本文選題：云計(jì)算 + 資源優(yōu)化　； 參考：《西北大學(xué)》2014年碩士論文

【摘要】：云計(jì)算毫無疑問已經(jīng)成為當(dāng)前IT業(yè)界最為重要且熱門的主題,它為傳統(tǒng)IT資源的管理和使用方式帶來了革命性的創(chuàng)新。隨著云用戶的日益增加,如何使云數(shù)據(jù)中心的虛擬化資源在實(shí)現(xiàn)容災(zāi)的基礎(chǔ)上,刪除冗余數(shù)據(jù),從整個(gè)數(shù)據(jù)中心來講減少云用戶的等待時(shí)間,同時(shí)還能提高計(jì)算資源的利用率,讓整個(gè)云數(shù)據(jù)中心的資源得到充分均衡地利用。這已經(jīng)成為當(dāng)前最重要也最受關(guān)注的云計(jì)算環(huán)境中資源調(diào)度問題之一。 本論文主要研究IaaS云平臺中的數(shù)據(jù)中心虛擬化計(jì)算資源的動(dòng)態(tài)分配與調(diào)度策略,以目前最主流的開源IaaS云平臺OpenStack為依托,在前人工作的基礎(chǔ)之上展開如下研究工作： (1)分析了當(dāng)前云計(jì)算技術(shù)的發(fā)展背景和研究意義以及國內(nèi)外對云計(jì)算技術(shù)研究的現(xiàn)狀,并對云計(jì)算的定義、基本特征、服務(wù)類型做了詳細(xì)的介紹。對OpenStack資源調(diào)度機(jī)制包括資源調(diào)度模塊、資源調(diào)度過程進(jìn)行了分析研究。 (2)基于OpenStack對IaaS云平臺的虛擬化計(jì)算資源進(jìn)行量化。提出并設(shè)計(jì)了在OpenStack云平臺上計(jì)算資源的調(diào)度算法,包括CPU密集型、內(nèi)存密集型等調(diào)度算法和實(shí)時(shí)反饋的綜合負(fù)載均衡資源優(yōu)化策略。同時(shí)闡述了實(shí)時(shí)反饋的綜合負(fù)載均衡資源優(yōu)化策略的主要API的Python定義和保存該策略運(yùn)行時(shí)信息的XML文件的定義。 (3)通過分析開源IaaS云平臺OpenStack的資源調(diào)度機(jī)制,提出一種基于OpenStack的可擴(kuò)展的多資源池分布式資源調(diào)度框架,該框架將物理主機(jī)劃分成多個(gè)邏輯資源池,在全局上針對各個(gè)資源池設(shè)定全局資源優(yōu)化策略,在每一個(gè)資源池本身設(shè)定局部的資源優(yōu)化策略。實(shí)驗(yàn)結(jié)果表明,本文提出的多資源池分布式資源調(diào)度框架很好地實(shí)現(xiàn)了OpenStack的資源優(yōu)化,并在提高資源利用率的同時(shí)實(shí)現(xiàn)了性能隔離與安全隔離,具有良好的擴(kuò)展性。
[Abstract]:Cloud computing has undoubtedly become the most important and hot topic in the current IT industry. It has brought revolutionary innovations for the management and use of traditional IT resources. With the increasing number of cloud users, how to make the virtualized resources of the cloud data center on the basis of disaster recovery and delete redundant data from the whole data center. Reducing the waiting time for cloud users can also improve the utilization of computing resources and make full use of the resources of the whole cloud data center. This has become one of the most important and most concerned cloud computing environment resource scheduling problems.
This paper mainly studies the dynamic allocation and scheduling strategy of the data center virtual computing resources in the IaaS cloud platform. Based on the most mainstream open source IaaS cloud platform OpenStack, the following research work is carried out on the basis of the predecessors' work:
(1) the background and significance of the current cloud computing technology and the status of the research on cloud computing technology at home and abroad are analyzed, and the definition, basic features and service types of cloud computing are introduced in detail. The OpenStack resource scheduling mechanism, including the resource scheduling module and the resource scheduling process, is analyzed and studied.
(2) quantifying the virtual computing resources of IaaS cloud platform based on OpenStack. A scheduling algorithm for computing resources on the OpenStack cloud platform is proposed and designed, including CPU intensive, memory intensive scheduling algorithms and real-time feedback integrated load balancing resource optimization strategies. Meanwhile, the real-time feedback integrated load balancing resource is described. The Python definition of the main API of the optimization strategy and the definition of the XML file for saving the runtime information of the policy.
(3) by analyzing the resource scheduling mechanism of the open source IaaS cloud platform OpenStack, a scalable multi resource pool distributed resource scheduling framework based on OpenStack is proposed. The framework divides the physical host into multiple logical resource pools, setting the whole Bureau resource optimization strategy for each resource pool on the global scale, and setting up each resource pool itself. The experimental results show that the multi resource pool distributed resource scheduling framework proposed in this paper has well implemented the resource optimization of OpenStack, and achieves performance isolation and security isolation at the same time of improving resource utilization, and has good scalability.

【學(xué)位授予單位】：西北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TP393.01

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