本文選題：SDN + QoS　； 參考：《北京交通大學(xué)》2017年碩士論文

【摘要】：傳統(tǒng)的QoS機(jī)制是為因特網(wǎng)而設(shè)計(jì),建立在因特網(wǎng)完全分布式的、逐跳路由式的體系結(jié)構(gòu)之上,缺乏整體網(wǎng)絡(luò)資源分布的統(tǒng)一的全局視圖,因而難以推廣應(yīng)用。SDN(Software Defined Network)具有集中控制的特點(diǎn),通過集中控控制器能夠輕松下發(fā)QoS策略,實(shí)現(xiàn)對所有網(wǎng)絡(luò)設(shè)備以及全網(wǎng)流量的集中管理控制,既可以完成靈活的QoS服務(wù)策略選擇,又能保證QoS策略的一致性。因而,在SDN下的QoS機(jī)制一經(jīng)提出,就得到學(xué)術(shù)界和工業(yè)界的關(guān)注,成為研究熱點(diǎn)。隨著云計(jì)算、移動(dòng)互聯(lián)網(wǎng)、Web2.0等新興業(yè)務(wù)的蓬勃發(fā)展,保證數(shù)據(jù)中心網(wǎng)絡(luò)及其應(yīng)用的服務(wù)質(zhì)量早已成為業(yè)界共識。在數(shù)據(jù)中心網(wǎng)絡(luò)中,許多著名的應(yīng)用形式,例如Web搜索、廣告、推薦系統(tǒng)等均具有類似的業(yè)務(wù)流特征,即是大流和小流混合的業(yè)務(wù)流。小流對時(shí)延敏感,但帶寬要求不高;大流帶寬要求高,但對時(shí)延不敏感。小流經(jīng)歷的時(shí)延直接影響到這些應(yīng)用中返回結(jié)果的質(zhì)量和最終的經(jīng)濟(jì)收益,因此如何保護(hù)小流的時(shí)延一直是研究熱點(diǎn)。本論文第一部分工作提出了一種在SDN下保證小流時(shí)延的QoS機(jī)制。針對目前的網(wǎng)絡(luò)節(jié)點(diǎn)輸出端口的處理能力具有非搶占性的特點(diǎn),即在一個(gè)時(shí)刻只能處理一個(gè)分組,且不能被搶占,該機(jī)制將分級隊(duì)列管理和動(dòng)態(tài)路由機(jī)制相結(jié)合,在輸出端口沒有被大流分組占用時(shí),采用分級隊(duì)列管理,保證小流分組優(yōu)先服務(wù);在輸出端口被大流分組占用時(shí),采用偏轉(zhuǎn)路由方案,根據(jù)其他輸出端口的占用情況,選擇最優(yōu)路由,保證小流分組優(yōu)先傳輸。仿真實(shí)驗(yàn)表明采用該機(jī)制可以明顯降低小流的傳輸時(shí)延。視頻流媒體已成為目前因特網(wǎng)的主要應(yīng)用,為了給視頻用戶提供更好的網(wǎng)絡(luò)服務(wù),了解并保證視頻流的服務(wù)質(zhì)量和用戶體驗(yàn)成為網(wǎng)絡(luò)提供商的重要任務(wù)。由于播放視頻時(shí)發(fā)生卡頓會直接影響到用戶的觀看體驗(yàn),從而影響用戶觀看視頻的次數(shù)和時(shí)長,卡頓事件往往被用來作為衡量用戶體驗(yàn)的主要指標(biāo)。鑒于基于HTTP的動(dòng)態(tài)自適應(yīng)流媒體,即是當(dāng)前視頻流媒體的主要傳輸技術(shù),本論文第二部分工作提出一種根據(jù)DASH視頻流的QoS參數(shù)來預(yù)測視頻卡頓的方法。該方法利用視頻客戶和服務(wù)器之間兩個(gè)方向上的流量數(shù)據(jù),使用機(jī)器學(xué)習(xí)技術(shù),建立分類模型,預(yù)測視頻播放時(shí)是否發(fā)生卡頓。原型實(shí)驗(yàn)結(jié)果顯示,采用我們的方法預(yù)測實(shí)時(shí)卡頓事件的準(zhǔn)確率高達(dá)98%,漏檢率僅為3%。
[Abstract]:The traditional QoS mechanism is designed for the Internet, which is based on the distributed and hop-by-hop routing architecture of the Internet, and lacks a unified global view of the overall network resource distribution. Therefore, it is difficult to popularize the application of .SDNN Software Defined Network, which has the characteristics of centralized control. Through the centralized controller, the QoS policy can be easily sent out, and the centralized management control of all network devices and the whole network traffic can be realized. It can not only complete the flexible QoS service policy selection, but also guarantee the consistency of QoS policy. Therefore, once the QoS mechanism under SDN is put forward, it has attracted the attention of academia and industry, and has become a research hotspot. With the development of cloud computing, mobile Internet, Web 2.0 and other new businesses, it has become a consensus in the industry to ensure the quality of service of data center network and its applications. In data center networks, many well-known applications, such as Web search, advertising and recommendation systems, have similar traffic characteristics, that is, large and small streams of traffic. The small stream is sensitive to delay, but the bandwidth is not high, while the large stream is not sensitive to delay. The delay experienced by the stream directly affects the quality of the returned results and the final economic benefits in these applications. Therefore, how to protect the delay of the stream is always a hot topic. In the first part of this thesis, we propose a QoS mechanism to guarantee the stream delay in SDN. In view of the non-preemptive ability of the current network node output port, that is, only one packet can be processed at a time and can not be preempted, the mechanism combines hierarchical queue management with dynamic routing mechanism. When the output port is not occupied by the large stream packet, the hierarchical queue management is adopted to ensure the priority service of the small stream packet, and when the output port is occupied by the large stream packet, the deflection routing scheme is adopted, according to the occupation of other output ports, The best route is chosen to ensure the priority transmission of the small stream packet. Simulation results show that the proposed mechanism can significantly reduce the transmission delay of the stream. Video streaming media has become the main application of the Internet at present. In order to provide better network services for video users, understanding and guaranteeing the quality of service and user experience of video streams has become an important task for network providers. Because the occurrence of Catton when playing video will directly affect the user's viewing experience and thus affect the number and duration of the user watching the video, the Catton event is often used as the main index to measure the user experience. In view of the fact that dynamic adaptive streaming media based on HTTP is the main transmission technology of video streaming at present, the second part of this paper proposes a method to predict video Carton based on the QoS parameters of DASH video stream. This method uses the traffic data in two directions between the video client and the server, uses the machine learning technology, establishes the classification model, and predicts whether the video playback will happen or not. The prototype experiment results show that the accuracy of our method for predicting real time Catton events is as high as 98%, and the missed detection rate is only 3%.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP393.0

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本文編號：1878167