近年來，由於多媒體及網路技術漸趨成熟，無所不在的多媒體服務之需求已顯著成長。為達成高傳輸速度及高資源可得性，點對點視訊串流應用程式及技術隨之普及且受重視，如PPStream及PPLive等軟體。然而在異質點對點網路環境中，使用者將可使用手機、PDA、筆記型電腦或個人電腦，並經由不同網路以存取隨選視訊服務。基於此議題，必須定義全新視訊編解碼架構以針對不同平台實現相應空間解析度/失真性的影片傳輸及播放。本論文提出 Multiple-Described Scalable Video Coding (MD-SVC)編解碼架構以及同儕網路拓蹼結構整合緩衝察覺式串流平台，並利用多核心平行程式化技術提供點對點視訊串流。在MD-SVC架構中，不同的MDC描述中各自包含原始影片中相異的畫格段，且每畫格均編碼為基礎層(base layer)及數個SVC增強層(enhancement layers)。更進一步地，我們定焦於全新非對稱性裝置調適性點對點串流系統的設計。此技術之拓蹼結構將以裝置能力、頻寬及封包往返時間為根據，承擔階層式會員樹之建立工作。而動態緩衝察覺式資料串流預定技術(Dynamic Buffer-aware Scheduling)將根據用戶端緩衝區內時間性呈現長度決定是否重新選擇來源提供者。在實驗中，我們將展示MD-SVC的實作，以及相關效能實測：與SVC比較PSNR值與解碼效能、在不同點對點網路壅塞及易誤性情況下的比較、平均同儕服務啟始時間、拓蹼穩定性、平均搜尋時間、於不同畫格速閾值下之延遲時間比等等。

Recently, the demands of universal multimedia service significantly increased due to mature multimedia processing and Internet technology. To achieve higher transmission speed and data availability, P2P video streaming applications become widely popular and emphasized, e.g., PPstream and PPlive. However, in the heterogeneous P2P network environment, users are eligible to utilize PDA, notebook or desktop computer through distinct network interfaces to get on-demand videos ubiquitously. To provide distinct spatial-resolution/fidelity videos and flexible video transmission (playback) over P2P networks, a brand new coding architecture needs to be devised. Also, unlike a homogeneous P2P network environment, a scenario of asymmetric P2P (A-P2P) streaming depicts that different peers' roles have different (asymmetric) capabilities of resource sharing with specific P2P topologies among heterogeneous devices and networks. In this thesis, we propose Multiple-Described Scalable Video Coding (MD-SVC) video coding scheme using the multi-core parallel programming paradigm for P2P video streaming; thereupon, focus on designing a novel a-P2P streaming architecture. In the proposed MD-SVC coding scheme, distinct MDC descriptions contain distinct portions of raw video frames, and each raw frame can be compressed as base layer and SVC enhancement layers. Furthermore, a proposed Dynamic Peer-Topology Management (DPTM) is responsible for constructing a hierarchical membership-tree based on the computing power of device, capacity of upstream bandwidth and round-trip-time. Besides, the dynamic buffer-aware scheduling is able to determine whether the peer needs to reconnect to a proper source provider based on temporal presentation length (TPL) in client's buffer. In our experiments, a real implementation of MD-SVC is exhibited and corresponding performances, e.g., PSNR and decoding speeds, are compared with original SVC in distinct congestion-level over P2P networks. Also, for streaming issues, comprehensive simulations such as average peer joining time, peer failure ratio, and peer waiting time will be measured and demonstrated.

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