Cloud benchmarking for performance

Blesson Varghese, Ozgur Akgun, Ian Miguel, Long Thai, Adam Barker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

18 Citations (Scopus)
270 Downloads (Pure)

Abstract

How can applications be deployed on the cloud to achieve maximum performance? This question has become significant and challenging with the availability of a wide variety of Virtual Machines (VMs) with different performance capabilities in the cloud. The above question is addressed by proposing a six step benchmarking methodology in which a user provides a set of four weights that indicate how important each of the following groups: memory, processor, computation and storage are to the application that needs to be executed on the cloud. The weights along with cloud benchmarking data are used to generate a ranking of VMs that can maximise performance of the application. The rankings are validated through an empirical analysis using two case study applications, the first is a financial risk application and the second is a molecular dynamics simulation, which are both representative of workloads that can benefit from execution on the cloud. Both case studies validate the feasibility of the methodology and highlight that maximum performance can be achieved on the cloud by selecting the top ranked VMs produced by the methodology.
Original languageEnglish
Title of host publicationProceedings of 2014 IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages535-540
Number of pages6
ISBN (Print)978-1-4799-4093-6
DOIs
Publication statusPublished - Dec 2014
Event2014 IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom) - Singapore, Singapore
Duration: 15 Dec 201418 Dec 2014

Conference

Conference2014 IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom)
CountrySingapore
CitySingapore
Period15/12/201418/12/2014

Bibliographical note

Acceptance rate (54/301): 18%

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