本文選題：視頻流 + 興趣挖掘　； 參考：《電子科技大學(xué)》2013年碩士論文

【摘要】：中國互聯(lián)網(wǎng)數(shù)據(jù)平臺(tái)的相關(guān)數(shù)據(jù)顯示，網(wǎng)絡(luò)視頻是用戶人均單日訪問時(shí)間最長的應(yīng)用，同時(shí)在線視頻已成為互聯(lián)網(wǎng)第一大應(yīng)用。對(duì)于網(wǎng)絡(luò)運(yùn)營商而言，其主要收入來源于向用戶銷售使用時(shí)長，大量的視頻流量并沒有帶來對(duì)稱的收入增長，同時(shí)由于市場競爭加劇，整個(gè)產(chǎn)業(yè)資費(fèi)水平下降，運(yùn)營商亟需改變傳統(tǒng)的盈利模式，由業(yè)務(wù)向服務(wù)的轉(zhuǎn)變是關(guān)鍵。而對(duì)于視頻服務(wù)提供商而言，，目前提供的都是免費(fèi)視頻，廣告收入拿捏著他們發(fā)展的命脈，而廣大、穩(wěn)定的視頻用戶群體是其營收的保證。當(dāng)前視頻資源異常豐富，要想培養(yǎng)忠實(shí)的粉絲，具有吸引力的內(nèi)容固然重要，如果能夠準(zhǔn)確根據(jù)用戶興趣主動(dòng)推薦視頻，將深深俘獲視頻用戶的心，但若因?yàn)榫W(wǎng)絡(luò)狀況而影響到最終的視覺體驗(yàn)，將功虧一簣。 另一方面，如果運(yùn)營商的網(wǎng)絡(luò)設(shè)備能夠?qū)I(yè)務(wù)進(jìn)行感知，可以識(shí)別傳輸網(wǎng)絡(luò)中的視頻流并進(jìn)行一些用戶興趣挖掘工作，為個(gè)性化服務(wù)提供一定的依據(jù)，差別服務(wù)及收費(fèi)模式的問題就可以迎刃而解，視頻服務(wù)提供商也可以訂制更高服務(wù)質(zhì)量的網(wǎng)絡(luò)而提供更好的用戶體驗(yàn)，所以由運(yùn)營商提供增值服務(wù)，由視頻服務(wù)提供商支付增值費(fèi)用，可以說是一個(gè)雙贏的局面。 本論文正是針對(duì)上述問題，以P2P及Web視頻流為研究對(duì)象，在深入分析當(dāng)前視頻流識(shí)別及興趣挖掘技術(shù)原理的基礎(chǔ)上，提出在網(wǎng)絡(luò)匯聚層環(huán)境建立一個(gè)基于OpenFlow的視頻流控制系統(tǒng)，主要內(nèi)容為： 1．研究視頻流識(shí)別及興趣挖掘技術(shù)原理，接合本控制系統(tǒng)特點(diǎn)，分析OpenFlow技術(shù)架構(gòu)原理及組成，確定了原型系統(tǒng)在OpenFlow架構(gòu)下實(shí)現(xiàn)具有可行性。 2．對(duì)系統(tǒng)進(jìn)行設(shè)計(jì)，主要功能是當(dāng)網(wǎng)絡(luò)視頻流在傳輸過程中經(jīng)過匯聚設(shè)備時(shí)，路由器根據(jù)一定的規(guī)則、算法對(duì)P2P、Web視頻流進(jìn)行視頻識(shí)別，在此基礎(chǔ)上提取用戶所觀看視頻的相關(guān)信息，根據(jù)所得信息結(jié)合用戶興趣模型，對(duì)視頻流用戶進(jìn)行興趣挖掘，同時(shí)為對(duì)識(shí)別出的視頻流進(jìn)行優(yōu)先級(jí)調(diào)度，設(shè)計(jì)了相應(yīng)的計(jì)費(fèi)功能。 3．在OPNET網(wǎng)絡(luò)仿真平臺(tái)下搭建測試環(huán)境，對(duì)系統(tǒng)進(jìn)行測試并分析。
[Abstract]:According to the related data of Chinese Internet data platform, online video is the longest application per user in a single day, and online video has become the largest application of the Internet.For network operators, their main revenue comes from the length of time spent selling to users, and a large amount of video traffic does not bring symmetrical revenue growth. Meanwhile, due to the intensification of market competition, the entire industry tariff level drops.Operators need to change the traditional profit model, from business to service is the key.For video service providers, all they offer is free video, advertising revenue is their lifeblood, and a large, stable video user base is its revenue guarantee.At present, video resources are extremely rich. If you want to cultivate loyal fans, it is important to have attractive content. If you can accurately and actively recommend videos according to users' interests, it will capture the hearts of video users.But if because of the network situation and affect the final visual experience, will fall short.On the other hand, if the network equipment of the operator can perceive the service, it can identify the video stream in the transmission network and do some work of user interest mining, which can provide some basis for the personalized service.The problem of different services and charging modes can be easily solved. Video service providers can also customize networks with higher service quality to provide a better user experience, so operators can provide value-added services.It is a double-win situation that the video service provider pays the value-added fee.Aiming at the above problems, this paper takes P2P and Web video stream as the research object, on the basis of deeply analyzing the technology principle of current video stream identification and interest mining, this paper proposes to establish a video flow control system based on OpenFlow in the network convergence layer environment.The main contents are:1.This paper studies the principle of video stream recognition and interest mining, integrates the characteristics of this control system, analyzes the principle and composition of OpenFlow technology architecture, and determines the feasibility of implementing the prototype system under the OpenFlow framework.2.The main function of the system is that when the network video stream passes through the convergent device in the course of transmission, the router carries out video recognition of P2PNs Web video stream according to certain rules.On this basis, the relevant information of the video viewed by the user is extracted. According to the information obtained and the interest model of the user, the interest mining of the video stream user is carried out, and the priority scheduling of the identified video stream is carried out at the same time.The corresponding billing function is designed.3.The test environment is built on the OPNET network simulation platform, and the system is tested and analyzed.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP273;TN919.8

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本文編號(hào)：1767638