發(fā)布時間：2018-02-20 02:42

  本文關(guān)鍵詞： 云計算 數(shù)據(jù)中心 動態(tài)遷移 資源整合 綠色能效 OpenStack　出處：《電子科技大學(xué)》2013年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著人類社會的飛速發(fā)展，相應(yīng)的環(huán)境問題也愈加突出，因全球變暖而引發(fā)的極端天氣不斷向人們發(fā)出警告，綠色能效、降低碳排放已成為研究熱點，這一理念也深刻影響著IT領(lǐng)域。數(shù)據(jù)中心自發(fā)展之初就面臨巨大的電能需求，而隨著虛擬化技術(shù)的逐步升級，云計算理念的深入人心，利用“瘦前端”接入“云端”服務(wù)器直接使用架設(shè)在數(shù)據(jù)中心上的系統(tǒng)功能擺脫硬件配置束縛已經(jīng)不再是設(shè)想，利用虛擬技術(shù)中的動態(tài)遷移技術(shù)取代傳統(tǒng)業(yè)務(wù)整合為綠色能效資源管理問題開辟了新的技術(shù)途徑。 本文第一章首先簡單介紹了云計算以及數(shù)據(jù)中心的歷史背景，介紹了相關(guān)技術(shù)的發(fā)展路線，并提出了基于能效的數(shù)據(jù)中心資源整合機制問題。 其次，整合機制的設(shè)計與實現(xiàn)都需要有實時監(jiān)控數(shù)據(jù)的支持，，在第二章中本文分析介紹了三種常用的數(shù)據(jù)中心監(jiān)控系統(tǒng)，并針對其數(shù)據(jù)中心電源監(jiān)控/管理和虛擬機監(jiān)控擴展做了分析與概括，最后提出兩種現(xiàn)階段性能較優(yōu)的數(shù)據(jù)中心監(jiān)控解決方案。 再次，本文第三章詳細介紹了現(xiàn)階段數(shù)據(jù)中心的能耗問題，介紹了兩種基于實時監(jiān)控數(shù)據(jù)的服務(wù)器能耗模型，簡要說明了現(xiàn)有硬件節(jié)能技術(shù)的功能與局限，并基于該能耗模型提出了物理機能效整合的基本準(zhǔn)則。隨后提出了基于雙閾值的能效整合機制及整合機制的三個核心問題：閾值設(shè)置，待遷移虛擬機選擇，虛擬機資源整合機制，最后本章提出三種虛擬機選擇機制以供選擇。 第四，為了更詳細的分析資源整合機制本文將基于能效的資源管理問題中的虛擬機資源整合問題單獨提出來，在第四章針對多虛擬機遷移場景從多種不同角度進行了分析和研究，提出了三種整合機制。RP整合機制基于隨機放置，存在不可控性；FFD整合機制將遷移整合轉(zhuǎn)化為裝箱問題，但忽略了源主機的區(qū)別，導(dǎo)致算法存在不穩(wěn)定性；GCBFD整合機制將分組思想引入FFD整合機制，提供了更好的算法性能和算法穩(wěn)定性。仿真結(jié)果表明，GCBFD整合機制穩(wěn)定準(zhǔn)確且有效的降低了云數(shù)據(jù)中心的能耗，為最優(yōu)選項。 最后，在第五章中，本文基于OpenStack開源云平臺進行了資源整合機制的開發(fā)設(shè)計，設(shè)計了基于OpenStack的能耗感知型資源整合智慧云平臺的模塊功能和邏輯接口。
[Abstract]:With the rapid development of human society, the corresponding environmental problems become more and more prominent. The extreme weather caused by global warming constantly warns people. Green energy efficiency and reducing carbon emissions have become the research focus. The data center has been facing huge power demand since the beginning of its development, but with the gradual upgrading of virtualization technology, cloud computing concept has been deeply rooted in people's hearts and minds. It is no longer envisaged to use the "thin front end" to access the "cloud" server directly using the system functions set up in the data center to get rid of the constraints of hardware configuration. The use of dynamic migration technology in virtual technology to replace traditional business integration has opened up a new technical approach to green energy efficiency resource management. In the first chapter of this paper, the historical background of cloud computing and data center is briefly introduced, the development route of related technology is introduced, and the resource integration mechanism of data center based on energy efficiency is put forward. Secondly, the design and implementation of the integration mechanism need the support of real-time monitoring data. In the second chapter, this paper analyzes and introduces three kinds of commonly used data center monitoring system. The data center power monitoring / management and virtual machine monitoring extension are analyzed and summarized. Finally, two kinds of data center monitoring solutions with better performance at present are put forward. Thirdly, the third chapter introduces the energy consumption of the data center in detail, introduces two kinds of server energy consumption models based on real-time monitoring data, briefly explains the function and limitation of the existing hardware energy-saving technology. Based on the energy consumption model, the basic principles of energy efficiency integration of physical machines are proposed. Then, the energy efficiency integration mechanism based on double thresholds and three key issues of integration mechanism are proposed: threshold setting, choice of virtual machine to be migrated, Finally, three mechanisms of virtual machine selection are proposed. 4th, in order to analyze the mechanism of resource integration in more detail, this paper puts forward the problem of virtual machine resource integration in resource management based on energy efficiency. In Chapter 4th, we analyze and study the multi-virtual machine migration scenarios from different angles, and propose three kinds of integration mechanisms .RP integration mechanism based on random placement, there is an uncontrolled FFD integration mechanism to transform migration integration into packing problem. However, the differences between the source host and the source host are ignored, which leads to the instability of the algorithm and the introduction of the grouping idea into the FFD integration mechanism. The simulation results show that the GCBFD integration mechanism is stable, accurate and effective to reduce the energy consumption of the cloud data center and is the best option. Finally, in chapter 5th, we design the resource integration mechanism based on OpenStack open source cloud platform, and design the module function and logic interface of energy consumption aware resource integration intelligent cloud platform based on OpenStack.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2013
【分類號】：TP308

【參考文獻】

相關(guān)期刊論文 前1條

1 李榮珩,越民義;FFD(L)≤11/9OPT(L)+7/9[J];科學(xué)通報;1997年11期

本文編號：1518575