【摘要】：視頻點播VoD（Video-on-Demand）實現(xiàn)了用戶與視頻資源高度交互的訪問模式，，使其得到越來越多用戶的青睞，成為目前互聯(lián)網(wǎng)上需求量最大的服務之一。點播服務中用戶交互式操作、用戶實時性觀看需求、服務規(guī)模爆炸性增長及用戶視頻數(shù)據(jù)請求量不穩(wěn)定性等特點給實現(xiàn)一種高用戶滿意度且經(jīng)濟有效的點播服務帶來了一定的問題�？紤]到點播系統(tǒng)中視頻片段及視頻間存在的關聯(lián)性特征，本文基于關聯(lián)性特征對如何實現(xiàn)經(jīng)濟有效且高質(zhì)量的點播服務進行了優(yōu)化研究，主要從以下幾個問題進行展開： 1）快速資源定位機制的實現(xiàn)。針對該問題，提出一種基于視頻片段關聯(lián)性的點播服務模型。所提模型利用視頻點播中視頻各個片段之間關聯(lián)性強度不同這一特點，使具有相似興趣點的節(jié)點能夠自主地組織在一起，從而有效地提高了節(jié)點在進行轉跳操作時查找目的片段的效率，提升了用戶觀看滿意度。對由該策略引出的節(jié)點鄰居優(yōu)化問題進行了分析，將其形式化描述為集合覆蓋問題，并提出一種基于貪心算法的鄰居近似優(yōu)化策略來解決該問題。仿真對比實驗驗證了所提策略在降低查找時延方面的有效性，并對所提鄰居優(yōu)化算法的有效性進行了驗證。 2）有關聯(lián)性視頻的點播服務在云平臺上的部署。針對該問題，本文通過對YouTube上有關聯(lián)性關系視頻的采集，得出用戶以近似90%的概率會選擇當前視頻三跳關聯(lián)以內(nèi)的視頻進行觀看這一結論，基于此提出一種基于簇的P2P云輔助點播服務模型。在所提模型中，由于云服務器存在一定的啟動延遲，因此對簇的帶寬遷移量進行了預測；針對云服務器有著不同的類型、租用代價以及服務能力的特點，提出一種滿足用戶帶寬需求前提下降低云服務器租用代價的云服務器租用策略，仿真對比實驗驗證了所提策略在降低服務資源開銷以及提高用戶滿意度上的有效性。 3）關聯(lián)性視頻內(nèi)容在分布式云服務器上的內(nèi)容放置問題。針對該問題，考慮到關聯(lián)性視頻的區(qū)域流行度差異，提出一種地域感知的關聯(lián)性視頻內(nèi)容在分布式云服務器上的內(nèi)容放置策略。該策略目的是在盡量維持關聯(lián)性關系及不同云服務器上負載均衡的同時降低用戶跨地域請求率。將問題形式化描述為一個有限制的K中心點劃分問題，提出一種地域感知的PAM算法解決該問題。仿真對比實驗表明了該算法在提高用戶本地請求率和降低用戶跨區(qū)域請求方面的有效性，同時也能較好地維持視頻之間的關聯(lián)關系。 4）提高節(jié)點緩存空間利用率的關聯(lián)性視頻內(nèi)容緩存替換問題。針對此問題，提出一種基于視頻相似的緩存替換策略。所提策略優(yōu)先考慮替換同已替換視頻集合語義相似度較大即可能為不受歡迎的視頻，并使替換視頻整體流行度盡可能地小且副本數(shù)盡可能地大。該問題可描述為一個多目標優(yōu)化問題，將其轉換為單目標優(yōu)化問題并進一步給出緩存替換策略。仿真實驗分析了策略中參數(shù)設置對緩存命中率的影響，并證實了所提策略在提高緩存內(nèi)容命中率上的有效性。 本論文研究得到國家“863計劃”專項課題（2008AA01A315），教育部高等學校博士學科點專項科研基金課題“基于云服務的視頻點播關鍵技術研究”(20114101110007)，河南省科技創(chuàng)新人才計劃項目“P2P VoD關鍵技術問題研究”（2011HASTIT003)以及河南省教育廳重點項目“基于云平臺的P2P VoD關鍵技術研究”(13A520562)的資助。
[Abstract]:Video-on-Demand (VOD) has become one of the most demanding services on the Internet because of its highly interactive access mode between users and video resources. Considering the correlation between video clips and videos in VOD system, this paper studies how to optimize the cost-effective and high-quality VOD service based on the correlation characteristics. We should start with the following issues:
1) Realization of a fast resource location mechanism. To solve this problem, an on-demand service model based on video clip association is proposed. The proposed model takes advantage of the different correlation strength between video clips in VOD, so that nodes with similar interest points can be organized independently, thus effectively improving the nodes. The efficiency of searching for the target segment during the jump operation improves the user's viewing satisfaction. The neighborhood optimization problem derived from this strategy is analyzed and formally described as a set coverage problem. A neighborhood approximate optimization strategy based on greedy algorithm is proposed to solve the problem. The proposed strategy is effective in reducing the search delay, and the validity of the proposed neighborhood optimization algorithm is verified.
2) Deployment of associative video on the cloud platform. To solve this problem, this paper collects related video on YouTube, and concludes that users will choose the video within the current three-hop association with a probability of 90%. Based on this conclusion, a cluster-based P2P cloud-assisted VOD service is proposed. In the proposed model, the bandwidth migration of the cluster is predicted because of the delay of the start-up of the cloud server, and a rental policy of the cloud server is proposed to reduce the rental cost of the cloud server while satisfying the user's bandwidth requirement. Simply, the simulation results verify the effectiveness of the proposed strategy in reducing service resource overhead and improving user satisfaction.
3) Content placement of related video on distributed cloud servers. To solve this problem, considering the regional popularity difference of related video, a region-aware content placement strategy for related video on distributed cloud servers is proposed. The problem is formally described as a restricted K-center partitioning problem, and a region-aware PAM algorithm is proposed to solve this problem. Simulation results show that the algorithm is effective in improving the local request rate and reducing the cross-region request rate. It can also better maintain the correlation between videos.
4) Relevant video content cache replacement problem to improve node cache space utilization. To solve this problem, a video-based cache replacement strategy is proposed. The proposed strategy gives priority to replacing videos that may be undesirable if they have a large semantic similarity with the replaced video set, and makes the replacement video as popular as possible. This problem can be described as a multi-objective optimization problem, which can be transformed into a single-objective optimization problem and a cache replacement strategy is given. The simulation results show that the proposed strategy is effective in improving the cache hit rate.
In this paper, the National 863 Program (2008 AA01A315), the Ministry of Education's Ph.D. Program Research Foundation Project "Research on Key Technologies of VOD Based on Cloud Services" (20114101110007), the Henan Science and Technology Innovation Talents Program Project "Research on Key Technologies of P2P VoD" (2011 HASTIT003) and The key project of Henan Provincial Department of education is supported by "P2P VoD key technology research based on cloud platform" (13A520562).
【學位授予單位】：鄭州大學
【學位級別】：博士
【學位授予年份】：2014
【分類號】：TN948.64

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