DocumentCode
78365
Title
Is the Same Instance Type Created Equal? Exploiting Heterogeneity of Public Clouds
Author
Zhonghong Ou ; Hao Zhuang ; Lukyanenko, Andrey ; Nurminen, Jukka K. ; Pan Hui ; Mazalov, Vladimir ; Yla-Jaaski, Antti
Author_Institution
Dept. of Comput. Sci. & Eng., Aalto Univ., Espoo, Finland
Volume
1
Issue
2
fYear
2013
fDate
July-December 2013
Firstpage
201
Lastpage
214
Abstract
Public cloud platforms might start with homogeneous hardware; nevertheless, because of inevitable hardware upgrades, or adding more capacity, the initial homogeneous platform will gradually evolve into heterogeneous as time passes by. The consequent performance heterogeneity is of concern to cloud users. In this paper, we evaluate performance variations from hardware heterogeneity and scheduling mechanisms of public clouds. Amazon Elastic Compute Cloud (Amazon EC2) and Rackspace Cloud are used as the representatives because of their relatively long record and wide usage among small and medium enterprises (SMEs). A comprehensive set of microbenchmarks and application-level macrobenchmarks have been used to investigate performance variation. Several major contributions have been made. First, we find out that heterogeneous hardware is a commonality among the relatively long-lasting cloud platforms, although the level of heterogeneity varies. Second, we observe that heterogeneous hardware is the primary culprit of performance variation of cloud platforms. Third, we discover that varied CPU acquisition percentages and different virtual machine scheduling mechanisms exacerbate the performance variation problem, especially for network related operations. Finally, based on the observations, we propose cost-saving approaches and analyze Nash equilibrium from cloud user perspective. By using a simple "trial-and-better" approach, i.e., keep good-performing instances and discard bad-performing instances, cloud users can achieve up to 30 percent cost saving.
Keywords
cloud computing; cost reduction; game theory; scheduling; virtual machines; Amazon EC2; Amazon Elastic Compute Cloud; Nash equilibrium; Rackspace Cloud; SME; application-level macrobenchmarks; cloud user perspective; cost-saving approach; hardware heterogeneity mechanisms; hardware upgrades; heterogeneous platform; homogeneous hardware; homogeneous platform; instance type; microbenchmarks; network related operations; performance variation problem; public cloud platforms; public clouds heterogeneity; scheduling mechanisms; small-and-medium enterprises; trial-and-better approach; varied CPU acquisition percentages; virtual machine scheduling mechanisms; Benchmark testing; Central Processing Unit; Cloud computing; Hardware; Servers; Virtual machine monitors; Amazon EC2; Hardware heterogeneity; VM scheduling mechanism; cloud computing; performance variation;
fLanguage
English
Journal_Title
Cloud Computing, IEEE Transactions on
Publisher
ieee
ISSN
2168-7161
Type
jour
DOI
10.1109/TCC.2013.12
Filename
6654148
Link To Document