本文選題：對(duì)等網(wǎng)絡(luò)　切入點(diǎn)：多關(guān)鍵字搜索　出處：《湖南大學(xué)》2012年碩士論文

【摘要】：現(xiàn)有的基于布魯姆過(guò)濾器的P2P網(wǎng)絡(luò)多關(guān)鍵字搜索，已經(jīng)提出了兩類(lèi)最基本的查詢模式：“與查詢”和“或查詢”，使用布魯姆過(guò)濾器編碼有效地減少了檢索過(guò)程中產(chǎn)生的網(wǎng)絡(luò)流量。然而，在P2P網(wǎng)絡(luò)中，節(jié)點(diǎn)的加入和離開(kāi)是自由的，存儲(chǔ)在節(jié)點(diǎn)上的文檔可能隨著節(jié)點(diǎn)的加入和離開(kāi)而插入和刪除，但布魯姆過(guò)濾器不支持刪除操作，當(dāng)網(wǎng)絡(luò)中文檔刪除頻繁時(shí)，需要不斷地重新構(gòu)造布魯姆過(guò)濾器以適應(yīng)文檔的刪除，這樣反而給系統(tǒng)增加其他開(kāi)銷(xiāo)。另外，傳統(tǒng)的搜索引擎支持在關(guān)鍵詞前冠以加號(hào)限定搜索結(jié)果中必須包含的詞匯，而用減號(hào)則表示限定搜索結(jié)果不能包含的詞匯。然而，在P2P網(wǎng)絡(luò)的多關(guān)鍵字搜索中沒(méi)有研究過(guò)這種查詢模式。本文以P2P多關(guān)鍵字搜索機(jī)制為研究對(duì)象，主要針對(duì)P2P網(wǎng)絡(luò)的動(dòng)態(tài)特性、P2P多關(guān)鍵字搜索機(jī)制產(chǎn)生大量的網(wǎng)絡(luò)流量以及P2P網(wǎng)絡(luò)的多關(guān)鍵字搜索功能擴(kuò)展進(jìn)行研究，主要工作如下： 一、提出基于計(jì)數(shù)布魯姆過(guò)濾器的P2P“與查詢”，使用計(jì)數(shù)布魯姆過(guò)濾器存儲(chǔ)關(guān)鍵字索引表，計(jì)數(shù)布魯姆過(guò)濾器支持刪除操作，且極易向布魯姆過(guò)濾器轉(zhuǎn)換，因此基于計(jì)數(shù)布魯姆過(guò)濾器的P2P“與查詢”既可以有效地減少網(wǎng)絡(luò)中的流量，又可以適應(yīng)P2P網(wǎng)絡(luò)節(jié)點(diǎn)可以自由加入或離開(kāi)的動(dòng)態(tài)環(huán)境，提高了檢索效率。實(shí)驗(yàn)結(jié)果表明，與傳統(tǒng)的基于布魯姆過(guò)濾器的P2P“與查詢”相比，基于計(jì)數(shù)布魯姆過(guò)濾器的P2P“與查詢”在命中率上提高了5%~10%，同時(shí)在查詢延遲上，減少了10ms~40ms。 二、提出基于計(jì)數(shù)布魯姆過(guò)濾器的P2P“或查詢”，實(shí)驗(yàn)結(jié)果表明，與傳統(tǒng)的基于布魯姆過(guò)濾器的P2P“或查詢”相比，基于計(jì)數(shù)布魯姆過(guò)濾器的P2P“或查詢”在命中率上提高了7%~11%，同時(shí)在查詢延遲上，減少了12ms~45ms。 三、提出一種基于布魯姆過(guò)濾器的P2P “減查詢”，，擴(kuò)展了P2P網(wǎng)絡(luò)多關(guān)鍵字搜索的功能。實(shí)驗(yàn)結(jié)果表明，與直接傳遞文檔集合的減查詢相比，基于布魯姆過(guò)濾器的P2P“減查詢”在命中率上提高了7%~15%，在查詢延遲上，減少了10ms~37ms。在產(chǎn)生網(wǎng)絡(luò)流量方面，減少了53.01％。
[Abstract]:The existing P2P network multi-keyword search based on Bloom filter has proposed two basic query modes: "and query" and "or query".The use of Bloom filter encodes effectively reduces the network traffic generated in the retrieval process.However, in P2P networks, nodes are free to join and leave, and documents stored on nodes may be inserted and deleted as nodes join and leave, but the Bloom filter does not support delete operations, and when documents are deleted frequently in the network,It is necessary to constantly reconstruct the Bloom filter to accommodate the deletion of documents, which adds other overhead to the system.In addition, the traditional search engine supports the words that must be included in the search results by a plus sign before the keywords, while the minus sign is used to denote the words that cannot be included in the restricted search results.However, this query mode has not been studied in the multi-keyword search in P2P networks.In this paper, the P2P multi-keyword search mechanism as the research object, mainly aimed at the dynamic characteristics of P2P network, P2P multi-keyword search mechanism generated a large number of network traffic and P2P network multi-keyword search function expansion, the main work is as follows:First, the P2P "and query" based on counting Bloom filter is proposed. The counter Bloom filter is used to store the key index table. The count Bloom filter supports deletion operation, and it is easy to convert to the Bloom filter.Therefore, P2P "and query" based on counting Bloom filter can not only effectively reduce the traffic in the network, but also adapt to the dynamic environment in which P2P nodes can join or leave freely, and improve the retrieval efficiency.The experimental results show that compared with the traditional P2P "and query" based on Bloom filter, the hit ratio of P2P "and query" based on counting Bloom filter is increased by 51010cm, and the query delay is reduced by 10ms / 40ms.Secondly, the P2P "or query" based on counting Bloom filter is proposed. The experimental results show that compared with the traditional P2P "or query" based on Bloom filter,Peer-to-Peer (P2P) or query based on count Bloom filter increases the hit rate by 7% and reduces query latency by 12 Ms / 45 Ms.Thirdly, a P2P "subtractive query" based on Bloom filter is proposed, which extends the function of multi-keyword search in P2P network.The experimental results show that, compared with subtractive queries that directly transfer document sets, the hit rate of P2P subtractive queries based on Bloom filter is increased by 7 / 15, and the query delay is reduced by 10 Ms / 37 ms.In the generation of network traffic, reduced the number of 53.01.
【學(xué)位授予單位】：湖南大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2012
【分類(lèi)號(hào)】：TP393.02;TP391.3

