發(fā)布時間：2018-05-06 06:07

  本文選題：CDN + P2P　； 參考：《北京郵電大學》2014年碩士論文

【摘要】：近些年隨著互聯(lián)網(wǎng)和流媒體技術(shù)的發(fā)展,流媒體服務逐漸成為互聯(lián)網(wǎng)的重要應用,并且趨向于向大規(guī)模、高質(zhì)量的方向發(fā)展。大規(guī)模流媒體服務也成為近年來的研究熱點。 相關(guān)研究表明,結(jié)合CDN和P2P技術(shù)的優(yōu)點,將它們應用到流媒體傳輸系統(tǒng)中能夠顯著提高流媒體傳輸?shù)男阅�。本文重點研究了以下三方面的內(nèi)容： 第一,針對系統(tǒng)中的網(wǎng)絡節(jié)點具有高度的自治性、動態(tài)性的特點,為了使系統(tǒng)中的服務請求節(jié)點能夠獲得更穩(wěn)定流暢的流媒體傳輸服務,我們在系統(tǒng)中加入了基于網(wǎng)絡距離和穩(wěn)定性的鄰居推薦功能。它能夠根據(jù)節(jié)點的網(wǎng)絡距離劃分網(wǎng)絡域,并幫助節(jié)點從網(wǎng)絡域中選擇穩(wěn)定性較好的節(jié)點作為鄰居節(jié)點�？梢允狗�(wěn)定性高的節(jié)點充分匹配,提高了服務的質(zhì)量。 第二,隨著系統(tǒng)中節(jié)點數(shù)量和資源數(shù)量增多,我們在系統(tǒng)中增加了基于用戶鄰域的推薦功能,幫助系統(tǒng)中的用戶找到他們可能喜歡的資源。但僅僅依靠中心服務器的協(xié)同過濾,計算量大、計算時間長。因此我們在原有的推薦算法上進行了改進,形成了基于興趣子網(wǎng)的分布式協(xié)同過濾推薦算法。該算法將大量的相似性計算任務分配給節(jié)點來完成,節(jié)點通過自發(fā)的相似性計算,組成興趣子網(wǎng)。然后由中心服務器完成推薦。降低了推薦過程的計算量,又不失推薦準確性。 第三,系統(tǒng)中的節(jié)點緩存有限,節(jié)點只有在緩存了服務請求節(jié)點請求的媒體段時,才能向該服務請求節(jié)點提供傳輸服務。顯然,能夠提供傳輸服務的節(jié)點越多,服務節(jié)點的壓力就會越小。針對這一問題,我們在系統(tǒng)中加入了基于資源熱度和分段優(yōu)先級的FIFO緩沖區(qū)替換策略,該策略根據(jù)節(jié)目熱度和用戶觀看節(jié)目時的習慣來管理緩沖區(qū),優(yōu)先保留優(yōu)先級較高的視頻塊,提高了能夠提供服務的節(jié)點的個數(shù),減小了服務節(jié)點的壓力和啟動延時。
[Abstract]:In recent years, with the development of Internet and streaming media technology, streaming media service has gradually become an important application of the Internet, and tends to the direction of large scale and high quality. Large-scale streaming media service has also become a research hotspot in recent years. Related studies show that the application of CDN and P2P technology to streaming media transmission system can significantly improve the performance of streaming media transmission. This paper focuses on the following three aspects: We add neighbor recommendation function based on network distance and stability in the system. It can divide the network domain according to the network distance of the node, and help the node to select the stable node as the neighbor node from the network domain. The nodes with high stability can be fully matched and the quality of service can be improved. Secondly as the number of nodes and resources increases in the system we add the recommendation function based on the user neighborhood to help the users to find the resources they may like. However, it only depends on the collaborative filtering of the central server, which results in a large amount of computation and a long calculation time. Therefore, we improve the original recommendation algorithm and form a distributed collaborative filtering recommendation algorithm based on interest subnet. The algorithm allocates a large number of similarity calculation tasks to nodes, which form subnets of interest through spontaneous similarity calculation. The recommendation is then completed by the central server. The calculation amount of recommendation process is reduced, and the accuracy of recommendation is not lost. Thirdly, the node cache in the system is limited. Only when the media segment requested by the service request node is cached, can the node provide the transmission service to the service requesting node. Obviously, the more nodes that can provide transport services, the less pressure on service nodes. In order to solve this problem, we add a FIFO buffer replacement strategy based on resource heat and segment priority, which manages the buffer according to the program heat and user's habit of watching the program. The priority is to retain the high priority video blocks, which can increase the number of nodes that can provide services and reduce the pressure and startup delay of service nodes.
【學位授予單位】：北京郵電大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TP393.02;TP391.3

【參考文獻】

相關(guān)期刊論文 前10條

1 楊戈;廖建新;朱曉民;樊秀梅;;流媒體分發(fā)系統(tǒng)關(guān)鍵技術(shù)綜述[J];電子學報;2009年01期

2 盛明;李捷;王鴻;;基于CDN路由的輕量級P2P節(jié)點選擇方案[J];河南大學學報(自然科學版);2011年01期

3 龔海剛;劉明;毛鶯池;陸桑璐;謝立;;P2P流媒體關(guān)鍵技術(shù)的研究進展[J];計算機研究與發(fā)展;2005年12期

4 李聰;梁昌勇;馬麗;;基于領(lǐng)域最近鄰的協(xié)同過濾推薦算法[J];計算機研究與發(fā)展;2008年09期

5 劉瑜;朱光喜;尹浩;劉雪寧;;內(nèi)容分發(fā)網(wǎng)發(fā)展綜述[J];計算機科學;2009年02期

6 王文波;范訓禮;房鼎益;;基于緩存偏移量的P2P流媒體調(diào)度策略[J];計算機工程;2009年23期

7 尹浩;林闖;文浩;陳治佳;吳大鵬;;大規(guī)模流媒體應用中關(guān)鍵技術(shù)的研究[J];計算機學報;2008年05期

8 楊傳棟,余鎮(zhèn)危,王行剛;結(jié)合CDN與P2P技術(shù)的混合流媒體系統(tǒng)研究[J];計算機應用;2005年09期

9 臧運港;陳光喜;;基于P2P和CDN的混合流媒體分發(fā)模型及分析[J];計算機應用研究;2010年06期

10 姜濤;鐘亦平;呂智慧;;基于PeerCast的P2P流媒體多點播放緩存管理設(shè)計[J];計算機應用與軟件;2009年06期

，

本文編號：1851103