PricingTheCloud : A Pricing Estimator for an Informed Cloud-Migration Process

Kamgang, Ines Raissa Djouela and Elhabbash, Abdessalam and Elkhatib, Yehia (2024) PricingTheCloud : A Pricing Estimator for an Informed Cloud-Migration Process. In: Proceedings of GECON 2024 : 20th International Conference on the Economics of Grids Clouds, Systems and Services. Springer, Cham.

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Abstract

One of the main challenges facing businesses migrating to the cloud is getting an estimate of their costs in advance. The estimators available to date allow companies to compare the different virtual machine offerings from each operator, but only venture very slightly into estimating the overall cost, which includes operational and network costs. Existing estimators include operational costs in their estimates, but almost no one considers the network cost, which is a complex but far from negligible component. In this paper, we seek to address this issue by proposing a new estimator called PricingTheCloud. It is an estimator that enables companies to have an accurate estimate of their costs in advance. Unlike other estimators, PricingTheCloud considers network costs in the cost estimation. Its evaluation shows an average accuracy of 86.73% for compute costs and 65.44% for network costs in different AWS-to-AWS scenarios as compared to AWS invoices and shows the effectiveness of the proposed estimator compared to three other cloud costs estimators namely, Cloudorado, Holori, and Vantage