Cost-Efficient CPU Provisioning for Scientific Workflows on Clouds

Cloud providers now offer resources as combinations of CPU frequencies and prices, with faster resources (which operate at higher frequencies) charged at a higher monetary cost. With the emergence of this new pricing scheme, the problem of choosing cost-efficient configurations is becoming even more challenging for users. The frequencies required to achieve cost-efficient configurations may vary in different scenarios, depending on both the provider’s pricing model and the application characteristics. In this paper, two cost-aware algorithms that select low-cost CPU frequencies for each resource to complete a scientific workflow application within a deadline and at a minimum cost are presented. The proposed approaches are evaluated and compared through simulation using different pricing models that charge resource provisioning also based on the CPU frequency.

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