【摘要】：云計(jì)算中的PaaS本質(zhì)上是物理資源的虛擬化,是構(gòu)建云計(jì)算數(shù)據(jù)中心的基礎(chǔ)。虛擬化是一種資源管理技術(shù),它將底層物理硬件透明化,使用戶更有效地使用這些資源。云計(jì)算借助虛擬機(jī)集群,將物理資源有效整合,實(shí)現(xiàn)資源共享,最大化資源利用率。它通常在硬件和應(yīng)用之間增加虛擬化層,這對(duì)云服務(wù)的系統(tǒng)性能(比如數(shù)據(jù)吞吐量、傳輸延時(shí)和每秒處理事務(wù)數(shù))有直接影響。在I/O虛擬化方面,傳統(tǒng)的方法是使用純軟件模擬的完全虛擬化方式來執(zhí)行I/O操作,但模擬執(zhí)行的過程需占用大量CPU資源,效率差。因此半虛擬化方式被提出來,通過前后端驅(qū)動(dòng)主動(dòng)通信來提高客戶機(jī)I/O性能。目前常用的虛擬化平臺(tái)KVM(Kernel-based Virtual Machine,內(nèi)核虛擬機(jī))采用設(shè)備驅(qū)動(dòng)標(biāo)準(zhǔn)框架Virtio來實(shí)現(xiàn)半虛擬化。半虛擬化框架Virtio在處理網(wǎng)絡(luò)請(qǐng)求時(shí),占用CPU資源最多的場(chǎng)景是I/O請(qǐng)求數(shù)據(jù)轉(zhuǎn)換時(shí),hypercall(超級(jí)調(diào)用)導(dǎo)致的頻繁的系統(tǒng)切換,造成性能瓶頸。針對(duì)這一問題,本文基于半虛擬化框架Virtio提出一種雙端聚合方法TAM(Two-end Aggregation Method)來降低虛擬層對(duì)云服務(wù)系統(tǒng)性能的影響。該方法以Virtio網(wǎng)絡(luò)模塊Virtio-net為基礎(chǔ),將通過Virtio-net前端模塊的請(qǐng)求聚合,傳入共享通道,異步通知后端;Virtio-net后端將共享通道Virtqueue隊(duì)列描述符列表中的可用請(qǐng)求逐一取出,分別處理后異步通知前端。通過聚合,雙端均將原本所需的多次hypercall的開銷減少為一次,降低CPU系統(tǒng)切換開銷,從而提升系統(tǒng)性能。使用Netperf基準(zhǔn)測(cè)試程序和Ping模擬真實(shí)應(yīng)用場(chǎng)景進(jìn)行實(shí)驗(yàn),結(jié)果表明:使用雙端聚合優(yōu)化方法TAM的Virtio網(wǎng)絡(luò)模型,其數(shù)據(jù)吞吐量和每秒處理事務(wù)數(shù)相比只優(yōu)化前端的AHC方法分別提高5.76%和4.3%,延時(shí)減少46.2%。
[Abstract]:PaaS in cloud computing is essentially the virtualization of physical resources and the foundation of building cloud computing data center. Virtualization is a resource management technology that makes the underlying physical hardware transparent and allows users to use these resources more efficiently. Cloud computing uses virtual machine cluster to integrate physical resources effectively, realize resource sharing and maximize resource utilization. It usually adds a virtualization layer between hardware and applications, which has a direct impact on the system performance of cloud services, such as data throughput, transmission latency, and the number of transactions processed per second. In the aspect of I / O virtualization, the traditional method is to use the complete virtualization mode of pure software simulation to perform I / O operations. However, the simulation process requires a large amount of CPU resources and is inefficient. Therefore, the semi-virtualization method is proposed to improve the client I / O performance by driving active communication at the front and back end. At present, KVM (Kernel-based Virtual Machine, kernel virtual machine), a common virtualization platform, adopts Virtio (device driver standard framework) to realize semi-virtualization. When the semi-virtualized framework Virtio processes network requests, the scenario where the CPU resource is most occupied is the frequent system switching caused by the, hypercall (super call when I? O requests data conversion), which results in the performance bottleneck. To solve this problem, this paper proposes a two-terminal aggregation method, TAM (Two-end Aggregation Method), based on the semi-virtualized framework Virtio (Two-end Aggregation Method) to reduce the impact of virtual layer on the performance of cloud service systems. Based on the Virtio network module Virtio-net, the method aggregates the request through the Virtio-net front-end module, passes in the shared channel, and notifies the back-end asynchronously. The Virtio-net backend takes out the available requests in the list of shared channel Virtqueue queue descriptors one by one, and separately processes the asynchronous notification front end. By aggregation, the cost of multiple hypercall is reduced to one time, and the switching overhead of CPU system is reduced, thus improving the performance of the system. The Netperf benchmark program and Ping are used to simulate the real application scenario. The results show that the Virtio network model of the two-terminal aggregation optimization method TAM is used. The data throughput and transactions per second are 5.76% and 4.3% higher and the latency is reduced by 46.2% compared with the AHC method which only optimizes the front end.
【學(xué)位授予單位】：太原理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP3

【參考文獻(xiàn)】

相關(guān)期刊論文 前5條

1 鄭哲;;一種物流云系統(tǒng)的架構(gòu)方法[J];電腦編程技巧與維護(hù);2013年22期

2 湯建龍;;CPU虛擬化技術(shù)分析和應(yīng)用[J];沙洲職業(yè)工學(xué)院學(xué)報(bào);2012年04期

3 張彬彬;汪小林;楊亮;賴榮鳳;王振林;羅英偉;李曉明;;修改客戶操作系統(tǒng)優(yōu)化KVM虛擬機(jī)的I/O性能[J];計(jì)算機(jī)學(xué)報(bào);2010年12期

4 顧振宇;張申生;李曉勇;;Xen中Credit調(diào)度算法的優(yōu)化[J];微型電腦應(yīng)用;2009年02期

5 李樹國,劉詩斌,高德遠(yuǎn),樊曉椏;存儲(chǔ)器管理部件的研究[J];西北工業(yè)大學(xué)學(xué)報(bào);2000年03期

相關(guān)碩士學(xué)位論文 前7條

1 程書欣;嵌入式虛擬化環(huán)境中I/O性能瓶頸分析與優(yōu)化[D];上海交通大學(xué);2015年

2 寧峰峰;虛擬化環(huán)境下的網(wǎng)絡(luò)IO性能優(yōu)化[D];上海交通大學(xué);2014年

3 李家祥;Xen虛擬機(jī)網(wǎng)絡(luò)I/O性能優(yōu)化研究[D];華中科技大學(xué);2013年

4 張洪素;基于Xen的虛擬交換技術(shù)的研究與設(shè)計(jì)[D];天津大學(xué);2012年

5 劉浩;基于負(fù)載均衡的存儲(chǔ)架構(gòu)研究與應(yīng)用[D];山東大學(xué);2011年

6 趙威;Xen虛擬化網(wǎng)絡(luò)I/O優(yōu)化方法[D];華中科技大學(xué);2011年

7 姚遠(yuǎn);虛擬機(jī)高效設(shè)備訪問模型設(shè)計(jì)與實(shí)現(xiàn)[D];國防科學(xué)技術(shù)大學(xué);2010年

，

本文編號(hào)：2466631