發(fā)布時間：2018-06-08 02:45

  本文選題：云應(yīng)用程序 + 資源配置預(yù)估　； 參考：《華北電力大學(xué)》2017年碩士論文

【摘要】：隨著云計算技術(shù)的發(fā)展,IT基礎(chǔ)設(shè)施需求已從傳統(tǒng)的設(shè)備購買轉(zhuǎn)變成按需租賃的方式。然而,人們往往會對自身程序需求資源預(yù)估不合理,導(dǎo)致購買的虛擬機(jī)或大或小,資源利用率不高。對云提供商來說,在資源分配前需要對用戶的使用資源有一定的了解。以期更好的制定虛擬機(jī)部署策略。針對上述問題,本文提出了基于云用戶應(yīng)用的云平臺虛擬機(jī)調(diào)度規(guī)劃。分為云應(yīng)用需求資源的預(yù)估、與虛擬機(jī)調(diào)度規(guī)劃的設(shè)計兩部分�；谠茟�(yīng)用參數(shù)的變化,提出了一種資源配置預(yù)估方法。仿照解釋器的思想,靜態(tài)分析程序源碼,得出任務(wù)執(zhí)行的語句數(shù);通過曲線擬合與少次數(shù)的程序運(yùn)行,得出程序運(yùn)行時間隨參數(shù)變化的趨勢。限制實(shí)驗(yàn)主機(jī)配置的CPU占用比例,得出參數(shù)、用戶程序運(yùn)行時間與CPU占用資源之間的關(guān)系。使用pascal hanoi程序?qū)υ摲椒ㄟM(jìn)行驗(yàn)證,證明該方法測得參數(shù)變化下的程序運(yùn)行時間與實(shí)際運(yùn)行時間非常接近,誤差率很小。通過對CPU占用率的限制,測得在不同的cpu-MIPS值下,程序?qū)嶋H運(yùn)行時間與預(yù)計運(yùn)行時間誤差很小。提出了基于負(fù)載預(yù)測的虛擬機(jī)資源分配方案,用靜態(tài)參數(shù)加動態(tài)監(jiān)測相結(jié)合的雙重機(jī)制避免了主機(jī)負(fù)載過重,通過預(yù)測主機(jī)負(fù)載情況,過濾掉即將達(dá)到警告值的主機(jī);引用了二維裝箱問題的BFD算法思想,對資源進(jìn)行最大化利用。對本方案與輪詢算法分別進(jìn)行仿真實(shí)驗(yàn),分析了兩種算法對主機(jī)綜合利用率與負(fù)載穩(wěn)定性的影響;分析了本方案在警告值(A2)不同的情況下與輪詢算法相比,主機(jī)綜合利用率的變化情況。實(shí)驗(yàn)可得本方案在A2參數(shù)為0.95時,與輪詢算法相比提高了資源利用率。同時主機(jī)負(fù)載變化相對平穩(wěn),主機(jī)性能相對穩(wěn)定。
[Abstract]:With the development of cloud computing technology, IT infrastructure needs have changed from traditional equipment purchase to on-demand leasing. However, people often do not estimate the resources of their own programs reasonably, which leads to the purchase of large or small virtual machines and low utilization of resources. For cloud providers, it is necessary to have a certain understanding of the user's use of resources before resource allocation. In order to better formulate virtual machine deployment strategy. Aiming at the above problems, this paper proposes a cloud platform virtual machine scheduling plan based on cloud user application. It is divided into two parts: the estimation of cloud application resource and the design of virtual machine scheduling planning. Based on the variation of cloud application parameters, a resource allocation estimation method is proposed. According to the idea of interpreter, static analysis of the program source code, get the number of statements executed by the task, through curve fitting and fewer times of the program running, get the program running time with the change of parameters trend. The relationship among the parameters, the running time of the user program and the CPU occupied resources is obtained by limiting the CPU occupancy ratio of the experiment host configuration. The pascal hanoi program is used to verify the method. It is proved that the program running time measured by this method is very close to the actual running time and the error rate is very small. By limiting the CPU occupancy rate, it is found that under different cpu-MIPS values, the error between the actual running time and the estimated running time of the program is very small. A virtual machine resource allocation scheme based on load prediction is put forward. The dual mechanism of static parameter and dynamic monitoring is used to avoid the overloading of the host, and by predicting the load of the host, it filters out the host which will reach the warning value. In this paper, the idea of BFD algorithm for two-dimensional packing problem is introduced to maximize the utilization of resources. The simulation experiments of this scheme and the polling algorithm are carried out, and the effects of the two algorithms on the overall utilization ratio and load stability of the host are analyzed, and the comparison between this scheme and the polling algorithm under the different warning value of A2) is presented. The overall utilization of the host changes. Experimental results show that this scheme can improve resource utilization compared with polling algorithm when A2 parameter is 0.95. At the same time, the host load changes relatively stable, host performance is relatively stable.
【學(xué)位授予單位】：華北電力大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP302;TP393.09

