發(fā)布時(shí)間：2018-07-28 13:27

【摘要】：任何軟件系統(tǒng)都不可避免地發(fā)生軟件衰退,虛擬化系統(tǒng)自然也不例外,因此有必要研究適合于虛擬化系統(tǒng)的自愈技術(shù)。虛擬化系統(tǒng)通常采用虛擬機(jī)在線遷移技術(shù)實(shí)現(xiàn)負(fù)載均衡、故障緩解等管理功能以提高系統(tǒng)可用性,而軟件自愈技術(shù)作為一種預(yù)防性維護(hù)和管理技術(shù),是降低系統(tǒng)衰退導(dǎo)致的系統(tǒng)失效風(fēng)險(xiǎn)、提高系統(tǒng)可用性的更為主動的方法。因此,本文融合了軟件自愈技術(shù)和虛擬機(jī)在線遷移技術(shù),以軟件自愈分析模型作為自愈技術(shù)研究的核心內(nèi)容,研究基于虛擬機(jī)在線遷移的自愈分析模型和虛擬機(jī)在線遷移優(yōu)化,分析自愈策略的成本,試圖為實(shí)施自愈技術(shù)提供決策依據(jù)。本文完成的主要工作和取得的研究成果如下:(1)針對單服務(wù)器虛擬化系統(tǒng)的軟件衰退問題,采用形式化模型描述了應(yīng)對衰退的自愈策略,以虛擬機(jī)監(jiān)視器和/或虛擬機(jī)集群為自愈對象分別構(gòu)造了四種不同的自愈策略對應(yīng)的自愈分析模型,采用了馬爾可夫再生理論進(jìn)行模型分析,并給出了一種最優(yōu)自愈策略的搜索方法。仿真實(shí)驗(yàn)表明合理的自愈策略不僅能有效提升系統(tǒng)可用性,而且能降低系統(tǒng)停機(jī)成本。(2)針對多服務(wù)器虛擬化系統(tǒng)中虛擬機(jī)監(jiān)視器和虛擬機(jī)之間的強(qiáng)依賴關(guān)系,利用隨機(jī)回報(bào)網(wǎng)模型分析了基于時(shí)間虛擬機(jī)冷自愈模型、虛擬機(jī)熱自愈模型和虛擬機(jī)遷移自愈模型,并提出了一個(gè)融入負(fù)載因素的基于時(shí)間和負(fù)載的虛擬機(jī)遷移自愈模型。仿真實(shí)驗(yàn)結(jié)果表明無論穩(wěn)態(tài)可用性還是事務(wù)丟失數(shù)量,虛擬機(jī)遷移自愈策略均優(yōu)于虛擬機(jī)冷/熱自愈策略;融入負(fù)載因素的自愈模型無論在系統(tǒng)可用性和吞吐率等指標(biāo)方面都優(yōu)于基于時(shí)間策略的自愈模型,且在系統(tǒng)負(fù)載動態(tài)變化時(shí)表現(xiàn)地更為穩(wěn)定。(3)為了降低多服務(wù)器虛擬化系統(tǒng)中基于虛擬機(jī)遷移的自愈成本,提出了一個(gè)虛擬機(jī)動態(tài)遷移預(yù)拷貝優(yōu)化算法MSTO。該算法根據(jù)時(shí)間局部性和空間局部性原理,設(shè)計(jì)了一種動態(tài)的遷移窗口設(shè)定和遷移頁面選擇策略,以適應(yīng)于動態(tài)的頁面臟度和遷移鏈路可用帶寬。實(shí)驗(yàn)結(jié)果表明MSTO在停機(jī)時(shí)間、總遷移時(shí)間和遷移總頁數(shù)等方面均優(yōu)于Xen的預(yù)拷貝方法。
[Abstract]:Any software system inevitably occurs software decline, virtualization system is no exception, so it is necessary to study self-healing technology suitable for virtualization system. Virtual machine online migration technology is usually used to achieve load balancing, fault mitigation and other management functions to improve system availability, while software self-healing technology as a preventive maintenance and management technology, It is a more active way to reduce the risk of system failure and improve system availability. Therefore, this paper combines the software self-healing technology and virtual machine online migration technology, taking the software self-healing analysis model as the core of the self-healing technology research, studies the self-healing analysis model based on virtual machine online migration and the virtual machine on-line migration optimization. This paper analyzes the cost of self-healing strategy and tries to provide decision basis for implementing self-healing technology. The main work and research results of this paper are as follows: (1) aiming at the problem of software degradation in single-server virtualization system, a formal model is used to describe the self-healing strategy. Taking virtual machine monitor and / or virtual machine cluster as self-healing objects, four self-healing analysis models corresponding to different self-healing strategies are constructed, and Markov reproducing theory is used to analyze the model. A search method of optimal self-healing strategy is given. Simulation results show that reasonable self-healing strategy can not only effectively improve system availability but also reduce system downtime cost. (2) aiming at the strong dependence between virtual machine monitor and virtual machine in multi-server virtualization system. The cold self-healing model, the thermal self-healing model and the migration self-healing model of virtual machine based on time and load are analyzed by using stochastic return net model, and a model of virtual machine migration self-healing based on time and load is proposed. Simulation results show that virtual machine migration self-healing strategy is superior to virtual machine cold / hot self-healing strategy regardless of steady-state availability or transaction loss. The self-healing model incorporating load factors is superior to the time-based self-healing model in terms of system availability and throughput. In order to reduce the self-healing cost of virtual machine migration in multi-server virtualization system, a dynamic migration pre-copy optimization algorithm MSTO is proposed. According to the principle of time locality and spatial locality, this algorithm designs a dynamic migration window setting and migration page selection strategy to adapt to the dynamic page dirt and the available bandwidth of the migration link. The experimental results show that MSTO is superior to Xen in terms of downtime, total migration time and total number of pages.
【學(xué)位授予單位】：南京理工大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2016
【分類號】：TP302

