本文選題：流量識別 + 路由控制　； 參考：《北京郵電大學(xué)》2014年碩士論文

【摘要】：隨著Internet的高速發(fā)展,互聯(lián)網(wǎng)業(yè)務(wù)從以單純的數(shù)據(jù)業(yè)務(wù)為主逐步發(fā)展為語音、視頻、數(shù)據(jù)等業(yè)務(wù),涵蓋了搜索、即時通信、網(wǎng)購、金融、游戲等領(lǐng)域�；ヂ�(lián)網(wǎng)極大地方便和豐富了人們的生活、學(xué)習(xí)、工作,同時也為網(wǎng)絡(luò)運營商帶來了極大的挑戰(zhàn)。當(dāng)前互聯(lián)網(wǎng)在業(yè)務(wù)的QoS支持上,需要解決兩個關(guān)鍵技術(shù)是：(1)如何識別不同的業(yè)務(wù)類型；(2)如何針對不同的業(yè)務(wù)類型,進行不同的控制。這兩個關(guān)鍵技術(shù)可歸納為流量識別和流量的路由控制。 本文圍繞著流量識別和流量的路由控制這兩個關(guān)鍵技術(shù),進行深入的研究。本文在研究過程中主要做了如下工作：(1)研究和比較當(dāng)前常用的流量識別技術(shù),包括基于端口的流量識別技術(shù)、基于深度包檢測的流量識別技術(shù)、基于行為模式的流量識別技術(shù)和基于機器學(xué)習(xí)的流量識別技術(shù),其中對性能最優(yōu)的基于有監(jiān)督機器學(xué)習(xí)的流量識別技術(shù)進行了更進一步的研究和分析；(2)基于SVM算法和Adaboost算法提出了一個實時流量識別算法；(3)基于TCP/IP協(xié)議棧,設(shè)計數(shù)據(jù)平面和控制平面相分離的路由架構(gòu)；(4)結(jié)合本文提出的實時流量識別算法和路由架構(gòu),實現(xiàn)具有流量識別功能的路由控制系統(tǒng),并完成系統(tǒng)的測試。 本文在提出基于SVM和Adaboost的實時流量識別算法時,進行了實驗對比。實驗結(jié)果表明,這種方法在實時流量識別方面的準(zhǔn)確率比原始的SVM算法和基于決策樹的Adaboost算法都高,具有可行性。結(jié)合這個實時流量識別算法和所設(shè)計的路由架構(gòu),本文實現(xiàn)了路由控制系統(tǒng),并搭建了測試環(huán)境完成了場景測試,證明了系統(tǒng)的可行性。
[Abstract]:With the rapid development of Internet, Internet business has gradually developed from simple data services to voice, video, data and other services, covering search, instant messaging, online shopping, finance, games and other fields. The Internet greatly facilitates and enriches people's life, study and work, but also brings great challenges to network operators. In the current QoS support of Internet services, two key technologies need to be solved: 1) how to identify different types of services / 2) how to control different types of services. These two key technologies can be summarized as flow identification and traffic routing control. This paper focuses on the two key technologies of traffic identification and traffic routing control. In this paper, we mainly do the following work: 1) Research and compare the current commonly used traffic identification technology, including port based traffic identification technology, depth packet detection based traffic identification technology, Behavioral pattern based traffic identification technology and machine learning based traffic identification technology are further studied and analyzed, in which the best performance based on supervised machine learning traffic identification technology is further studied and analyzed. (2) based on SVM algorithm and Adaboost algorithm, a real-time traffic identification algorithm is proposed. Based on TCP / IP protocol stack, a routing architecture with data plane and control plane is designed. The routing control system with the function of flow identification is implemented, and the test of the system is completed. In this paper, a real-time traffic recognition algorithm based on SVM and Adaboost is proposed. Experimental results show that the accuracy of this method in real-time traffic recognition is higher than the original SVM algorithm and Adaboost algorithm based on decision tree. Combined with the real-time traffic identification algorithm and the designed routing architecture, this paper implements the routing control system, and builds a test environment to complete the scene test, which proves the feasibility of the system.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.06;TP181

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