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基于清华云监控平台的云迁移性能
引用本文:马海峰,意合巴力,王烨,杨家海,张潮.基于清华云监控平台的云迁移性能[J].计算机应用,2015,35(11):3026-3030.
作者姓名:马海峰  意合巴力  王烨  杨家海  张潮
作者单位:1. 黑龙江科技大学 计算机与信息工程学院, 哈尔滨 150022;2. 清华大学 网络科学与网络空间研究院, 北京 100084;3. 新疆广电网络股份有限公司, 乌鲁木齐 830091;4. 中国移动通信集团公司, 北京 100032
基金项目:教育部-中国移动研究基金资助项目(MCM20123041);黑龙江省教育厅科学技术研究项目(12533052).
摘    要:当云计算技术兴起后,很多企业已经或计划将业务和应用迁移到云上,而这面临着应用性能可能降低,关键业务和应用安全性受到威胁等问题,因此是否云迁移还是部署到独立服务器上,是一个需要深入研究的问题.以清华云平台为基础,搭建了基于Nagios的清华云监控平台,先对清华云平台和架构进行介绍,再对Nagios和清华云监控平台架构进行了论述,在云迁移性能评估中,以Ubuntu和Windows为操作系统平台,以CPU负载和内存使用为评估指标,分别在云服务器和独立服务器上运行CPU运算类和服务器负载类两类应用,最后对实验结果进行了分析和比较.实验表明,部分应用在独立服务器上性能更好,并不适合云迁移.

关 键 词:云计算    性能监控    云迁移    OpenStack    Nagios
收稿时间:2015-06-17
修稿时间:2015-07-21

Cloud migration performance of tsinghua cloud monitoring platform
MA Haifeng,YI Hebali,WANG Ye,YANG Jiahai,ZHANG Chao.Cloud migration performance of tsinghua cloud monitoring platform[J].journal of Computer Applications,2015,35(11):3026-3030.
Authors:MA Haifeng  YI Hebali  WANG Ye  YANG Jiahai  ZHANG Chao
Affiliation:1. Computer and Information Engineering Institute, Heilongjiang University of Science and Technology, Harbin Helongjiang 150022, China;2. Institute for Network Sciences and Cyberspace, Tsinghua University, Beijing 100084, China;3. Xinjiang Broadcast and Television Company Limited, Urumqi Xinjiang 830091, China;4. China Mobile Communications Corporation, Beijing 100032, China
Abstract:With the popularization of cloud computing technology, many enterprises have migrated or are planning to migrate their business and applications to the cloud. But it may face the problems of application performance degradation, and the key business and applications may suffer security threats. Therefore, migrating to cloud or deploying in independent server is a problem that needs to be further studied. In this paper, based on the Tsinghua cloud platform, Tsinghua cloud monitoring platform was set up based on Nagios. Firstly, Tsinghua cloud platform and its architecture were introduced, and then Nagios and the architecture of Tsinghua cloud monitoring platform were discussed. For cloud migration performance evaluation, Ubuntu and Windows were used as operating system platforms, CPU load and memory usage were used as evaluation indexes, two applications of CPU computing type and server load type respectively ran on the cloud server and the independent server. At last, the experimental results were analyzed and compared. The experimental result shows that some applications have better performance on independent servers that may not be suitable for migrating to cloud platform.
Keywords:cloud computing                                                                                                                        performance monitoring                                                                                                                        cloud migration                                                                                                                        OpenStack                                                                                                                        Nagios
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