本文選題：容錯能力評測 + 云計算��； 參考：《哈爾濱工業(yè)大學(xué)》2013年碩士論文

【摘要】：隨著信息系統(tǒng)中數(shù)據(jù)量的迅速增長，傳統(tǒng)的計算和存儲模式已經(jīng)不能滿足日益增長的數(shù)據(jù)處理和存儲需求。在早期分布式處理、并行處理以及網(wǎng)格計算技術(shù)的基礎(chǔ)之上發(fā)展而來的云計算技術(shù)成為目前炙手可熱的海量數(shù)據(jù)解決手段。但是，隨著云計算平臺的普及與推廣，可靠性成為它面臨的一項重大困難與挑戰(zhàn)。容錯能力能夠從一個層面上反映出系統(tǒng)可靠性的高低。因此，評測云計算平臺的容錯能力對其可靠性研究具有重要意義。 由于云計算平臺的復(fù)雜程度高、軟件規(guī)模大，使得云計算平臺的容錯能力評測成為一項艱巨的任務(wù)。目前針對云計算平臺測試已有的研究成果中，涉及容錯能力評測的內(nèi)容較少并且測試方法較為單一，需要更加深入的研究與完善。 評測容錯能力的最有效手段是基于故障注入思想的測試方法。本文以開源云計算平臺—Hadoop作為研究目標(biāo)，深入研究Hadoop中核心組件的容錯機制�；诂F(xiàn)實應(yīng)用中可能出現(xiàn)的故障類型，結(jié)合Hadoop平臺的部署結(jié)構(gòu)以及運行機制的特點，，提出了一種多層次的Hadoop容錯能力測試框架。從軟件健壯性測試、MapReduce故障注入測試、網(wǎng)絡(luò)故障注入測試和HDFS故障注入測試四個層次出發(fā)，分別模擬了云計算平臺在應(yīng)用中可能出現(xiàn)的多種軟硬件異常。 依據(jù)Hadoop多層次容錯能力測試框架，設(shè)計了針對Hadoop的容錯能力評測平臺，實現(xiàn)了多種故障注入工具，形成了對Hadoop的軟件健壯性測試以及可能發(fā)生節(jié)點故障、網(wǎng)絡(luò)故障、硬盤故障等故障類型的容錯能力測試的覆蓋。在故障注入過程中，監(jiān)控和回收云計算平臺對于故障的反饋信息，進(jìn)行結(jié)果分析從而向研究人員提供真實可靠的評測結(jié)果，最終為云計算平臺的容錯能力評測提供有力的數(shù)據(jù)支撐。 為了驗證Hadoop容錯能力評測方法的可行性，本文使用Hadoop搭建了一個小型的云計算平臺環(huán)境進(jìn)行實驗。軟件健壯性測試發(fā)現(xiàn)了Hadoop接口和實現(xiàn)中存在的不足并進(jìn)行了缺陷定位。在測試環(huán)境中進(jìn)行的節(jié)點或進(jìn)程級失效故障、數(shù)據(jù)操作失效故障、數(shù)據(jù)校驗故障、資源過載故障和網(wǎng)絡(luò)故障的注入測試有效地證明了各個故障注入工具的有效性。通過結(jié)合Hadoop基準(zhǔn)性能測試程序進(jìn)行故障注入前后性能變化情況的對比，能夠?qū)adoop平臺的容錯能力進(jìn)行定性的評測。
[Abstract]:With the rapid growth of data in information systems, the traditional computing and storage mode can no longer meet the increasing demand for data processing and storage. Cloud computing technology developed on the basis of early distributed processing, parallel processing and grid computing technology has become a hot solution to mass data. However, with the popularization and popularization of cloud computing platform, reliability becomes a major difficulty and challenge. Fault-tolerant ability can reflect the reliability of the system from one level. Therefore, it is important to evaluate the fault tolerance of cloud computing platform. Due to the complexity of cloud computing platform and the large scale of software, it becomes a difficult task to evaluate the fault tolerance of cloud computing platform. At present, among the existing research results of cloud computing platform testing, the content of fault tolerance capability evaluation is less and the test method is relatively single, so it needs more in-depth research and improvement. The test method based on fault injection is the most effective method to evaluate fault tolerance. In this paper, the open source cloud computing platform-Hadoop is taken as the research goal, and the fault-tolerant mechanism of core components in Hadoop is deeply studied. Based on the possible fault types in practical applications and the characteristics of deployment structure and running mechanism of Hadoop platform, a multi-level Hadoop fault-tolerant capability testing framework is proposed. From the four levels of software robustness test MapReduce fault injection test network fault injection test and HDFS fault injection test several software and hardware anomalies in cloud computing platform are simulated respectively. According to the testing framework of Hadoop multi-level fault-tolerant capability, a fault tolerance evaluation platform for Hadoop is designed, and many kinds of fault injection tools are realized. The software robustness test of Hadoop and the possible node faults and network failures are formed. Hard disk failure and other types of fault tolerance test coverage. In the process of fault injection, the feedback information of cloud computing platform is monitored and recycled, and the result analysis is carried out in order to provide the researchers with real and reliable evaluation results. Finally, it provides powerful data support for fault tolerance evaluation of cloud computing platform. In order to verify the feasibility of Hadoop fault-tolerant capability evaluation method, this paper uses Hadoop to build a small cloud computing platform environment for experiments. Software robustness test found the shortcomings of Hadoop interface and implementation, and carried out defect location. The injection tests of node or process level failure, data operation failure, data check fault, resource overload fault and network fault in the test environment effectively prove the effectiveness of each fault injection tool. The fault tolerance of Hadoop platform can be evaluated qualitatively by comparing the performance changes before and after fault injection with Hadoop benchmark performance test program.
【學(xué)位授予單位】：哈爾濱工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP302.8

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