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Empirical Performance Assessment of Public Clouds Using System Level Benchmarks

Empirical Performance Assessment of Public Clouds Using System Level Benchmarks

Sanjay P. Ahuja, Thomas F. Furman, Kerwin E. Roslie, Jared T. Wheeler
Copyright: © 2013 |Volume: 3 |Issue: 4 |Pages: 11
ISSN: 2156-1834|EISSN: 2156-1826|EISBN13: 9781466635012|DOI: 10.4018/ijcac.2013100106
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MLA

Ahuja, Sanjay P., et al. "Empirical Performance Assessment of Public Clouds Using System Level Benchmarks." IJCAC vol.3, no.4 2013: pp.81-91. http://doi.org/10.4018/ijcac.2013100106

APA

Ahuja, S. P., Furman, T. F., Roslie, K. E., & Wheeler, J. T. (2013). Empirical Performance Assessment of Public Clouds Using System Level Benchmarks. International Journal of Cloud Applications and Computing (IJCAC), 3(4), 81-91. http://doi.org/10.4018/ijcac.2013100106

Chicago

Ahuja, Sanjay P., et al. "Empirical Performance Assessment of Public Clouds Using System Level Benchmarks," International Journal of Cloud Applications and Computing (IJCAC) 3, no.4: 81-91. http://doi.org/10.4018/ijcac.2013100106

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Abstract

Amazon's Elastic Compute Cloud (EC2) Service is one of the leading public cloud service providers and offers many different levels of service. This paper looks into evaluating the memory, central processing unit (CPU), and input/output I/O performance of two different tiers of hardware offered through Amazon's EC2. Using three distinct types of system benchmarks, the performance of the micro spot instance and the M1 small instance are measured and compared. In order to examine the performance and scalability of the hardware, the virtual machines are set up in a cluster formation ranging from two to eight nodes. The results show that the scalability of the cloud is achieved by increasing resources when applicable. This paper also looks at the economic model and other cloud services offered by Amazon's EC2, Microsoft's Azure, and Google's App Engine.

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