本文關(guān)鍵詞： 云計(jì)算 資源管理 應(yīng)用可用性 資源整合 資源安置　出處：《上海交通大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：本文旨在研究云計(jì)算環(huán)境中多約束情況下的虛擬資源調(diào)度管理問題。多約束一方面是指來(lái)自用戶的質(zhì)量屬性約束，比如對(duì)響應(yīng)時(shí)間和吞吐量等性能要求和對(duì)部署在云平臺(tái)上應(yīng)用的可用性要求。這些用戶約束是以SLA的形式，由用戶向云服務(wù)提供商提出的。另一方面，多約束是指來(lái)自云服務(wù)提供商的約束，主要是指減少包括能源開銷在內(nèi)的運(yùn)營(yíng)成本的約束。在運(yùn)行和維護(hù)云平臺(tái)時(shí)，云服務(wù)提供商總是力求減少能耗來(lái)降低成本，提高利潤(rùn)。云平臺(tái)中資源的供給和部署需要在滿足用戶約束和降低云服務(wù)提供商的運(yùn)營(yíng)成本之間進(jìn)行平衡。為云用戶提供更多的虛擬資源可以確保云應(yīng)用的性能和可用性等需求得到滿足，但是會(huì)增加云服務(wù)提供商的運(yùn)營(yíng)成本；反之，如果為云用戶提供較少的虛擬資源，盡管可以有效減低云服務(wù)提供商的運(yùn)營(yíng)成本，但是可能會(huì)導(dǎo)致云應(yīng)用響應(yīng)時(shí)間過(guò)長(zhǎng)和可用性過(guò)低等情況。因此，如何提供、安置和整合云平臺(tái)上的虛擬資源滿足不同利益共享者的約束成為了云服務(wù)用戶和云服務(wù)提供商兩方面共同關(guān)注的話題。 因而，本文提出了一種約束分離的云資源管理框架——通過(guò)分離云應(yīng)用和云服務(wù)提供商不同的需求關(guān)注點(diǎn)，在不同層次上滿足他們各自的需求。我們將云資源的管理分為應(yīng)用層和平臺(tái)層上的資源管理。其中，質(zhì)量屬性需求到虛擬資源的映射被抽象成應(yīng)用控制器。在應(yīng)用控制器中，用戶對(duì)性能屬性的要求被轉(zhuǎn)化為虛擬資源的數(shù)量，將可用性需求轉(zhuǎn)化為虛擬資源位置的部署方案。在平臺(tái)層的管理框架中，采用整合策略，使得虛擬資源盡可能地運(yùn)行在較少的物理服務(wù)器上，以達(dá)到減少運(yùn)行的物理機(jī)數(shù)量從而節(jié)約能源和成本的目的。 在應(yīng)用層的資源管理模塊中，，本文提出了一種計(jì)算部署在云平臺(tái)上的應(yīng)用可用性的計(jì)算模型，以及一種動(dòng)態(tài)虛擬資源安置算法。它們?cè)谧畲蟪潭壬蠞M足了用戶的應(yīng)用可用性需求，同時(shí)也減少了分散部署虛擬資源帶來(lái)的通訊開銷。資源安置算法綜合使用了兩種伸縮策略：水平伸縮和垂直伸縮。垂直伸縮策略是指改變虛擬機(jī)內(nèi)部持有的資源數(shù)量，而水平伸縮策略是指改變虛擬機(jī)實(shí)例的數(shù)量。由于這兩種策略對(duì)應(yīng)用可用性、通訊開銷和軟件版本開銷的影響不盡相同，我們根據(jù)應(yīng)用當(dāng)前的可用性和用戶約束中規(guī)定的可用性的差值來(lái)選擇執(zhí)行哪種策略。 在平臺(tái)層的資源管理模塊中，本文也給出了一種改進(jìn)的資源整合方案。該方案將資源的整合分為反應(yīng)式資源整合模塊和周期性資源整合模塊。反應(yīng)式資源整合模塊自治地運(yùn)行在每一臺(tái)物理服務(wù)器內(nèi)部，根據(jù)監(jiān)測(cè)是否有異常情況，決定是否進(jìn)行資源整合。異常情況包括超過(guò)預(yù)定資源利用率上限的負(fù)載過(guò)度情況，和低于預(yù)定資源利用率下限的負(fù)載不足情況。針對(duì)這兩種情況本文給出了不同的算法來(lái)制定資源整合方案。周期性資源整合模塊，作為反應(yīng)式資源整合的補(bǔ)充，周期性地在可用性區(qū)域內(nèi)進(jìn)行所有虛擬資源的整合。 最后為了驗(yàn)證這兩種策略—可用性感知的動(dòng)態(tài)資源安置模塊和資源整合模塊的正確性和有效性，本文模擬真實(shí)云環(huán)境的架構(gòu)，設(shè)計(jì)并實(shí)現(xiàn)了兩個(gè)實(shí)驗(yàn)。在實(shí)驗(yàn)一中通過(guò)模擬兩種典型場(chǎng)景——擴(kuò)容和減容的應(yīng)用，對(duì)比了水平伸縮策略、垂直伸縮策略和本文提出的可用性感知策略在可用性滿足率、平均應(yīng)用可用性、通訊開銷和軟件版本開銷上的表現(xiàn)。實(shí)驗(yàn)二通過(guò)模擬一個(gè)可用性區(qū)域中多臺(tái)物理服務(wù)器和多臺(tái)多種粒度的虛擬機(jī)，來(lái)驗(yàn)證改進(jìn)的資源整合方案的有效性。實(shí)驗(yàn)結(jié)果表明，本文中提出的算法減少了整合活動(dòng)帶來(lái)的遷移成本，是一個(gè)實(shí)際具有應(yīng)用價(jià)值的有效策略。 本文的主要貢獻(xiàn)在于從不同利益共享者的角度對(duì)多約束資源管理框架的構(gòu)建進(jìn)行了初步的探索。將來(lái)自不同利益共享者的約束分離開來(lái)，在不同層次上予以滿足。其中，重點(diǎn)關(guān)注了應(yīng)用層上的可用性約束的滿足和云平臺(tái)層上的節(jié)能約束的滿足，從而達(dá)到云資源使用者和云資源管理者共贏的目的。
[Abstract]:Virtual resource scheduling management problems, this paper aims to study the cloud computing environment with multiple constraints under multiple constraints. One refers to the quality attribute constraints from users, such as response time and throughput performance requirements and deployment of applications on the cloud platform availability requirements. These user constraints are in the form of SLA, proposed by user Xiang Yun service provider. On the other hand, multi constraint refers to from the cloud service provider constraints, mainly refers to reduce energy costs, including operating cost constraints. In the operation and maintenance of the cloud platform, cloud service providers always strive to reduce energy consumption to reduce costs and increase profits. Supply and deployment of resources in the cloud platform the need to balance to meet user constraints and reduce operating costs between cloud service providers. To provide more virtual resources can ensure the performance of cloud applications for cloud users And availability requirements are met, but will increase the cloud service provider operating costs; on the other hand, if the virtual resources provide less for cloud users, although cloud service providers can effectively reduce operating costs, but may lead to a cloud application response time and availability low. Therefore, how to provide, placement and the integration of virtual resources in the cloud to meet the needs of different stakeholders constraints has become a common concern of the two users of cloud services and cloud service providers of the topic.
