【摘要】：云計(jì)算是搭建在同構(gòu)廉價(jià)普通節(jié)點(diǎn)上的分布式計(jì)算環(huán)境，在節(jié)點(diǎn)不可信的特點(diǎn)下，分布式存儲(chǔ)成為了云計(jì)算的必然選擇，存儲(chǔ)與計(jì)算的整合趨勢(shì)也日益明顯。本文搭建了一個(gè)簡(jiǎn)單的對(duì)等架構(gòu)的云計(jì)算環(huán)境，并從分布式存儲(chǔ)與并行計(jì)算兩個(gè)方面對(duì)二者可能的協(xié)同進(jìn)行了研究，提出了一套分布式存儲(chǔ)策略和面向數(shù)據(jù)驅(qū)動(dòng)的調(diào)度策略。 本文的云計(jì)算環(huán)境的物理層搭建在機(jī)柜式環(huán)境上，網(wǎng)絡(luò)拓?fù)鋵硬捎脤?duì)等式架構(gòu)，整個(gè)環(huán)境基于Spring框架和各Java嵌入式組件搭建，并采用了多種流行通信框架，可以實(shí)現(xiàn)環(huán)境的快速搭建、高可擴(kuò)展和快速部署。本文將傳統(tǒng)的MPI環(huán)境與分布式存儲(chǔ)進(jìn)行了整合，探究了一種云計(jì)算環(huán)境下不采用MapReduce編程模型實(shí)現(xiàn)并行計(jì)算的方法。 在協(xié)同性的分布式存儲(chǔ)方面，本文提出了一套云計(jì)算環(huán)境下適用于地震資料的分布式存儲(chǔ)策略，該策略在充分研究地震資料及其處理特點(diǎn)的基礎(chǔ)上，對(duì)地震資料的數(shù)據(jù)劃分，副本的部署和定位進(jìn)行了研究。在協(xié)同性的并行計(jì)算方面，本文除了對(duì)分布式存儲(chǔ)和MPI環(huán)境進(jìn)行了整合，還設(shè)計(jì)了一種面向數(shù)據(jù)驅(qū)動(dòng)的對(duì)等式調(diào)度策略，，該策略充分利用了分布式存儲(chǔ)的優(yōu)勢(shì)，不僅攤銷(xiāo)了分布式存儲(chǔ)的成本，而且節(jié)約了數(shù)據(jù)準(zhǔn)備的時(shí)間。
[Abstract]:Cloud computing is a distributed computing environment built on the isomorphic low cost ordinary nodes. With the characteristics of the nodes being unreliable, distributed storage has become the inevitable choice of cloud computing, and the integration of storage and computing is becoming more and more obvious. In this paper, a simple peer-to-peer cloud computing environment is built, and the possible collaboration between distributed storage and parallel computing is studied. A set of distributed storage strategy and data-driven scheduling strategy are proposed. In this paper, the physical layer of cloud computing environment is built in the cabinet environment, the network topology layer adopts the peer-to-peer architecture, the whole environment is based on the Spring framework and each Java embedded component, and adopts a variety of popular communication frameworks. Environment can be quickly built, high scalability and rapid deployment. In this paper, the traditional MPI environment is integrated with distributed storage, and a method of parallel computing without using MapReduce programming model in cloud computing environment is explored. In the aspect of collaborative distributed storage, this paper proposes a distributed storage strategy for seismic data in cloud computing environment. Based on the full study of the characteristics of seismic data and its processing, this strategy divides the seismic data. The deployment and location of copies were studied. In the aspect of collaborative parallel computing, this paper not only integrates distributed storage and MPI environment, but also designs a data-driven peer-to-peer scheduling strategy, which makes full use of the advantages of distributed storage. It not only amortizes the cost of distributed storage, but also saves the time of data preparation.
【學(xué)位授予單位】：中國(guó)石油大學(xué)（華東）
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類(lèi)號(hào)】：TP333

【參考文獻(xiàn)】

相關(guān)期刊論文 前5條

1 文領(lǐng)章;劉財(cái);魏旭光;;網(wǎng)絡(luò)存儲(chǔ)技術(shù)在石油地震數(shù)據(jù)處理中的應(yīng)用[J];吉林大學(xué)學(xué)報(bào)(地球科學(xué)版);2010年S1期

2 劉國(guó)志;趙誠(chéng);吳宏剛;;地震數(shù)據(jù)存儲(chǔ)設(shè)備的性能及其在地震儀器上的應(yīng)用[J];物探裝備;2008年06期

3 王磊;解福;;信任驅(qū)動(dòng)的資源調(diào)度算法[J];微型機(jī)與應(yīng)用;2010年18期

4 魯大營(yíng);曹寶香;;基于計(jì)算網(wǎng)格的移動(dòng)Agent透明性遷移[J];科技資訊;2006年26期

5 曾薇;楊樂(lè);譚穎;;網(wǎng)絡(luò)存儲(chǔ)技術(shù)在地震數(shù)據(jù)存儲(chǔ)中的應(yīng)用[J];震災(zāi)防御技術(shù);2011年03期

本文編號(hào)：2140568