【摘要】：數(shù)據(jù)中心的建設與發(fā)展將有利于數(shù)據(jù)中心的商業(yè)應用與運作,然而近年來,隨著云計算的快速發(fā)展,通過互聯(lián)網技術實現(xiàn)的各種應用層出不窮,為了滿足日益增長的用戶需求,數(shù)據(jù)中心的規(guī)模在不斷的擴大,這給數(shù)據(jù)中心帶來了一系列新的問題,如能耗、性能、安全、管理問題等等。特別是高能耗問題,而虛擬機整合是解決數(shù)據(jù)中心高能耗問題的手段之一。其思想是使用虛擬機實時遷移,以便一些輕載的物理機可以關閉或者切換到低功耗模式,并通過特定的目標函數(shù)尋找一個近似最優(yōu)解。本文在分析現(xiàn)有虛擬機整合算法不足的基礎上,提出兩種改進的虛擬機整合算法,主要成果包括:首次提出了一種基于多種群蟻群算法的虛擬機整合算法。其思想是根據(jù)當前資源需求來減少活躍的物理機的數(shù)量,通過特定的目標函數(shù)建立遷移計劃,各種群的信息熵來決定螞蟻群體間的信息交流策略,以此來保證算法收斂性和多樣性之間的平衡。通過仿真實驗分別和基于蟻群系統(tǒng)的虛擬機整合算法以及基于向量代數(shù)的虛擬機整合算法進行比較,驗證了該算法在降低能量消耗和減少虛擬機遷移次數(shù)方面的有效性。首次提出了一種基于文化-多種群蟻群算法的虛擬機整合算法。在該算法中,將多蟻群算法放入文化算法的種群空間中,并將種群空間中每代螞蟻的最優(yōu)值通過函數(shù)傳入文化算法的信仰空間中。通過信仰空間中的進化算法對該方案進行進化,并指導種群空間進行優(yōu)化,以期通過用最少的遷移次數(shù)來使更多的物理機進入休眠狀態(tài),來達到減少云數(shù)據(jù)中心能耗的目的。仿真實驗驗證了該算法不僅有效的降低了能量消耗而且減少了虛擬機遷移次數(shù)。
[Abstract]:The construction and development of the data center will benefit the commercial application and operation of the data center. However, with the rapid development of cloud computing in recent years, various applications realized through the Internet technology emerge one after another, in order to meet the increasing needs of users. The scale of the data center is expanding, which brings a series of new problems to the data center, such as energy consumption, performance, security, management and so on. Especially the problem of high energy consumption, and virtual machine integration is one of the methods to solve the problem of high energy consumption in data center. The idea is to use virtual machines to migrate in real time so that some light-duty physical machines can turn off or switch to low-power mode and find an approximate optimal solution through specific objective functions. Based on the analysis of the shortcomings of existing virtual machine integration algorithms, two improved virtual machine integration algorithms are proposed in this paper. The main achievements are as follows: for the first time, a virtual machine integration algorithm based on multi-colony ant colony algorithm is proposed. The idea is to reduce the number of active physical machines according to the current resource requirements, to establish migration plans through specific objective functions, and to determine the information exchange strategy among ant populations by the information entropy of various groups. In order to ensure the balance between convergence and diversity of the algorithm. The simulation results are compared with the algorithm based on ant colony system and the algorithm based on vector algebra respectively. The results show that the algorithm is effective in reducing the energy consumption and the number of times of virtual machine migration. A virtual machine integration algorithm based on culture-multi-colony ant colony algorithm is proposed for the first time. In this algorithm, the multi-ant colony algorithm is put into the population space of the cultural algorithm, and the optimal value of each generation ant in the population space is passed into the belief space of the cultural algorithm through the function. The scheme is evolved by evolutionary algorithms in belief space, and the population space is optimized to reduce the energy consumption of cloud data centers by making more physical machines dormant with the least number of migration times. The simulation results show that the proposed algorithm not only reduces the energy consumption but also reduces the number of virtual machine migration.
【學位授予單位】：天津工業(yè)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP302;TP308

【參考文獻】

相關期刊論文 前4條

1 趙君;馬中;劉馳;李海山;王新余;;一種多目標蟻群優(yōu)化的虛擬機放置算法[J];西安電子科技大學學報;2015年03期

2 葉可江;吳朝暉;姜曉紅;何欽銘;;虛擬化云計算平臺的能耗管理[J];計算機學報;2012年06期

3 李剛健;;基于虛擬化技術的云計算平臺架構研究[J];吉林建筑工程學院學報;2011年01期

4 郭一楠;王輝;;文化算法研究綜述[J];計算機工程與應用;2009年09期

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本文編號：2226096