DocumentCode
627456
Title
PseudoApp: Performance prediction for application migration to cloud
Author
Byung Chul Tak ; Chunqiang Tang ; Hai Huang ; Long Wang
Author_Institution
IBM T. J. Watson Res. Center, Hawthorne, NY, USA
fYear
2013
fDate
27-31 May 2013
Firstpage
303
Lastpage
310
Abstract
To migrate an existing application to cloud, a user needs to estimate and compare the performance and resource consumption of the application running in different clouds, in order to select the best service provider and the right virtual machine size. However, it is prohibitively expensive to install a complex application in multiple new environments solely for the purpose of performance benchmarking. Performance modeling is more practical but the accuracy is limited by system factors that are hard to model. We propose a new technique called PseudoApp to address these challenges. Our solution creates a pseudo-application to mimic the resource consumption of a real application. A pseudo-application runs the same set of distributed components and executes the same sequence of system calls as those of the real application. By benchmarking a simple and easyto-install PseudoApp in different cloud environments, a user can accurately obtain the performance and resource consumption of the real application. We apply PseudoApp to Apache and TPC-W and find that PseudoApp accurately predicts their performance with 2-8% error in throughput.
Keywords
cloud computing; software performance evaluation; virtual machines; Apache; PseudoApp; TPC-W; application migration; cloud environments; distributed components; performance benchmarking; performance consumption; performance modeling; performance prediction; resource consumption; virtual machine size; Generators; Kernel; Message systems; Throughput; Time factors; Web pages; Web servers;
fLanguage
English
Publisher
ieee
Conference_Titel
Integrated Network Management (IM 2013), 2013 IFIP/IEEE International Symposium on
Conference_Location
Ghent
Print_ISBN
978-1-4673-5229-1
Type
conf
Filename
6572999
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