本文選題：云 + 多層應(yīng)用�。� 參考：《山東大學(xué)》2014年碩士論文

【摘要】：云計(jì)算以其高可伸縮、高可靠、按需付費(fèi)等特征,被業(yè)界廣泛接受。越來越多的大型網(wǎng)絡(luò)應(yīng)用向云中遷移,開始以服務(wù)的形式供人使用。交付到云中的網(wǎng)絡(luò)應(yīng)用可以基于云資源按需地自適應(yīng)伸縮,保證系統(tǒng)性能的同時(shí)大大減少了成本,提高了資源利用率。云中的服務(wù)提供問題是網(wǎng)絡(luò)應(yīng)用向云中交付的關(guān)鍵技術(shù),所謂云中的服務(wù)提供(Service Provisioning)是指ISV(Independent Software Vendors,獨(dú)立軟件開發(fā)商)將開發(fā)好的應(yīng)用交付到云中PaaS(Platform as a Service,平臺即服務(wù))平臺,PaaS平臺根據(jù)應(yīng)用的負(fù)載和性能需求,將資源按需提供給應(yīng)用,同時(shí)保證系統(tǒng)在運(yùn)行時(shí)的動(dòng)態(tài)按需擴(kuò)展的過程。 云中的網(wǎng)絡(luò)應(yīng)用一般為多層應(yīng)用,如電子商務(wù)應(yīng)用、社交網(wǎng)絡(luò)應(yīng)用等。多層應(yīng)用是指應(yīng)用分為Web層、應(yīng)用服務(wù)層和數(shù)據(jù)庫層等。云中多層應(yīng)用的服務(wù)提供問題相比一般應(yīng)用的服務(wù)提供問題要復(fù)雜的多,傳統(tǒng)的云資源分配方法已不再適用,面臨諸多挑戰(zhàn)： 1、多層應(yīng)用各層之間的依賴復(fù)雜性和服務(wù)特征差異復(fù)雜性。多層應(yīng)用各層之間的依賴復(fù)雜性是指多層應(yīng)用各層之間是相互影響的,一方面影響到達(dá)各層的負(fù)載量,另一方面影響各層的負(fù)載到達(dá)規(guī)律,使多層應(yīng)用各層負(fù)載情況更復(fù)雜,更難預(yù)測；多層應(yīng)用各層服務(wù)特征的差異復(fù)雜性是指多層應(yīng)用的各層承載的服務(wù)功能不同,服務(wù)時(shí)間等不同。 2、云資源處理能力的復(fù)雜性和多層多類混合資源的組合復(fù)雜性。多層應(yīng)用各層之間的依賴復(fù)雜性和服務(wù)特征的差異復(fù)雜性導(dǎo)致了資源處理能力的復(fù)雜性,即同類資源單位時(shí)間內(nèi)能夠有效處理的請求個(gè)數(shù)與每層應(yīng)用的負(fù)載分布和服務(wù)特征相關(guān),變得異常復(fù)雜；多層多類混合資源的組合復(fù)雜性是指不同的資源提供給各層的處理能力不同,對多層應(yīng)用進(jìn)行服務(wù)提供,存在多種資源的多種組合,如何選擇一個(gè)合適的資源組合,使得在滿足用戶SLA要求下,實(shí)現(xiàn)服務(wù)質(zhì)量和資源代價(jià)兩個(gè)矛盾目標(biāo)的均衡,是個(gè)技術(shù)難題。 為此,’本文針對云中多層應(yīng)用服務(wù)提供問題面臨的挑戰(zhàn),主要研究了： 1、構(gòu)建在線監(jiān)控架構(gòu),對多層應(yīng)用的每層負(fù)載分布進(jìn)行監(jiān)測,并提出基于自回歸模型的預(yù)測方法對應(yīng)用負(fù)載進(jìn)行預(yù)測,解決了多層應(yīng)用各層之間的依賴復(fù)雜性問題；對每層服務(wù)特征進(jìn)行監(jiān)測,解決了多層應(yīng)用各層之間的服務(wù)特征差異復(fù)雜性問題。 2、應(yīng)用排隊(duì)論對部署多層應(yīng)用各層的資源進(jìn)行建模,求解資源對各層應(yīng)用的處理能力,解決了資源處理能力的復(fù)雜性問題；提出基于性能-代價(jià)均衡的多目標(biāo)優(yōu)化算法,應(yīng)用帕累托最優(yōu)思想,求得服務(wù)質(zhì)量和資源代價(jià)均較優(yōu)的服務(wù)提供策略,解決多層多類混合資源的組合復(fù)雜性問題。 本文使用多層應(yīng)用基準(zhǔn)測試RUBiS進(jìn)行實(shí)驗(yàn),通過大量實(shí)驗(yàn)數(shù)據(jù)驗(yàn)證本文提出的方法�；诓杉腞UBiS運(yùn)行數(shù)據(jù),對負(fù)載進(jìn)行預(yù)測,并將實(shí)際運(yùn)行數(shù)據(jù)與本文提出的預(yù)測方法預(yù)測的負(fù)載進(jìn)行比較。實(shí)驗(yàn)結(jié)果顯示,本文的負(fù)載預(yù)測方法與實(shí)際負(fù)載誤差較小,預(yù)測方法具有較好的性能。另一方面,通過實(shí)驗(yàn),將本文提出的服務(wù)提供策略與隨機(jī)策略、貪婪策略從服務(wù)提供方案所對應(yīng)的總體性能、資源代價(jià)等多個(gè)角度進(jìn)行比較分析。實(shí)驗(yàn)結(jié)果顯示,與同類服務(wù)提供策略相比,本文所提出的基于性能-代價(jià)均衡的多目標(biāo)優(yōu)化服務(wù)提供策略具有較好的綜合性能,服務(wù)質(zhì)量和資源代價(jià)均較優(yōu)。本文的研究成果為更好地提高云基礎(chǔ)資源的利用率和精確的服務(wù)提供方法提供基礎(chǔ),具有較高的實(shí)用價(jià)值與廣闊的應(yīng)用前景。
[Abstract]:Cloud computing is widely accepted by the industry because of its high scalability, high reliability and payment by demand. More and more large network applications have migrated to the cloud and started to use in the form of service. The network applications delivered to the cloud can be based on the adaptive scalability of the cloud resources, ensure the performance of the system and greatly reduce the cost and increase the cost. Resource utilization. Service delivery in the cloud is a key technology for network applications to deliver to the cloud. The so-called Service Provisioning is the ISV (Independent Software Vendors, independent software developer) that delivers the developed applications to the cloud PaaS (Platform as a Service, platform and service) platform, PaaS platform According to the application's load and performance requirements, the resources are provided to the application on demand, while ensuring the system's dynamic and on-demand expansion process at runtime.
The network application in the cloud is generally used as multi-layer applications, such as e-commerce applications, social network applications, etc. multi-layer applications refer to applications divided into Web layer, application service layer and database layer. The service provision problem of multi-layer applications in cloud is much more complicated than general application services, and the traditional method of cloud resource allocation is no longer applicable. Facing many challenges:
