【摘要】：移動互聯(lián)網(wǎng)快速發(fā)展,特別是隨著4G網(wǎng)絡(luò)的普及,越來越多的用戶觀看網(wǎng)絡(luò)視頻。ISP向用戶提供互聯(lián)網(wǎng)接入服務(wù),面對大量的互聯(lián)網(wǎng)視頻用戶,若網(wǎng)絡(luò)出現(xiàn)延遲、抖動或丟包等問題,網(wǎng)絡(luò)視頻容易出現(xiàn)卡頓現(xiàn)象,嚴重降低用戶的觀看體驗質(zhì)量。因此,ISP需要在大量視頻出現(xiàn)卡頓前,及時改善網(wǎng)絡(luò)條件提高用戶觀看體驗質(zhì)量。面對嚴峻的市場競爭,若通過終端反饋或向視頻網(wǎng)站購買相關(guān)信息不僅困難而且成本過高。然而,ISP可以獲取服務(wù)器和客戶端之間的視頻流量數(shù)據(jù),如何通過網(wǎng)絡(luò)流量改善用戶觀看體驗逐漸受到了關(guān)注。本文主要工作是通過視頻流量數(shù)據(jù)對視頻播放過程進行重構(gòu)并且檢測視頻卡頓的次數(shù)和時長,目的是幫助ISP改善用戶觀看體驗質(zhì)量。視頻流量數(shù)據(jù)主要包含在HTTP和TCP數(shù)據(jù)包中。其中,HTTP數(shù)據(jù)包報文主要包含了視頻的基本信息,TCP數(shù)據(jù)包報文主要包含了已編碼的視頻數(shù)據(jù)。然而,基于對用戶隱私的保護,ISP不能解析HTTP數(shù)據(jù)包提取視頻的基本信息,所以我們主要通過TCP數(shù)據(jù)包中的視頻數(shù)據(jù)對視頻播放過程進行重構(gòu),檢測視頻卡頓的卡頓次數(shù)和時長。由于TCP數(shù)據(jù)包的視頻數(shù)據(jù)是無差別的已編碼視頻片段,我們在重構(gòu)視頻播放過程前,需要對視頻基本信息進行估計。其中,視頻清晰度和視頻初始延遲的估計準確性對視頻重構(gòu)的影響最大,我們在文中提出了相關(guān)的估計方法。在獲得視頻基本信息后,我們基于隊列理論提出了重構(gòu)視頻播放過程的數(shù)學模型和給出檢測視頻卡頓次數(shù)和時長的方法。實際上,網(wǎng)絡(luò)流量數(shù)據(jù)除了視頻數(shù)據(jù)之外還包括了文本、圖片等數(shù)據(jù),種類繁多而且規(guī)模龐大。ISP需要快速清洗非視頻數(shù)據(jù)和檢測視頻卡頓信息,所以我們把我們的檢測方法部署在Apache Storm實時計算系統(tǒng)上。我們實驗的視頻主要選自國內(nèi)的視頻網(wǎng)站騰訊視頻、愛奇藝、優(yōu)酷以及全球最大的視頻網(wǎng)站YouTube。最后實驗結(jié)果通過絕對誤差、相對誤差和最小二乘擬合方法評價系統(tǒng)的性能。結(jié)果顯示我們的方法有較好的檢測效果。
[Abstract]:With the rapid development of mobile Internet, especially with the popularity of 4G network, more and more users watch network video. ISP provides Internet access services to users. In the face of a large number of Internet video users, if the network is delayed, Because of jitter or packet loss, network video is prone to the phenomenon of Catton, which seriously reduces the quality of the user's viewing experience. Therefore, ISP needs to improve the network conditions and improve the quality of the user's viewing experience in time before a large number of videos appear in Carton. In the face of severe market competition, it is not only difficult but also too expensive to buy related information through terminal feedback or video website. However, ISP can obtain video traffic data between server and client, and how to improve the user's viewing experience through network traffic has been paid more and more attention. The main work of this paper is to reconstruct the video playback process through video traffic data and to detect the number and duration of video replay. The purpose of this paper is to help ISP improve the quality of user viewing experience. Video traffic data are mainly contained in HTTP and TCP packets. Among them, the HTTP packet mainly contains the basic information of the video, and the TCP packet mainly contains the encoded video data. However, because of the protection of user privacy, ISP can not parse the basic information of the HTTP packet to extract the video, so we reconstruct the video playback process mainly through the video data in the TCP packet. Check the number and duration of the video's Catton. Since the video data of TCP packets are undifferentiated encoded video fragments, we need to estimate the basic information of video before reconstructing the video playback process. The estimation accuracy of video definition and initial delay has the greatest influence on video reconfiguration. We propose a related estimation method in this paper. After obtaining the basic information of video, we propose a mathematical model of reconstructing video playback process based on queue theory and present a method to detect the number and duration of video replay. In fact, network traffic data include text, pictures and other data in addition to video data. ISP needs to quickly clean non-video data and detect video carton information. So we deploy our detection method on Apache Storm real-time computing system. The videos we experimented with are mainly selected from domestic video websites Tencent, iqiyi, Youku and YouTube., the world's largest video site. Finally, the performance of the system is evaluated by absolute error, relative error and least square fitting method. The results show that our method has better detection effect.
【學位授予單位】：深圳大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN919.8

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