BitTorrent是目前受到相當廣泛使用之點對點（peer-to-peer）模式的網路檔案分享系統。在此系統中，一個檔案被切割成一塊塊較小的檔案片段，使得節點可以同時向不同的其他節點抓取不同的檔案片段，以縮短整個檔案完成下載所需的時間。由於檔案完成下載前的每個階段，每個節點其所擁用的檔案片段分佈與其他節點所擁有的檔案片段分佈皆不相同，在點對點網路模式中節點動態加入與離開的環境下，當擁有稀少檔案片段的節點離開造成此片段的遺失，使得系統中所有的使用者因為缺少此遺失的片段而無法完成完整檔案下載，此問題稱為斷頭問題( last block problem )。因此檔案片段的下載順序對於所有檔案片段於網路中的分佈是影響BitTorrent斷頭問題的重要關鍵，同時也對整體下載效能產生影響。
BitTorrent採用最稀少片段優先演算法(rarest first algorithm)，使每一個節點根據每一個檔案片段存在網路中的普遍度，優先選擇網路中存在最稀少的片段進行下載，藉此來減低斷頭問題發生的機率。然而，由於每個節點僅擁有其相連節點取得之片段分佈資訊，使得最稀少片段優先演算法的效能，因受限的區域性片段分佈資訊而有所限制。本文提出之方法，除了新增一個簡單的訊息交換機制，使得每一個節點能取得更廣域的片段分佈資訊做為選擇檔案片段下載的依據，同時搭配考量合作節點興趣之片段選擇演算法，有效地使得節點能夠配合其合作節點而優先下載真正稀有的檔案片段，除了達到降低斷頭問題的發生機率，也增加節點間合作的穩定性。透過模擬實驗的驗證四種相關演算法，其結果顯示，本文所提出之方法，確實相較於目前BitTorrent所使用之最稀少片段優先演算法，更加能夠避免斷頭問題的發生。

BitTorrent is a popular file distribution system based on emerging peer-to-peer communication model. Files are partitioned into pieces and can be downloaded from multiple peers in parallel in order to shorten the downloading process. However, due to dynamics of peer joining and leaving, the last block problem may occur when some rare pieces cannot be found among existing peers. BitTorrent employs a rarest-first piece selection algorithm for alleviating the last block problem, but its efficiency is limited due to a local view of peers. In this thesis, we proposed an interest-intended piece selection (IIPS) algorithm to select pieces that, if downloaded, would increase the availability of those pieces in the system while also increase the probability that the downloading peer to be selected for cooperation by its neighboring peers. This is done by a lightly-weighted vector exchanging process which enlarges the scope of piece rareness. Simulation results show that the proposed scheme effectively prevents the last block problem and outperforms the rarest-first algorithm in terms of system robustness, average file download time and the occurrences of the last block problem.

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