A performance prediction scheme for computation-intensive applications on cloud

Hongli Zhang, Panpan Li, Zhigang Zhou, Xiaojiang Du, Weizhe Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

As cloud computing services are gaining popularity, many organizations are considering migrating their large-scale computing applications to cloud. Different cloud service providers (CSPs) may have different computing platforms and billing methods. Most cloud customers don't know which CSP is more suitable for their applications and how much computing resource should be purchased. To address this issue, in this paper, we present a performance prediction scheme that allows a cloud customer to accurately predict computing resource (e.g., running time) for an application. The proposed scheme identifies application's control flow and scaling blocks, constructs a miniature version program to run in local machines, and then replays it in cloud to get the performance ratio between local and cloud. Our real-network experiments show that the scheme can achieve high prediction accuracy with low overhead.

Original languageEnglish
Title of host publication2013 IEEE International Conference on Communications, ICC 2013
Pages1957-1961
Number of pages5
DOIs
StatePublished - 2013
Event2013 IEEE International Conference on Communications, ICC 2013 - Budapest, Hungary
Duration: 9 Jun 201313 Jun 2013

Publication series

NameIEEE International Conference on Communications
ISSN (Print)1550-3607

Conference

Conference2013 IEEE International Conference on Communications, ICC 2013
Country/TerritoryHungary
CityBudapest
Period9/06/1313/06/13

Keywords

  • Cloud computing
  • cost
  • performance prediction

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