Therefore, this paper proposes a constraint separation cloud resource management framework, through the separation of cloud applications and cloud service providers to the needs of different concerns, meet their needs at different levels. We will cloud resources into the management of resource management and application layer platform layer. The quality attribute requirements to map virtual resources are abstracted into application controller. In the application of the controller, the user requirements on the performance of property is converted to a virtual number of resources, the availability requirements are mapped into the virtual resource deployment scheme. The position of the platform layer management framework, the integration strategy of the virtual resources as much as possible running on a physical server less, in order to reduce the number of physical machines running so as to save energy and cost.
In resource management module of application layer, this paper presents the calculation model of application availability of a computing deployment in the cloud on the platform, and a dynamic virtual resource placement algorithm. They satisfy the user application usability requirements in the greatest degree, but also reduce the dispersion of the deployment of virtual resources bring communication overhead the integrated use of resources. For algorithm two expansion strategy: horizontal expansion and vertical expansion. The vertical expansion strategy refers to the change of internal resources held by the number of virtual machines, and the horizontal expansion strategy refers to changes in the number of virtual machine instances. By the two strategies of application usability, effects of communication overhead and software version overhead we are not the same, according to the provisions of the current application of usability and user constraints in the availability of the difference to choose what kind of strategy implementation.
In resource management module in the platform layer, an improved resource integration scheme is also given in this paper. The program will be the integration of resources divided into resource integration module and periodic resource integration module. The reactive resource integration module run autonomously on each physical server, according to whether there is abnormal situation monitoring and decide whether the integration of resources. Exceptions include more than the upper limit of the excessive load rate using a predetermined resource, and the shortage of the lower limit of the rate is lower than the load using a predetermined resource. In the light of the two cases presented different algorithms to develop resource integration scheme. The periodic resource integration module, as a complementary of the reactive periodically, the integration of all virtual resources in availability in the region.
Finally in order to verify these two strategies - availability aware dynamic resource placement module and resource integration module is correct and effective, this paper simulates the real cloud environment architecture, design and implementation of the two experiments. Through the simulation of two typical scenarios -- the application of dilatancy and volume reduction in Experiment 1, the level of contrast the expansion strategy, vertical expansion strategy and the availability of knowledge strategy in the availability rate, average application availability, communication overhead and software version overhead on performance. Experiment two through virtual machine simulation of a physical server availability zone and multiple granularities, to verify the effectiveness of resource integration the improved scheme. Experimental results show that the proposed algorithm reduces the cost of migration integration activities, is an effective strategy for the actual application value.
The main contribution of this paper is from different benefit sharing makes a preliminary exploration on the construction of multi constrained resource management framework "perspective. From the separation of the constraints of sharing different interests, to meet the requirements in different levels. Among them, the focus on energy constrained availability constraints on application layer content and cloud platform layer on the meeting, so as to achieve cloud resource users and cloud resource management and win-win goal.

