文獻,根據(jù)自身課題的具體要求,對網(wǎng)絡流量識別和關鍵內(nèi)容提取中的關鍵技術和算法進行了較為深入的研究,研究的重點主要有TCP/IP體系結構,報文分類算法和模式匹配算法,同時,在研究相關理論的基礎上實現(xiàn)了一個用于網(wǎng)絡流量識別和關鍵內(nèi)容提取的Demo系統(tǒng)。由于實驗條件的限制,雖然本文中實現(xiàn)的Demo系統(tǒng)可以完成對網(wǎng)絡流量的識別和關鍵內(nèi)容的提取,并且有直觀的展示。但是,很難客觀地評價其性能指標,所以,在本文中,還基于OPNET平臺,對所實現(xiàn)的網(wǎng)絡流量識別和關鍵內(nèi)容提取算法進行了仿真和測試�？傮w來說,本文具有如下一些特點:1.較為全面的分析和研究了報文分類算法和模式匹配算法,這兩類算法是網(wǎng)絡流量識別和關鍵內(nèi)容提取的技術基礎。2.在研究相關算法的基礎上,使用C++語言編程實現(xiàn)了一個網(wǎng)絡流量識別和關鍵內(nèi)容提取系統(tǒng)。3.在實現(xiàn)相關系統(tǒng)的基礎上,又基于OPNET網(wǎng)絡仿真平臺對系統(tǒng)所采用的算法的性能做了測試和分析。4.本文所實現(xiàn)的網(wǎng)絡流量識別與關鍵內(nèi)容提取技術不僅可用于實際的網(wǎng)絡環(huán)境中,作為軟件系統(tǒng)使用,還可以單獨將算法抽取出來,進行功能擴充和性能分析。
[Abstract]:With the rapid development of multimedia services and P2P services, the service data transmitted over the network is becoming more and more diversified. Because of the different types and objects of services, the requirements of the network are also obviously different. For example, the requirements of transmission delay, packet loss rate and various QoS requirements, in order to better control network traffic, improve network utilization, and better serve on demand for different services. The first problem to be solved is network traffic identification, which is the basis of packet classification. The main research work of this paper is to realize the identification of network traffic and the extraction of network key content. The key technologies and algorithms of network traffic identification and key content extraction are deeply studied. The research focuses on TCP/IP architecture, packet classification algorithm and pattern matching algorithm. Based on the research of related theories, a Demo system for network traffic identification and key content extraction is implemented. Although the Demo system realized in this paper can realize the identification of network traffic and the extraction of key contents, and has a visual display. However, it is difficult to evaluate its performance index objectively, so in this paper, it is also based on OPNET platform. The network traffic recognition and key content extraction algorithms are simulated and tested. In general, this paper has some characteristics as follows: 1.The packet classification algorithm and the pattern matching algorithm are analyzed and studied comprehensively. These two algorithms are the technical foundation of network traffic identification and key content extraction. Based on the research of related algorithms, a network traffic identification and key content extraction system is implemented by C language programming. The performance of the algorithm used in the system is tested and analyzed based on the OPNET network simulation platform. 4. The network traffic identification and key content extraction technology realized in this paper can be used not only in the actual network environment, but also as a software system. The algorithm can also be extracted separately for function expansion and performance analysis.
【學位授予單位】：電子科技大學
【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：1640531