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王志平;李小勇;;基于實(shí)時計算平臺的虛擬機(jī)調(diào)度策略[J];計算機(jī)工程;2016年05期

2 魏蔚;劉揚(yáng);楊衛(wèi)東;;一種通用云計算資源調(diào)度問題的快速近似算法[J];計算機(jī)研究與發(fā)展;2016年03期

3 鄧見光;趙躍龍;袁華強(qiáng);;一種多QoS目標(biāo)約束的云計算任務(wù)調(diào)度策略[J];計算機(jī)應(yīng)用研究;2016年08期

4 薛濤;馬騰;;基于資源權(quán)重最大資源利用率的動態(tài)資源調(diào)度算法[J];計算機(jī)應(yīng)用研究;2016年05期

5 游慶根;王冉;馬輝民;張春暉;;云環(huán)境下基于雙邊匹配的虛擬機(jī)部署決策方法[J];計算機(jī)應(yīng)用研究;2015年10期

6 周東清;O@慶乾;;異構(gòu)云平臺中能源有效的虛擬機(jī)部署研究[J];計算機(jī)科學(xué);2015年03期

7 陳小嬌;陳世平;;基于DEA的能耗感知虛擬機(jī)資源分配算法[J];小型微型計算機(jī)系統(tǒng);2015年01期

8 黃明凱;劉先華;譚明星;謝子超;程旭;;一種面向解釋器的間接轉(zhuǎn)移預(yù)測技術(shù)[J];計算機(jī)研究與發(fā)展;2015年01期

9 董健康;王洪波;李陽陽;程時端;;IaaS云中面向能源效率優(yōu)化的虛擬機(jī)調(diào)度算法(英文)[J];中國通信;2014年03期

10 張小慶;賀忠堂;李春林;張恒喜;錢瓊芬;;云計算系統(tǒng)中數(shù)據(jù)中心的節(jié)能算法研究[J];計算機(jī)應(yīng)用研究;2013年04期

相關(guān)博士學(xué)位論文 前3條

1 徐琳;云計算環(huán)境下計算型任務(wù)的資源需求預(yù)測[D];中國科學(xué)技術(shù)大學(xué);2015年

2 徐昕;基于博弈論的云計算資源調(diào)度方法研究[D];華東理工大學(xué);2015年

3 郭濤;IaaS平臺中虛擬機(jī)部署策略與運(yùn)行機(jī)制的研究[D];太原理工大學(xué);2014年

相關(guān)碩士學(xué)位論文 前5條

1 田苗苗;云數(shù)據(jù)中心虛擬機(jī)的低能耗部署和遷移策略[D];中國科學(xué)技術(shù)大學(xué);2015年

2 王敏訥;基于cloudstack的虛擬機(jī)部署方案的研究與實(shí)現(xiàn)[D];北京郵電大學(xué);2015年

3 王力;云計算環(huán)境下高效公平的虛擬機(jī)調(diào)度機(jī)制[D];西安電子科技大學(xué);2014年

4 殷小龍;云計算環(huán)境下的虛擬機(jī)調(diào)度策略研究[D];南京郵電大學(xué);2014年

5 吳鈞超;基于云用戶應(yīng)用評估的云平臺任務(wù)調(diào)度策略研究[D];哈爾濱工業(yè)大學(xué);2013年

，

本文編號：1994066