Performance modeling on the basis of application type in virtualized environments

ISCAS OpenIR

	Performance modeling on the basis of application type in virtualized environments
	Meng, Fanxin (1); Du, Guangyu (2); He, Hong (2); Yuan, Shengzhong (2); He, H.(hehong@sdu.edu.cn)
	2013
发表期刊	Journal of Software
ISSN	1796217X
卷号	8 期号:11 页码:2847-2854
摘要	Virtualization technology plays an essential role in resource in modern large data centers while it also causes interference among virtual machines which co-located in common physical machine contending for the shared physical resources. In this paper, we study the performance prediction models in virtualized environment. Unclassified model developed from all types of applications is quite inaccuracy to predict performance of test applications as it is too general. We respectively develop models for each type of applications classified by the resources that they use. See5/C5 technology is used to determine the type of test application before executing its corresponding performance prediction model and linear regression technique is adopt to develop performance prediction models. Finally, comparing classified models with the unclassified one, the former get 0.038 average prediction errors for test applications while unclassified model arrives 0.609 average prediction errors. © 2013 ACADEMY PUBLISHER.; Virtualization technology plays an essential role in resource in modern large data centers while it also causes interference among virtual machines which co-located in common physical machine contending for the shared physical resources. In this paper, we study the performance prediction models in virtualized environment. Unclassified model developed from all types of applications is quite inaccuracy to predict performance of test applications as it is too general. We respectively develop models for each type of applications classified by the resources that they use. See5/C5 technology is used to determine the type of test application before executing its corresponding performance prediction model and linear regression technique is adopt to develop performance prediction models. Finally, comparing classified models with the unclassified one, the former get 0.038 average prediction errors for test applications while unclassified model arrives 0.609 average prediction errors. © 2013 ACADEMY PUBLISHER.
收录类别	EI
部门归属	(1) School of Mechanical, Electrical and Information Engineering, Shandong University, Weihai, Weihai, 264209, China; (2) Institute of Software of Chinese Academy of Sciences, Beijing. 100000, China
语种	英语
内容类型	期刊论文
URI标识	http://ir.iscas.ac.cn/handle/311060/17047
专题	中国科学院软件研究所
通讯作者	He, H.(hehong@sdu.edu.cn)
推荐引用方式 GB/T 7714	Meng, Fanxin ,Du, Guangyu ,He, Hong ,et al. Performance modeling on the basis of application type in virtualized environments[J]. Journal of Software,2013,8(11):2847-2854.
APA	Meng, Fanxin ,Du, Guangyu ,He, Hong ,Yuan, Shengzhong ,&He, H..(2013).Performance modeling on the basis of application type in virtualized environments.Journal of Software,8(11),2847-2854.
MLA	Meng, Fanxin ,et al."Performance modeling on the basis of application type in virtualized environments".Journal of Software 8.11(2013):2847-2854.