發(fā)布時間：2018-04-14 17:26

  本文選題：云計算 + 虛擬資源分配　； 參考：《福建師范大學(xué)》2012年碩士論文

【摘要】：云計算被認(rèn)為是下一代的IT服務(wù)模式,受到學(xué)術(shù)界和工業(yè)界的巨大關(guān)注。使用云計算,只需通過計算和存儲能力都十分有限的終端設(shè)備,就可獲得近乎無限的計算和存儲能力。社會對云計算需求的不斷擴大需要構(gòu)建規(guī)模巨大的數(shù)據(jù)中心,而維護其運行需要大量的能量。如何高能效地運行數(shù)據(jù)中心是一個急待解決的問題。 本文首先對云計算的一些基本概念,分類,特點和研究熱點等做了簡單的描述,并介紹了國內(nèi)外關(guān)于高能效虛擬資源分配的研究,以及目前仍存在的不足之處。其次,在服務(wù)器性能指標(biāo)約束的前提下,為了有效降低服務(wù)器集群的能耗。本文將云計算中的虛擬資源分配問題模型化為一個路徑構(gòu)建的問題,利用改進的精華策略螞蟻系統(tǒng)(elitist strategy for ant system, EAS)來進行資源分配方案的優(yōu)化,仿真結(jié)果表明,在提高服務(wù)器利用率的同時,新策略有效地降低了數(shù)據(jù)中心的能耗。為了更大限度地降低數(shù)據(jù)中心的能耗,本文使用動態(tài)調(diào)壓調(diào)頻技術(shù)DVFS (Dynamic Voltage and Frequency Scaling),進一步將云計算中的虛擬資源分配問題建模為 個多目標(biāo)優(yōu)化模型,并使用優(yōu)秀的多目標(biāo)進化算法non-dominated sorting genetic algorithm Ⅱ(NSGA-Ⅱ)求解該多目標(biāo)優(yōu)化模型,仿真結(jié)果表明,針對不同特征的虛擬主機和服務(wù)器的需求,策略能夠在合理的時間內(nèi)生成調(diào)度方案,從而有效地降低運行數(shù)據(jù)中心所需能耗。在本文的最后部分,針對原始NSGA-Ⅱ算法在進化過程中難以通過有效的變異過程來提高對局部解空間的搜索能力,導(dǎo)致在求解多目標(biāo)優(yōu)化問題時出現(xiàn)的早熟現(xiàn)象,通過改進NSGA-Ⅱ算法的變異過程,提高算法對局部解空間的搜索能力,保持了種群的多樣性,避免了早熟現(xiàn)象,同時改進了多目標(biāo)優(yōu)化模型,引入開關(guān)服務(wù)器代價做為優(yōu)化目標(biāo),仿真結(jié)果表明策略能在保證SLAs (Service Level Agreements)的前提下,更加高能效地運行云計算數(shù)據(jù)中心。
[Abstract]:Cloud computing is regarded as the next generation of IT service model, which has attracted great attention from academia and industry.With cloud computing, almost unlimited computing and storage capabilities can be obtained by terminal devices with very limited computing and storage capabilities.The increasing demand for cloud computing requires the construction of a large data center, and the maintenance of its operation requires a great deal of energy.How to run the data center efficiently is an urgent problem to be solved.In this paper, the basic concepts, classification, characteristics and research focus of cloud computing are briefly described, and the domestic and foreign research on the allocation of energy efficient virtual resources, as well as the existing deficiencies are introduced.Secondly, in order to reduce the energy consumption of the server cluster effectively, under the constraint of the server performance index.In this paper, the virtual resource allocation problem in cloud computing is modeled as a path construction problem, and the improved essence strategy ant system, named as strategy for ant system, is used to optimize the resource allocation scheme. The simulation results show that,At the same time, the new strategy can effectively reduce the energy consumption of the data center.In order to reduce the energy consumption of the data center to a greater extent, this paper uses the dynamic Voltage and Frequency scaling technology DVFS to model the virtual resource allocation problem in cloud computing as follows:Non-dominated sorting genetic algorithm 鈪，

本文編號：1750329