【參考文獻(xiàn)】

相關(guān)期刊論文 前7條

1 肖明忠,代亞非,李曉明;拆分型Bloom Filter[J];電子學(xué)報(bào);2004年02期

2 崔曉微;董雷剛;;非結(jié)構(gòu)化P2P搜索方法分析及展望[J];大慶師范學(xué)院學(xué)報(bào);2011年03期

3 孫力;陳蘭;袁媛;;基于節(jié)點(diǎn)興趣的非結(jié)構(gòu)化P2P搜索機(jī)制[J];計(jì)算機(jī)工程;2009年23期

4 譚義紅;陳治平;林亞平;;基于興趣挖掘的非結(jié)構(gòu)化P2P搜索機(jī)制研究與實(shí)現(xiàn)[J];計(jì)算機(jī)應(yīng)用;2006年05期

5 張輝;孫大松;;基于路由學(xué)習(xí)的非結(jié)構(gòu)化P2P搜索技術(shù)研究[J];計(jì)算機(jī)與數(shù)字工程;2010年06期

6 謝鯤;文吉?jiǎng)?張大方;謝高崗;;布魯姆過(guò)濾器查詢算法[J];軟件學(xué)報(bào);2009年01期

7 蘇玉;毛力;;基于蟻群算法的非結(jié)構(gòu)化P2P搜索機(jī)制的研究[J];計(jì)算機(jī)工程與設(shè)計(jì);2010年05期

相關(guān)博士學(xué)位論文 前1條

1 王向輝;P2P網(wǎng)絡(luò)拓?fù)浣Y(jié)構(gòu)研究[D];哈爾濱工程大學(xué);2008年

相關(guān)碩士學(xué)位論文 前4條

1 鄧祖明;P2P搜索技術(shù)研究[D];電子科技大學(xué);2007年

2 施聰;對(duì)等網(wǎng)絡(luò)中基于關(guān)鍵字的搜索[D];上海交通大學(xué);2008年

3 趙夷平;傳統(tǒng)搜索引擎與語(yǔ)義搜索引擎比較研究[D];吉林大學(xué);2009年

4 程偉;P2P存儲(chǔ)系統(tǒng)中資源搜索機(jī)制的研究[D];中國(guó)科學(xué)技術(shù)大學(xué);2009年

本文編號(hào)：1711080