本文選題：Web緩存　切入點(diǎn)：緩存替換算法　出處：《江西理工大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著Internet網(wǎng)絡(luò)的迅速發(fā)展，Internet應(yīng)用已遍及工業(yè)、軍事、醫(yī)療、教育等領(lǐng)域，給人們的生活帶來(lái)了極大的便利。與此同時(shí)，網(wǎng)絡(luò)用戶接入數(shù)量急劇膨脹，而網(wǎng)絡(luò)帶寬等硬件設(shè)施的升級(jí)非常有限，用戶在瀏覽網(wǎng)絡(luò)資源時(shí)具有較大的訪問(wèn)延遲。如何減少用戶訪問(wèn)延遲、提高用戶訪問(wèn)速度是Web領(lǐng)域面臨的實(shí)際問(wèn)題。Web緩存通過(guò)保存用戶訪問(wèn)過(guò)的內(nèi)容，，有效減少了用戶獲取網(wǎng)絡(luò)資源等待時(shí)間，但其無(wú)法對(duì)用戶即將訪問(wèn)的內(nèi)容進(jìn)行主動(dòng)地緩存。預(yù)取技術(shù)彌補(bǔ)了Web緩存技術(shù)的不足，已成為優(yōu)化緩存系統(tǒng)性能、降低用戶訪問(wèn)延遲的重要方法。本文充分利用預(yù)取技術(shù)能預(yù)測(cè)用戶的訪問(wèn)對(duì)象的優(yōu)勢(shì)，提出了一種基于預(yù)測(cè)模型的緩存替換算法。通過(guò)仿真實(shí)驗(yàn)表明了算法的優(yōu)越性，在一定程度上提高了緩存系統(tǒng)的性能。本文的研究?jī)?nèi)容主要包含以下幾點(diǎn)： 1、本文介紹了Web緩存系統(tǒng)結(jié)構(gòu)的主要組成部分和預(yù)取技術(shù)的基本理論，對(duì)不同的緩存和預(yù)取方式分別進(jìn)行了闡述，詳細(xì)講解了Web訪問(wèn)的四個(gè)相關(guān)特性，對(duì)緩存替換算法和預(yù)取算法的研究成果進(jìn)行了研究和總結(jié)。 2、為了使日志中的數(shù)據(jù)正確、可用，介紹了Web日志挖掘的概念，以及日志數(shù)據(jù)預(yù)處理的四個(gè)主要步驟。簡(jiǎn)要介紹了Markov鏈的概念，對(duì)多Markov鏈模型進(jìn)行了詳細(xì)闡述。為了構(gòu)造多Markov鏈模型，對(duì)類Markov鏈合并、準(zhǔn)則函數(shù)和聚類相似度的相關(guān)定義進(jìn)行了討論。 3、在分析了影響緩存替換因素的基礎(chǔ)上，構(gòu)造了一個(gè)目標(biāo)函數(shù)來(lái)計(jì)算緩存中對(duì)象的鍵值，用于衡量對(duì)象在緩存中的存儲(chǔ)價(jià)值。利用預(yù)取技術(shù)能預(yù)測(cè)用戶訪問(wèn)對(duì)象的優(yōu)勢(shì)，為所有用戶構(gòu)造了多Markov鏈模型，用于訪問(wèn)對(duì)象的預(yù)測(cè)。為了提高緩存的命中率，使緩存保留具有較大存儲(chǔ)價(jià)值的對(duì)象，以及通過(guò)模型預(yù)測(cè)得到的訪問(wèn)對(duì)象，提出了基于多Markov鏈預(yù)測(cè)模型的緩存替換算法。使用日志驅(qū)動(dòng)的方法對(duì)算法進(jìn)行了仿真實(shí)驗(yàn)，并使用不同的性能評(píng)價(jià)指標(biāo)將該算法與多種算法進(jìn)行了比較。實(shí)驗(yàn)結(jié)果表明，提出的算法優(yōu)于其它算法，更能減少用戶的訪問(wèn)延遲，進(jìn)而優(yōu)化緩存的性能。
[Abstract]:With the rapid development of Internet network, Internet application has been widely used in the fields of industry, military, medical treatment, education and so on, which brings great convenience to people's life. At the same time, the number of Internet users has expanded rapidly. However, the upgrade of network bandwidth and other hardware facilities is very limited, and users have greater access latency when browsing network resources. Improving user access speed is a practical problem in the field of Web. The web cache can effectively reduce the waiting time for users to obtain network resources by saving the contents that users have visited. But it can't cache the content that the user is about to access actively. Prefetching technology has made up the deficiency of Web caching technology, and has become the optimization of caching system performance. This paper takes full advantage of the prefetching technology to predict the users' access objects, and proposes a cache replacement algorithm based on the prediction model. The simulation results show the superiority of the algorithm. To a certain extent, the performance of cache system is improved. The research content of this paper mainly includes the following points:. 1. This paper introduces the main components of Web cache system structure and the basic theory of prefetching technology, expounds the different caching and prefetching methods, and explains in detail the four related characteristics of Web access. The research results of cache replacement algorithm and pre-fetching algorithm are studied and summarized. 2. In order to make the data in log correct and usable, the concept of Web log mining and four main steps of log data preprocessing are introduced. The concept of Markov chain is briefly introduced. In order to construct the multiple Markov chain model, the definition of Markov like chain merging, criterion function and clustering similarity are discussed in detail. 3. Based on the analysis of the factors affecting cache substitution, an objective function is constructed to calculate the key value of the object in the cache, which is used to evaluate the storage value of the object in the cache. A multiple Markov chain model is constructed for all users to predict access objects. In order to improve the hit rate of cache, keep objects with large storage value, and access objects predicted by the model, A cache replacement algorithm based on multiple Markov chain prediction model is proposed. The algorithm is simulated by log driven method, and the algorithm is compared with many algorithms by using different performance evaluation indexes. The proposed algorithm is superior to other algorithms, which can reduce the user's access delay and optimize the performance of cache.
【學(xué)位授予單位】：江西理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP333;O211.62

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