【摘要】：作為一種新興的技術(shù),云計(jì)算將IT基礎(chǔ)設(shè)施、平臺(tái)和軟件以服務(wù)的形式通過網(wǎng)絡(luò)以按需分配的方式對(duì)外提供。云計(jì)算通過虛擬化的方式將計(jì)算、存儲(chǔ)、網(wǎng)絡(luò)等資源構(gòu)建成統(tǒng)一的資源池,有效降低資源分配和管理的難度。如何高效、合理地管理資源池,實(shí)現(xiàn)云計(jì)算的動(dòng)態(tài)性、可伸縮性等特點(diǎn)顯得尤為重要。目前主流的云計(jì)算服務(wù)平臺(tái)如OpenStack、CloudStack等依賴人工配置方式實(shí)現(xiàn)資源管理。由于業(yè)務(wù)的資源需求規(guī)模和系統(tǒng)負(fù)載呈現(xiàn)周期性波動(dòng),用戶無法及時(shí)準(zhǔn)確地調(diào)整資源,導(dǎo)致出現(xiàn)業(yè)務(wù)運(yùn)行異常和資源浪費(fèi)等問題。針對(duì)這些問題,本論文提出了一種基于OpenStack的資源自適應(yīng)管理系統(tǒng)。該系統(tǒng)基于平臺(tái)資源的監(jiān)控?cái)?shù)據(jù)進(jìn)行智能分析和決策,動(dòng)態(tài)調(diào)整虛擬機(jī)資源。 本論文的主要研究工作分成了四個(gè)部分： 首先,設(shè)計(jì)了一個(gè)采用DSA (Disco very-Strategy-Action)思想的資源自適應(yīng)管理框架。該框架包括資源發(fā)現(xiàn)、資源調(diào)度決策和資源調(diào)整實(shí)施三個(gè)部分。資源發(fā)現(xiàn)部分負(fù)責(zé)監(jiān)測(cè)資源池的資源狀況和接收用戶資源請(qǐng)求信息。資源調(diào)度決策部分基于上述信息生成資源調(diào)整的操作指令。資源調(diào)整實(shí)施部分負(fù)責(zé)執(zhí)行操作指令。通過這三部分的協(xié)同工作,提高了系統(tǒng)響應(yīng)資源需求的實(shí)時(shí)性。 然后,設(shè)計(jì)實(shí)現(xiàn)了基于C/S架構(gòu)的資源監(jiān)控子系統(tǒng)。該子系統(tǒng)包括客戶端和服務(wù)端兩個(gè)模塊�？蛻舳四K完成對(duì)物理主機(jī)和虛擬機(jī)的CPU利用率、內(nèi)存等性能數(shù)據(jù)的周期性采集。服務(wù)端模塊負(fù)責(zé)匯總客戶端采集的監(jiān)控?cái)?shù)據(jù),完成數(shù)據(jù)持久化存儲(chǔ),并基于可配置的閡值檢測(cè)資源負(fù)載觸發(fā)告警。 接著,設(shè)計(jì)實(shí)現(xiàn)了資源管理決策子系統(tǒng)。該子系統(tǒng)負(fù)責(zé)處理資源負(fù)載告警和創(chuàng)建虛擬機(jī)請(qǐng)求。對(duì)于虛擬機(jī)資源告警,系統(tǒng)自動(dòng)統(tǒng)計(jì)歷史監(jiān)控?cái)?shù)據(jù),生成合理的資源調(diào)整決策,借助OpenStack提供的虛擬機(jī)配置調(diào)整和虛擬機(jī)遷移的接口完成資源的動(dòng)態(tài)調(diào)整。這樣有效減少了瞬時(shí)峰值引起的不必要調(diào)整。對(duì)于創(chuàng)建虛擬機(jī)的請(qǐng)求,采用貪心算法選擇合適的主機(jī)來放置新建虛擬機(jī)。該子系統(tǒng)在滿足自適應(yīng)業(yè)務(wù)資源需求的同時(shí)保證平臺(tái)資源利用最大化。 最后,本論文將資源監(jiān)控和管理決策兩個(gè)子系統(tǒng)的功能封裝成標(biāo)準(zhǔn)REST API。基于這些API和OpenStack服務(wù)接口,設(shè)計(jì)實(shí)現(xiàn)了云計(jì)算服務(wù)平臺(tái)的Web控制臺(tái)。該控制臺(tái)支持用戶定制虛擬機(jī)的資源監(jiān)控和自動(dòng)調(diào)整功能,可視化呈現(xiàn)虛擬機(jī)的監(jiān)控?cái)?shù)據(jù)等。 本論文對(duì)實(shí)現(xiàn)的云計(jì)算服務(wù)平臺(tái)資源管理系統(tǒng)進(jìn)行了實(shí)驗(yàn)和測(cè)試,并將實(shí)驗(yàn)室的多媒體會(huì)議系統(tǒng)運(yùn)行到平臺(tái)上以驗(yàn)證資源管理系統(tǒng)的有效性。實(shí)驗(yàn)結(jié)果表明,所提的資源管理系統(tǒng)能及時(shí)有效地適應(yīng)業(yè)務(wù)資源需求和系統(tǒng)負(fù)載的變化,實(shí)現(xiàn)了預(yù)期的功能需求。
[Abstract]:As an emerging technology, cloud computing provides IT infrastructure, platforms and software as services through the network and distributes them on demand. Cloud computing constructs computing, storage, network and other resources into a unified resource pool through virtualization, which effectively reduces the difficulty of resource allocation and management. It is very important to manage resource pool efficiently and reasonably to realize the dynamic and scalability of cloud computing. Current mainstream cloud computing service platforms such as OpenStack,CloudStack rely on manual configuration to achieve resource management. Due to the periodic fluctuation of resource demand scale and system load, users can not adjust resources accurately and timely, which leads to problems such as abnormal operation of business and waste of resources. To solve these problems, this paper proposes a resource adaptive management system based on OpenStack. The system makes intelligent analysis and decision based on monitoring data of