本文選題：云計(jì)算 + 宿主機(jī)選擇�。� 參考：《吉林大學(xué)》2016年碩士論文

【摘要】：近幾年,云計(jì)算概念越來(lái)越熱,云,是一種全新的服務(wù)模式,云平臺(tái)通過(guò)網(wǎng)絡(luò)和虛擬化技術(shù)對(duì)基礎(chǔ)硬件進(jìn)行整合,使用戶脫離了對(duì)IT設(shè)施及平臺(tái)的管理,將更多的精力放到業(yè)務(wù)邏輯上,同時(shí)還提高了計(jì)算資源的使用率,一改以往傳統(tǒng)IT的服務(wù)方式,讓IT服務(wù)從使用到維護(hù)均跨越了時(shí)空的限制。IT領(lǐng)域的每一次變革勢(shì)必會(huì)波及到金融領(lǐng)域,云計(jì)算給金融領(lǐng)域帶來(lái)了新的發(fā)展契機(jī)和新的需求。各家金融機(jī)構(gòu)紛紛利用云計(jì)算這個(gè)平臺(tái)對(duì)大數(shù)據(jù)中心進(jìn)行升級(jí)改造,以拓展新的業(yè)務(wù)領(lǐng)域,優(yōu)化管理工作。這就對(duì)云計(jì)算提出了更高的要求,不僅要求保證金融業(yè)務(wù)和數(shù)據(jù)的安全性,同時(shí)要求技術(shù)力量具有高的可靠性。一個(gè)好的云架構(gòu)應(yīng)該為金融業(yè)務(wù)提供充分的可靠性和安全性。云計(jì)算服務(wù)是建立在部署于宿主機(jī)機(jī)群上的虛擬資源上的。傳統(tǒng)的虛擬機(jī)部署工作通常單一地依據(jù)宿主機(jī)當(dāng)前CPU狀況來(lái)作為目標(biāo)宿主,宿主機(jī)其他的資源狀況未作為部署參數(shù)考慮進(jìn)來(lái),同時(shí)也忽略了虛擬機(jī)所要消耗的資源特點(diǎn)。不同用戶完成的業(yè)務(wù)目標(biāo)不同,因此提出的資源請(qǐng)求也具有不同特點(diǎn)。單純地依靠宿主機(jī)CPU這一指標(biāo)作為部署依據(jù),可能導(dǎo)致宿主機(jī)不能滿足用戶的IT資源請(qǐng)求,隨著云平臺(tái)的用戶增加,進(jìn)而可能影響整個(gè)云平臺(tái)的負(fù)載均衡,導(dǎo)致IT資源得不到有效合理的利用。因此,宿主機(jī)的選擇、虛擬資源的部署對(duì)于云計(jì)算提供優(yōu)質(zhì)的服務(wù)有至關(guān)重要的作用。本文提出了基于個(gè)性化需求的宿主機(jī)選擇模型,該模型將用戶的資源請(qǐng)求量化,再根據(jù)云中宿主機(jī)的性能情況與量化結(jié)果進(jìn)行比對(duì),選擇最適合用戶的宿主機(jī)予以部署虛擬資源。同時(shí)還對(duì)該模型中涉及的負(fù)載預(yù)測(cè)機(jī)制、負(fù)載均衡機(jī)制均進(jìn)行了深入的研究,并提出了適合該模型的負(fù)載預(yù)測(cè)機(jī)制和負(fù)載均衡機(jī)制。通過(guò)實(shí)驗(yàn)驗(yàn)證:與傳統(tǒng)的宿主機(jī)選擇方法相比,該模型在充分滿足用戶個(gè)性化需求的前提下,在降低虛擬機(jī)遷移頻率、均衡云平臺(tái)的負(fù)載,保證系統(tǒng)穩(wěn)定性方面有明顯提高。
[Abstract]:In recent years, cloud computing concept is becoming more and more hot, cloud is a new service model, cloud platform through network and virtualization technology to integrate the basic hardware, so that users out of the management of IT facilities and platforms, By focusing more on business logic and increasing the utilization rate of computing resources, we have changed the traditional IT service style. Every revolution in IT field will inevitably spread to the financial field. Cloud computing has brought new development opportunities and new needs to the financial field. Financial institutions use cloud computing as a platform to upgrade and upgrade the big data Center to expand new areas of business and optimize management. This puts forward higher requirements for cloud computing, not only to ensure the security of financial services and data, but also to require high reliability of technical forces. A good cloud architecture should provide adequate reliability and security for financial operations. Cloud computing services are built on virtual resources deployed on a host cluster. The traditional virtual machine deployment is usually based solely on the current CPU status of the host as the target host. The other resource conditions of the host are not considered as deployment parameters and the characteristics of the resources consumed by the virtual machine are ignored. Different users accomplish different business objectives, so the resource request has different characteristics. Relying solely on the host CPU as the basis for deployment may result in the host being unable to meet the user's IT resource requests. As the number of users on the cloud platform increases, it may affect the load balance of the entire cloud platform. As a result, IT resources can not be used effectively and reasonably. Therefore, the choice of host and the deployment of virtual resources are very important for cloud computing to provide high quality services. In this paper, a host selection model based on personalized requirements is proposed. The model quantifies users' resource requests, and then compares them with the quantization results according to the performance of the host in the cloud. Select the most suitable host for the user to deploy the virtual resource. At the same time, the load forecasting mechanism and load balancing mechanism involved in the model are deeply studied, and the load forecasting mechanism and load balancing mechanism suitable for the model are proposed. The experimental results show that compared with the traditional host selection method, the model can reduce the migration frequency of virtual machine, balance the load of cloud platform, and ensure the stability of the system.
【學(xué)位授予單位】：吉林大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TP393.09

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本文編號(hào)：2112647