【摘要】：云計(jì)算(Cloud Computing)是以服務(wù)概念為主的新型計(jì)算方式,利用現(xiàn)有的強(qiáng)大網(wǎng)絡(luò)、計(jì)算和存儲(chǔ)資源提供計(jì)算、存儲(chǔ)和平臺(tái)服務(wù),并具有良好的可擴(kuò)充性和穩(wěn)定性。云計(jì)算平臺(tái)具有虛擬性、層次性以及動(dòng)態(tài)性等特點(diǎn),比傳統(tǒng)的分布式計(jì)算(Distributed Computing)更加復(fù)雜。因此,資源監(jiān)控是云計(jì)算平臺(tái)的重要組成部分,其對(duì)提高云計(jì)算平臺(tái)的服務(wù)質(zhì)量發(fā)揮重要作用,研究云計(jì)算環(huán)境下監(jiān)控方法具有重要的意義。 目前云環(huán)境下的監(jiān)控系統(tǒng)存在著如下問(wèn)題：(1)監(jiān)控對(duì)象有局限性,往往只關(guān)注云平臺(tái)的某一層次的資源或服務(wù),不能為系統(tǒng)較為提供全面的監(jiān)控。(2)現(xiàn)有的一些監(jiān)控框架不具有通用性,針對(duì)某些特定的云平臺(tái)效果不錯(cuò),但是不能適合用于其他云平臺(tái)。(3)資源監(jiān)控系統(tǒng)中的數(shù)據(jù)傳輸算法雖然采用了混合推拉算法,但是其效率還可以進(jìn)步的提高,從而進(jìn)一步減少對(duì)系統(tǒng)的影響。 本文主要做了如下工作,來(lái)解決上述問(wèn)題： 本文對(duì)云環(huán)境下的資源監(jiān)控進(jìn)行了深入的研究,抽象了資源監(jiān)控系統(tǒng)的模型,明確了建立面向服務(wù)的資源監(jiān)控,詳細(xì)討論了監(jiān)控服務(wù)的系統(tǒng)結(jié)構(gòu)。 其次,針對(duì)資源監(jiān)控系統(tǒng)采集數(shù)據(jù)細(xì)節(jié)進(jìn)行了研究,對(duì)云服務(wù)的層次和能耗做了分析,提出了較為詳細(xì)的數(shù)據(jù)采集指標(biāo)和監(jiān)控代理的設(shè)計(jì)。 然后,進(jìn)一步深入研究了當(dāng)前比較流行的混合推拉模式,指出了其中存在的問(wèn)題,并對(duì)問(wèn)題給出了解決方案。為了驗(yàn)證設(shè)計(jì)方案的效果,提出了四個(gè)對(duì)比指標(biāo),以此為依據(jù)進(jìn)行算法的對(duì)比。通過(guò)分析多組實(shí)驗(yàn)的結(jié)果驗(yàn)證了改進(jìn)方案的有效性。 最后,研究了數(shù)據(jù)的處理,闡述了資源監(jiān)控系統(tǒng)對(duì)數(shù)據(jù)處理的過(guò)程,在此基礎(chǔ)上提出了數(shù)據(jù)處理組件的結(jié)構(gòu)。
[Abstract]:Cloud computing (Cloud Computing) is a new computing method based on the concept of service. Using the existing powerful network, computing and storage resources provide computing, storage and platform services, and it has good scalability and stability. Cloud computing platform is more complex than traditional distributed computing (Distributed Computing) because of its virtual, hierarchical and dynamic characteristics. Therefore, resource monitoring is an important part of cloud computing platform, which plays an important role in improving the quality of service of cloud computing platform. At present, the following problems exist in the monitoring system in the cloud environment: (1) the monitoring objects have limitations, and they usually only pay attention to the resources or services at a certain level of the cloud platform. Can not provide more comprehensive monitoring for the system. (2) some of the existing monitoring framework is not universal, for some specific cloud platform effect is good, But it is not suitable for other cloud platforms. (3) although the hybrid push-pull algorithm is used in the resource monitoring system, its efficiency can be improved, thus further reducing the impact on the system. This paper mainly does the following work to solve the above problems: this paper has carried on the thorough research to the resources monitoring under the cloud environment, has abstracted the resources monitoring system model, has clearly established the service-oriented resources monitoring, The system structure of monitoring service is discussed in detail. Secondly, the details of data collection in resource monitoring system are studied, the level of cloud service and energy consumption are analyzed, and the detailed data acquisition index and the design of monitoring agent are put forward. Then, the current popular hybrid push-pull model is further studied, the existing problems are pointed out, and the solutions to the problems are given. In order to verify the effect of the design, four contrasting indexes are put forward, based on which the algorithm is compared. The effectiveness of the improved scheme is verified by analyzing the results of multi-group experiments. Finally, the processing of data is studied, and the process of data processing in resource monitoring system is expounded. On the basis of this, the structure of data processing component is put forward.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.09

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本文編號(hào)：2150449