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The cost of doing science on the cloud: The Montage example
Abstract
Utility grids such as the Amazon EC2 cloud and Amazon S3 offer computational and storage resources that can be used on-demand for a fee by compute and data-intensive applications. The cost of running an application on such a cloud depends on the compute, storage and communication resources it will provision and consume. Different execution plans of the same application may result in significantly different costs. Using the Amazon cloud fee structure and a real-life astronomy application, we study via simulation the cost performance tradeoffs of different execution and resource provisioning plans. We also study these trade-offs in the context of the storage and communication fees of Amazon S3 when used for long-term application data archival. Our results show that by provisioning the right amount of storage and compute resources, cost can be significantly reduced with no significant impact on application performance.
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Cited by
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Juve, G., Chervenak, A., Deelman, E., Bharathi, S., Mehta, G., & Vahi, K. (2013) · Future Generation Computer Systems · doi:10.1016/j.future.2012.08.015 · Cited by 788
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Metadata
- Authors
- Deelman, E., Singh, G., Livny, M., Berriman, B., & Good, J.
- Venue
- 2008 SC - International Conference for High Performance Computing, Networking, Storage and Analysis
- Publisher
- IEEE
- Published
- 2008-11
- Pages
- 1-12
- ISSN
- 2167-4337 (ISSN-L)
- OpenAlex
- W3150630553
- Cited by
- 483
- References
- 0
- FWCI
- 30.95
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: The cost of doing science on the cloud: The Montage example. https://app.cochat.ai/papers/10.1109/sc.2008.5217932
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- Deelman, E., Singh, G., Livny, M., Berriman, B., & Good, J. (2008). The cost of doing science on the cloud: The Montage example. 2008 SC - International Conference for High Performance Computing, Networking, Storage and Analysis. https://doi.org/10.1109/sc.2008.5217932
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