【參考文獻(xiàn)】

相關(guān)期刊論文 前9條

1 Thandar Thein;Jong Sou Park;;Availability Analysis of Application Servers Using Software Rejuvenation and Virtualization[J];Journal of Computer Science & Technology;2009年02期

2 孟海寧;齊勇;侯迪;;基于非馬爾可夫隨機(jī)Petri網(wǎng)的軟件再生建模與分析[J];計(jì)算機(jī)學(xué)報(bào);2007年12期

3 懷進(jìn)鵬;李沁;胡春明;;基于虛擬機(jī)的虛擬計(jì)算環(huán)境研究與設(shè)計(jì)[J];軟件學(xué)報(bào);2007年08期

4 徐建;張琨;游靜;劉鳳玉;;基于分形的軟件衰退預(yù)測[J];系統(tǒng)仿真學(xué)報(bào);2007年03期

5 蔣樂天;徐國治;周玲玲;;基于強(qiáng)局部加權(quán)回歸算法的軟件老化趨勢提取[J];上海交通大學(xué)學(xué)報(bào);2006年11期

6 游靜;徐建;趙學(xué)龍;劉鳳玉;;嵌套的基于時(shí)間的軟件抗衰策略模型與分析[J];系統(tǒng)仿真學(xué)報(bào);2006年04期

7 范新媛,徐國治,應(yīng)忍冬,蔣樂天;基于隨機(jī)回報(bào)網(wǎng)的機(jī)群系統(tǒng)可用性建模及仿真[J];系統(tǒng)仿真學(xué)報(bào);2004年08期

8 范新媛,徐國治,應(yīng)忍冬,蔣樂天;基于檢查點(diǎn)和Rejuvenation的軟件運(yùn)行模型分析[J];計(jì)算機(jī)仿真;2004年01期

9 范新媛,徐國治,應(yīng)忍冬;基于檢查點(diǎn)和Rejuvenation的軟件可靠性建模分析[J];系統(tǒng)仿真學(xué)報(bào);2003年11期

，

本文編號：2150298