platform resources and dynamically adjusts virtual machine resources. The main work of this thesis is divided into four parts: firstly, a resource adaptive management framework based on DSA (Disco very-Strategy-Action is designed. The framework includes three parts: resource discovery, resource scheduling decision and resource adjustment implementation. The resource discovery section is responsible for monitoring the resource status of the resource pool and receiving user resource request information. The resource scheduling decision part generates the operation instruction of resource adjustment based on the above information. The Resource Adjustment implementation is responsible for executing operational instructions. Through the collaborative work of the three parts, the real-time response of the system is improved. Then, the resource monitoring subsystem based on C / S architecture is designed and implemented. The subsystem includes two modules: client and server. The client module completes the periodic collection of CPU utilization, memory and other performance data of the physical host and virtual machine. The server module is responsible for collecting the monitoring data collected by the client, completing the data persistence storage, and detecting the resource load trigger alarm based on the configurable threshold value. Then, the resource management decision subsystem is designed and implemented. The subsystem is responsible for handling resource load alarms and creating virtual machine requests. For the virtual machine resource alarm, the system automatically statistics the historical monitoring data, generates reasonable resource adjustment decision, and completes the dynamic resource adjustment with the help of the virtual machine configuration adjustment and the virtual machine migration interface provided by OpenStack. This effectively reduces the unnecessary adjustment caused by the instantaneous peak. For the request of creating virtual machine, the greedy algorithm is used to select the appropriate host to place the new virtual machine. The subsystem not only meets the needs of adaptive business resources, but also ensures the maximum utilization of platform resources. Finally, the functions of resource monitoring and management decision subsystem are encapsulated into standard REST API.. Based on these API and OpenStack service interfaces, the Web console of cloud computing service platform is designed and implemented. The console supports resource monitoring and automatic adjustment of custom virtual machines, and visualizes monitoring data of virtual machines. In this paper, the resource management system of the cloud computing service platform is tested and tested, and the multimedia conference system of the laboratory is run on the platform to verify the effectiveness of the resource management system. The experimental results show that the proposed resource management system can effectively adapt to the changes of business resource requirements and system load and achieve the expected functional requirements.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TP393.07

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本文編號(hào)：2227569