隨著科技進步，人們對於觀看影音串流的需求大幅增加，商業化影音平台仍以主從式(Client-Server)架構為主，然而，同儕式網路(Peer-To-Peer，P2P)的概念是每個使用者都是對等的，可以直接交換視訊片段，有效降低單一影音串流伺服器之負擔，但商業化平台未能納入同儕式網路(P2P)機制之主因是其快取(Cache)分佈不均，以致造成影音串流品質不穩定，因此，本論文提出以隨機線性網路編碼(Random Linear Network Coding，RLNC)以及有限域算數(Galois Field Arithmetic)改善同儕式串流(P2P Streaming)缺點，運用隨機線性網路編碼(RLNC)改善封包遺失時之傳輸速度，同時有限域算數(Galois Field Arithmetic)動態調整快取(Cache)分布不均的情況，進而達成快取(Cache)高彈性儲存。本論文在節點(Peer)頻繁跳離時可增加1.1%~10.8%透過同儕式網路(P2P)請求之緩衝區(Buffer)大小；當節點發生封包遺失(Packet Loss)時，因改善傳輸速度而可增加3.8%~19.2%透過同儕式網路(P2P)請求之緩衝區(Buffer)大小；在快取(Cache)較集中時，無論新加入節點(Peer)間隔前一節點(Peer)多久，可提升11.8%~54.7%透過同儕式網路(P2P)請求之緩衝區(Buffer)大小。上述提及提升透過同儕式網路(P2P)請求之緩衝區(Buffer)大小表示本論文可有效提昇快取(Cache)種類及數量，因而降低伺服器負擔。

With the advancement of technology, people’s demand for watching video streaming has increased. Most commercial video streaming platforms adopt the client-server architecture as default. In the peer to peer (P2P) architecture, each peer has the same capability and can exchange video data directly. P2P can reduce the burden of streaming servers. However, why the commercial platforms do not adopt the P2P architecture is that P2P may have the unstable quality of watching video streaming due to the unevenly distributed cache. Therefore, this paper would propose to utilize random linear network coding (RLNC) and Galois field arithmetic to improve P2P streaming. RLNC can improve packet loss, and Galois field arithmetic is able to dynamically adjust the distribution of cache, reduce transmission delay and cache highly elastic storage. When the churn of peers keeps high, our proposal can add 1.1%~10.8% buffer size of P2P requests. When packet loss keeps happened, our proposal can add 3.8%~19.2% buffer size of P2P requests. When the P2P caches become homogeneous, our proposal can add 11.8%~54.7% buffer size from P2P requests. As mentioned earlier, those add buffer size from P2P requests can represent this paper can add cache's type and count thus server reduced burden.

摘要 i
ABSTRACT iii
誌謝 v
目錄 vi
圖目錄 viii
第一章　緒論 1
1.1 研究動機 1
1.2 研究目的 2
1.3 論文架構 3
第二章　文獻探討 5
2.1 主從式架構 5
2.2 同儕式網路架構 6
2.3 混合式架構 8
2.4 網路編碼 10
第三章　系統架構分析與設計 14
3.1 結合網路編碼之提案分析 14
3.1.1 減少Cache儲存空間儲存並融合無冗餘錯位編碼傳輸提高Cache彈性 14
3.1.2 傳送時使用冗餘擴充彌補封包遺失 15
3.1.3 減少Cache儲存空間儲存並融合無冗餘編碼保存提高Cache彈性 17
3.1.4 以冗餘擴充保存彌補封包遺失 19
3.1.5 透過加法編碼使資源同時抵達目的地 20
3.1.6 透過加法編碼混合保存熱門及稀有Cache 21
3.2 Web-P2P Streaming with dynamic RLNC 23
第四章　實驗結果 28
4.1 P2P Churn 28
4.2 網路情況變化 35
4.3 Cache集中 37
第五章　結論 45
參考文獻 47
附錄A 52
有限域算數(Galois Field Arithmetic)運算方式 52
有限域算數(Galois Field Arithmetic)加法運算 52
有限域算數(Galois Field Arithmetic)最小多項式 52
有限域算數(Galois Field Arithmetic)乘法 53
附錄B 54
隨機線性網路編碼(RLNC)編碼流程 54
隨機線性網路編碼(RLNC)解碼流程 55
附錄C 56
論文初稿原創性比對 56
論文完稿原創性比對 57

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