An Approach to Estimating Cloud Resources Prior to New Business Startup

Md. Mahmudul Hasan, Md. Shamim Hossain

Abstract


One of the challenging issues in cloud computing is to estimate plausible cloud resources earlier to begin a new business. Vendors or cloud partners are often falling in risks by investing money without aware of the resources they can avail against their budget. In this study, we aim to build a two-stage model that guides vendors to specify a budget as a model parameter and obtain the possible cloud resources via a methodical process. In the first stage of the model, we consider and simulate the monthly cost calculator of Amazon EC2 service using Row Echelon Form to know which factors are involved in driving total cost for cloud resources and how much they affect the cost. In the second stage, we follow a reverse process to optimize the factor values using Genetic Algorithms for determining cloud resources. Finally, our proposed system is evaluated based on popular error measurement processes, MAE and MRE, and they show the outcomes are significant with moderate results in few cases.


Keywords


Estimation; Cloud resources; Cost factors; Startup; Budget; Genetic algorithms.

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