非結構同儕網路上以特徵相似度為基準之搜尋方法

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姓名

張以洵(Yi-hsun Chang) 查詢紙本館藏

畢業系所

通訊工程學系

論文名稱

非結構同儕網路上以特徵相似度為基準之搜尋方法
(Feature-based Similarity Search ApproachFeature-based Similarity Search Approach in Unstructured Peer-to-Peer Network)

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至系統瀏覽論文 ( 永不開放)

摘要(中)

本論文提出一套在非結構同儕網路上以特徵相似度為基準之搜尋方法，此方法設計上以構成物件名稱的關鍵字為該物件之特徵，同儕之間利用自身所擁有物件的特徵，計算和其它同儕之間語義上的距離，建構一個語義性重疊網路(Semantic Overlay Network；SON)，縮短具有共同興趣的同儕在語義網路上的距離，使得詢問訊息能有目標地在一個局部範圍內傳遞，減少詢問訊息傳送所產生的網路流量負載(traffic overhead)。
此方法也同時考量同儕系統內物件具有不同的冷門或熱門的特性，提出以特徵相似性來決定詢問訊息傳送的對象的同儕評比機制，並且搭配快取檢索機制來促進熱門請求物件的傳送，最後，本研究整合上述之方法提出一套可適性並行搜尋演算法，模擬結果顯示在靜態語義重疊網路上，並行搜尋演算法能達到與Flooding方法相近的搜尋命中率，並大幅減少詢問訊息數量。
關鍵字：同儕網路, 搜尋相似度, 語義重疊網路, 同儕評比

摘要(英)

This paper proposes a keyword-based search approach based on search similarity in unstructured peer-to-peer networks. Peers extract the keyword terms from object names as the objects’ features. With the feature similarity among peers’ objects, they compute semantic distance between any two peers, and then collectively construct a semantic overlay network (SON). Peers with common access/request interests can be relatively close with shorter distances. This property can used to guide the search requests to be routed in semantic vicinity where target objects could be found, and thus reduce traffic overhead to some extent.
Consider the property of object popularity, i.e., popular vs. unpopular objects. This study designs a peer ranking mechanism based on the feature-based similarity which can be used to route queries efficiently and also proposes a cache index mechanism which can improve the forwarding of queries for popular objects. With all above, this paper therefore designs an adaptive parallel search approach. Simulation results show that the proposed search mechanism can not only improve the hit rate close to that by the flooding approach, but also significantly reduce the amount of query messages.
Keywords: Peer-to-peer networks, Search similarity, Semantic overlay network, Peer ranking

關鍵字(中)

★ 同儕評比
★ 同儕網路
★ 搜尋相似度
★ 語義重疊網路

關鍵字(英)

★ Peer-to-peer networks
★ Search similarity
★ Semantic overlay network
★ Peer ranking

論文目次

摘要 I
ABSTRACT II
表目錄 V
圖目錄 VI
第一章緒論 1
1.1 研究背景 1
1.2 研究動機與目的 2
1.3 論文結構 3
第二章　相關論文 4
第三章　系統設計 6
3.1 系統描述 6
3.2 特徵分類演算法 8
3.3 靜態語義性重疊網路(SON)建構 16
3.4 請求向量GQ與節點命中率向量HI* 19
3.5 同儕評比機制(PEER RANKING MECHANISM) 21
3.6 可適性並行搜尋演算法 22
第四章模擬驗證 27
4.1 模擬環境 27
4.2 WALKER數目對搜尋命中率的影響 28
4.3 FEATURE-SIMILARITY-BASED搜尋方法與FLOODING搜尋方法之比較 31
第五章　結論與未來研究工作 35
5.1結論 35
5.2未來研究工作 35
參考文獻 37

參考文獻

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指導教授

胡誌麟(Chih-lin Hu)

審核日期

2010-8-27

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