1, the complexity of dependency complexity and the complexity of service characteristics between layers. The dependence complexity between layers of multilayer applications refers to the interaction between layers of multilayer applications. On the one hand, it affects the load of each layer. On the other hand, it affects the load of each layer to the rules, making the load situation more complex and more complex and more complex. It is difficult to predict; the difference and complexity of the service characteristics of different levels of multi-layer application is that the service functions of different layers of multi-layer application are different, and the service time is different.
2, the complexity of cloud resource processing capability and the complexity of multi-layer and multi class mixed resources. The complexity of dependency complexity and the difference complexity of service characteristics between layers of multilayer applications lead to the complexity of resource processing capability, that is, the number of requests and the load distribution and service of each application in the same resource unit time. The combination of multi-layer and multi class mixed resources is that different resources provide different processing capabilities for each layer, provide services to multi-layer applications, have multiple combinations of various resources, and choose a suitable resource combination to meet the user's SLA requirements and achieve the quality of service and the realization of the quality of service. The balance between the two conflicting objectives of resource cost is a technical problem.
For this reason, this paper focuses on the challenges faced by multi-layer application services in cloud computing.
1, the online monitoring architecture is constructed to monitor the load distribution in each layer of multi-layer applications, and the prediction method based on autoregressive model is proposed to predict the application load, and the dependency complexity between layers of multilayer applications is solved. The service characteristics of each layer are monitored and the difference of service characteristics between layers of multi layer applications is solved. Complexity problem.
2, using queuing theory to model the resources of each layer of deployment of multilayer applications, solving the processing ability of resources to each layer, and solving the complexity of resource processing capability. A multi-objective optimization algorithm based on performance cost equilibrium is proposed, and the Pareto optimal idea is applied to obtain services which are both superior in service quality and resource cost. Strategy to solve the combinatorial complexity problem of multi tier and multi class mixed resources.
In this paper, the experiment is carried out using a multi-layer application datum test RUBiS, and a large amount of experimental data is used to verify the proposed method. Based on the running data of the collected RUBiS, the load is predicted and the actual running data is compared with the predicted load predicted by the prediction method proposed in this paper. The experimental results show that the load forecasting method and the actual situation of this paper are based on the experiment results. The load error is small, and the prediction method has good performance. On the other hand, through the experiment, the service provision strategy and random strategy proposed in this paper, greedy strategy from the overall performance of the service provision and the resource cost are compared and analyzed. The proposed multi objective optimization service based on performance cost equilibrium provides better comprehensive performance and better service quality and resource cost. The research results of this paper provide the basis for improving the utilization rate of cloud base resources and the accurate service provision method, which has high practical value and broad application prospects.
【學(xué)位授予單位】：山東大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.09

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本文編號：2107973