【學(xué)位授予單位】：上海交通大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP3

【共引文獻(xiàn)】

相關(guān)期刊論文 前10條

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6 王加昌;曾輝;何騰蛟;張娜;;面向數(shù)據(jù)中心的虛擬機(jī)部署及優(yōu)化算法[J];計(jì)算機(jī)應(yīng)用;2013年10期

7 Claudia Canali;Riccardo Lancellotti;;Improving Scalability of Cloud Monitoring Through PCA-Based Clustering of Virtual Machines[J];Journal of Computer Science & Technology;2014年01期

8 錢育蓉;于炯;王衛(wèi)源;孫華;廖彬;楊興耀;;云計(jì)算環(huán)境下軟硬件節(jié)能和負(fù)載均衡策略[J];計(jì)算機(jī)應(yīng)用;2013年12期

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相關(guān)博士學(xué)位論文 前4條

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相關(guān)碩士學(xué)位論文 前10條

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3 陳靜怡;云環(huán)境下基于內(nèi)存共享的服務(wù)器整合算法研究[D];復(fù)旦大學(xué);2012年

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7 張飛飛;云環(huán)境中基于Map/Reduce的虛擬機(jī)調(diào)度策略研究[D];西安電子科技大學(xué);2013年

8 彭近堯;基于能效的數(shù)據(jù)中心資源整合機(jī)制[D];電子科技大學(xué);2013年

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本文編號(hào)：1480018