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.

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

  • Ines Raissa Djouela Kamgang,
  • Abdessalam Elhabbash,
  • Yehia Elkhatib

摘要

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.