本文選題：天線仿真云　切入點(diǎn)：OpenStack　出處：《天津工業(yè)大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著天線仿真技術(shù)的發(fā)展和智能天線的普及,高校、中小企業(yè)等研究機(jī)構(gòu)對計算機(jī)軟硬件等基礎(chǔ)設(shè)施的需求隨之快速增長,頻繁的設(shè)備更新和相對獨(dú)立的軟、硬件運(yùn)行模式,導(dǎo)致了天線仿真的成本逐年攀升。隨著云計算和虛擬化技術(shù)的興起,可以將天線仿真與云計算技術(shù)相結(jié)合,打破制約天線仿真技術(shù)發(fā)展的瓶頸。在高�；蛑行∑髽I(yè)建設(shè)實(shí)驗(yàn)室環(huán)境下的天線仿真云平臺,不僅能夠使計算機(jī)軟硬件資源得到合理利用,而且可以極大地方便科研人員的實(shí)踐活動,有效提升科研效率。本文首先介紹了幾種主流的IaaS云平臺,并選擇了被業(yè)界廣泛接受的OpenStack技術(shù)構(gòu)建了天線仿真云平臺,創(chuàng)建了天線仿真云平臺必備的仿真環(huán)境模板文件和云主機(jī)類型,為用戶提供了按需使用的仿真環(huán)境和計算機(jī)硬件的服務(wù);然后深入研究了 OpenStack的整體架構(gòu)和核心組件,結(jié)合OpenStack源碼,對OpenStack的初始虛擬機(jī)分配模塊、虛擬機(jī)動態(tài)遷移模塊進(jìn)行了深入地分析,闡述了其工作原理,并指出其中存在的不足之處;最后,針對OpenStack原生資源調(diào)度策略存在的缺陷,分別提出了多目標(biāo)蟻群優(yōu)化算法和虛擬機(jī)動態(tài)遷移多目標(biāo)優(yōu)化算法。利用多目標(biāo)蟻群優(yōu)化算法對虛擬機(jī)初始放置策略進(jìn)行改進(jìn),通過信息素的持續(xù)更新快速地獲取到最優(yōu)解,從而為新建的虛擬機(jī)找到最佳的放置位置。仿真結(jié)果表明,該算法既可以保證良好的服務(wù)性能,又能夠降低資源負(fù)載及電量損耗,確保數(shù)據(jù)中心達(dá)到一個良好的運(yùn)行狀態(tài)。利用虛擬機(jī)動態(tài)遷移多目標(biāo)優(yōu)化算法對OpenStack虛擬機(jī)的動態(tài)遷移策略進(jìn)行改進(jìn)。設(shè)計了二分上整延時法及時間預(yù)測法確定遷移時機(jī),利用多目標(biāo)優(yōu)化算法選取恰當(dāng)?shù)哪繕?biāo)物理主機(jī),設(shè)計了基于概率的選擇算法用以規(guī)避虛擬機(jī)的群聚效應(yīng)。CloudSim仿真結(jié)果表明,這一整套虛擬機(jī)資源動態(tài)調(diào)度方法能夠勝任對資源進(jìn)行實(shí)時調(diào)度的工作,同時能夠優(yōu)化數(shù)據(jù)中心的性能。
[Abstract]:With the development of antenna simulation technology and the popularization of smart antenna, the demand for computer hardware and software infrastructure in universities, small and medium-sized enterprises and other research institutions has increased rapidly, frequent equipment updates and relatively independent software and hardware operation mode, With the rise of cloud computing and virtualization technology, antenna simulation can be combined with cloud computing technology. The antenna simulation cloud platform can not only make rational use of computer software and hardware resources, but also break the bottleneck restricting the development of antenna simulation technology. Moreover, it can greatly facilitate the practical activities of researchers and effectively improve the efficiency of scientific research. Firstly, this paper introduces several mainstream IaaS cloud platforms, and selects the widely accepted OpenStack technology to construct antenna simulation cloud platform. The necessary simulation environment template file and cloud host type of antenna simulation cloud platform are created, which provide users with the simulation environment and computer hardware service on demand, and then deeply study the overall architecture and core components of OpenStack. Combined with OpenStack source code, the initial virtual machine allocation module and virtual machine dynamic migration module of OpenStack are deeply analyzed, its working principle is expounded, and the shortcomings are pointed out. Aiming at the defects of the native resource scheduling strategy of OpenStack, the multi-objective ant colony optimization algorithm and the virtual machine dynamic migration multi-objective optimization algorithm are proposed, and the multi-objective ant colony optimization algorithm is used to improve the initial placement strategy of virtual machine. Through the continuous updating of pheromone, the optimal solution can be obtained quickly, so as to find the best placement position for the new virtual machine. The simulation results show that the algorithm can not only guarantee good service performance, but also reduce the resource load and power consumption. The dynamic migration strategy of OpenStack virtual machine is improved by using the multi-objective optimization algorithm of virtual machine dynamic migration. The binary integral delay method and time prediction method are designed to determine the migration opportunity. Using the multi-objective optimization algorithm to select the appropriate target physical host, the probability-based selection algorithm is designed to avoid the clustering effect of virtual machine. The simulation results show that, This set of virtual machine resource dynamic scheduling methods can perform the task of real-time resource scheduling and optimize the performance of the data center at the same time.
【學(xué)位授予單位】：天津工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TN820;TP391.9

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