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研究生: 謝承宇
Cheng-Yu Hsieh
論文名稱: 基於MPEG-DASH雲端自適性視訊串流系統設計與實作
Design and Implementation of a MPEG-DASH based Cloud Adaptive Video Streaming System
指導教授: 陳建中
Jiann-Jone Chen
口試委員: 唐政元
Cheng-Yuan Tang
何瑁鎧
Maw-Kae Hor
吳怡樂
Yi-Leh Wu
學位類別: 碩士
Master
系所名稱: 電資學院 - 電機工程系
Department of Electrical Engineering
論文出版年: 2016
畢業學年度: 104
語文別: 中文
論文頁數: 71
中文關鍵詞: 自適性串流視訊品質調整播放緩衝器控制
外文關鍵詞: MPEG-DASH, Rate Adaptation, Buffer Control
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  • 隨著網路科技進步與智慧型行動裝置普及,視訊串流相關應用之需求日增,如何提供適用使用者頻寬與運算能力之視訊串流技術為主要關鍵技術。視訊串流技術從早期需要中央伺服器控管推播串流方式轉換為高通用性的HTTP自適性串流(HTTP adaptive streaming),不僅克服防火牆與NAT穿透的問題,更能確保每位用戶都能透過線上即時影音的服務取用相應多媒體資料。目前自適性串流技術的發展如Apple的HTTP Live Streaming、Microsoft的Smooth Streaming、Adobe的HTTP Dynamic Streaming與唯一之國際標準Dynamic Adaptive Streaming over HTTP (MPEG-DASH),自適性串流技術可以因應網路頻寬發生變化適當調整視訊內容編碼參數,以提供使用者在收視期間畫面不會中斷或停頓。本論文研究與實作一基於MPEG-DASH架構之雲端自適性串流系統,使用開源軟體自行建置一雲端轉碼與串流系統平台,包含雲端伺服器、網路通道及Android用戶端的系統環境,此平台整合視訊轉碼技術與MPEG-DASH檔案封裝方式重新封裝多媒體資料,經由HTTP協定傳輸至用戶端。本論文提出一個在使用者所在網路環境下能夠提供更佳視訊品質與播放順暢度的自適性串流調整機制,其中包含基於網路流量的頻寬估測方法與根據預測播放緩衝器儲存量之視訊品質選擇策略,並且考慮在多用戶情況下如何讓每個用戶都可以穩定接收視訊串流服務與公平使用同一網路頻寬。實驗結果顯示本論文提出之基於網路吞吐量與未來播放緩衝器狀態(Network Throughput and Future Buffer,NTFB)的自適性串流演算法,可以不受播放緩衝器大小與多用戶情況下影響,且在系統效能與PSNR上相較於參考方法都有更好的效果。


    With the prevalence of video streaming services (e.g. YouTube, Netflix), cloud video streaming technologies become important. HTTP-based adaptive streaming (HAS) has emerged as the prominent technology for video delivery over the Internet. The HAS allows video streaming services to go through firewalls and NAT friendly and has the potential to improve the quality of service (QoS), as comparison with the traditional centralized streaming service. In the HAS approach, video contents are segmented into small packets with fixed time duration and then encoded at multiple resolutions and bitrates to meet the requirements of user network conditions and heterogeneous devices. In this thesis, we design and implement a cloud HTTP adaptive streaming system based on MPEG-DASH standard, which includes a server and multiple DASH clients. We also propose a client-side adaptive algorithm, based on network throughput and future buffer usage (NTFB). As multiple clients share the same network resources and compete for available bandwidth, the NTFB will select the required video segment from a best client, which compromises stability, fairness, and efficiency for robust video adaption. Experimental results show that, as compared with conventional algorithms, the NTFB can yield smoother bitrate transmission and higher video PSNRs with a smaller buffer.

    第一章 緒論 1.1 研究背景與動機 1.2 研究項目與方法概述 1.3 論文架構 第二章 背景知識與相關文獻探討 2.1 媒體串流之編碼壓縮相關背景知識 2.1.1 H.264/AVC 2.1.2 視訊轉碼技術 2.2 網路傳輸技術 2.2.1 傳輸層視訊串流協定(TCP vs. UDP) 2.2.2 應用層視訊串流協定(HTTP vs. RTSP) 2.2.3 可用頻寬估測技術分析 2.2.4 網路頻寬使用之ON-OFF狀態 2.3 HTTP自適性串流技術之介紹與比較 2.3.1 Apple HTTP Live Streaming 2.3.2 Microsoft Smooth Streaming 2.3.3 Adobe HTTP Dynamic Streaming 2.3.4 MPEG Dynamic Adaptive Streaming over HTTP 2.3.5 自適性串流技術比較 2.4 自適性串流之相關演算法探討 2.4.1 基於網路吞吐量之視訊品質選擇策略 2.4.2 基於播放緩衝器儲存量之視訊品質選擇策略 2.4.3 視訊片段下載排程 第三章 本論文之系統架構 3.1 整體系統架構與功能描述 3.2 雲端視訊轉碼平台 3.2.1 視訊檔案分段 3.2.2 MapReduce平行處理模型 3.3 MPD更新機制 3.4 DASH用戶端運作流程 第四章 所提出之方法 4.1 問題描述 4.2 演算法流程 4.3 可用頻寬估測(Available Bandwidth Estimation) 4.4 視訊品質選擇策略(Bitrate Adaptation) 4.5 片段下載請求排程(Segment Request Scheduling) 第五章 實驗結果 5.1 實驗環境與參數設置 5.1.1 實驗前提 5.1.2 實驗平台 5.1.3 實驗測試序列 5.1.4 網路模擬器(Network Emulator) 5.1.5 系統效能指標 5.1.6 實驗流程 5.2 單一用戶之實驗結果與分析 5.2.1 遞增網路模型 5.2.2 遞減網路模型 5.2.3 隨機網路模型 5.3 多用戶之實驗結果分析 5.3.1 多用戶在不同播放緩衝器大小之分析 5.3.2 多用戶之系統效能分析 5.4 實驗結果與討論 第六章 結論與未來方向 6.1 結論 6.2 未來展望 參考文獻

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