Cloud benchmarking for performance
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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.
Varghese , B , Akgun , O , Miguel , I , Thai , L & Barker , A 2014 , Cloud benchmarking for performance . in 6th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2014) . IEEE , pp. 535-540 . DOI: 10.1109/CloudCom.2014.28
6th IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2014)
© 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.2014.28
Date of Acceptance: 20/09/2014