Show simple item record

Files in this item

Thumbnail

Item metadata

dc.contributor.authorVarghese, Blesson
dc.contributor.authorAkgun, Ozgur
dc.contributor.authorMiguel, Ian
dc.contributor.authorThai, Long
dc.contributor.authorBarker, Adam
dc.date.accessioned2015-02-16T14:31:03Z
dc.date.available2015-02-16T14:31:03Z
dc.date.issued2014-12-15
dc.identifier.citationVarghese , B , Akgun , O , Miguel , I , Thai , L & Barker , A 2014 , Cloud benchmarking for performance . in Proceedings 2014 IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom 2014) . , 7037713 , IEEE , pp. 535-540 , 6th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2014) , Singapore , Singapore , 15/12/14 . https://doi.org/10.1109/CloudCom.2014.28en
dc.identifier.citationconferenceen
dc.identifier.isbn9781479940936
dc.identifier.otherPURE: 165450596
dc.identifier.otherPURE UUID: 0e8ec1d4-27b1-48ac-b1f0-d20b9ef51659
dc.identifier.otherArXiv: http://arxiv.org/abs/1411.0912v1
dc.identifier.otherORCID: /0000-0001-9519-938X/work/33166294
dc.identifier.otherWOS: 000392947000073
dc.identifier.otherORCID: /0000-0002-6930-2686/work/68281431
dc.identifier.otherScopus: 84937883984
dc.identifier.urihttp://hdl.handle.net/10023/6107
dc.description.abstractHow 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.
dc.format.extent6
dc.language.isoeng
dc.publisherIEEE
dc.relation.ispartofProceedings 2014 IEEE 6th International Conference on Cloud Computing Technology and Science (CloudCom 2014)en
dc.rights© 2014. IEEE. This is the accepted manuscript of a conference paper originally submitted to the IEEE 6th International Conference on Cloud Computing Technology and Science- Cloud benchmarking for performance Varghese, B., Akgun, O., Miguel, I., Thai, L. & Barker, A. 15 Dec 2014 6th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2014). IEEE, p. 535-540 available from http://dx.doi.org/10.1109/CloudCom.2014.28en
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectBDCen
dc.subject.lccQA75en
dc.titleCloud benchmarking for performanceen
dc.typeConference itemen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews.School of Computer Scienceen
dc.contributor.institutionUniversity of St Andrews.Centre for Interdisciplinary Research in Computational Algebraen
dc.identifier.doihttps://doi.org/10.1109/CloudCom.2014.28
dc.identifier.urlhttp://2014.cloudcom.org/en
dc.identifier.urlhttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7031670en


This item appears in the following Collection(s)

Show simple item record