隨著網路科技進步與智慧型手持式裝置的普及，人們使用網路來觀看影片的需求也日益增多，這樣的演變發展也間接地促進許多網路即時串流技術的崛起，網路串流方式從需要伺服器擔任控管角色的推播式串流逐漸轉換成高通用性的HTTP-based串流，不但解決防火牆與NAT穿透的問題，更能確保每個用戶都能成功獲取多媒體資料，享受線上即時影音的服務。
而在HTTP-based的串流中也有許多工業實現的即時自適性串流協定，如：Adobe’s HTTP Dynamic Streaming、Microsoft’s Smooth Streaming以及Apple’s HTTP Live Streaming等，針對網路頻寬發生變化時做出適時的調整，以能提供使用者不會有中斷觀看為大前提進行調校，不過，也由於調教方式往往不是根據使用者的觀看習性與主觀體驗進行修正，會造成系統只是在做符合當前硬體或設施限制的串流。
有鑑於此，本論文進行使用者對影片的兩項編碼因素進行滿意度調查，設計出能在相同網路頻寬下提供使用者更佳的影片品質與播放順暢度的自適性串流機制，不以客觀因素決定影片品質，而是藉由主觀感受而認定那些品質是更能提升使用者的滿意度。在系統實現上採用動態自適性串流的國際標準MPEG-DASH為串流核心，並將串流實現於Android的多媒體框架中且移植到TI Pandaboard ES開發版上進行驗證。本論文亦提出一套決策模型與基於緩衝的頻寬預測方法當作此符合QoE自適性串流的調控機制，藉以提升使用者觀賞影片的滿意度，根據實驗結果，於一般網路的行為上能使使用者的體驗滿意度上升近20%。

Due to improvement of network technologies and population of smart handheld devices, the requirement of network video streaming are increaseing. This trend leads to many new network streaming technologies were developed, such as Adobe’s HTTP Dynamic Streaming、Microsoft’s Smooth Streaming and Apple’s HTTP Live Streaming.
In order to provide one better quality streaming and smoother playback experience, those streaming methods, Adaptive HTTP Streaming, can adjust quality of video streaming according to variations of bandwidth or computing power. The streaming device can download the suitable quality of media segment or chunk, which were pre-encoded into different bitrates and stored in server. However those methods just adjust the quality according to limitation of facilities, not choose the best of user experience feedbacked content.
In this paper, we investigate two facts of quality of video encoding for user watching experience. Design and implement one QoE-based adaptive streaming mechanism for improving quality and fluency of video streaming. We use MPEG-DASH and port Google Android 4.2.2 Jelly Bean operating system on TI PandaBoard ES. And we also provide one buffer-based bandwidth prediction and strategic decision module for adaptive streaming. According to experimental result, this mechanism can improve 20% satisfaction of watching video streaming in normal network situations.

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