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Optimal selection of application loading on cloud services

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  • Sanjay Sharma
  • Bharat Sharma

Abstract

There is a need for identifying computing power hours and storage utilisation along with total cost optimisation. The present paper focuses on optimal selection of application loading process on the cloud services considering relevant factors. Using this model, small companies that plan to develop applications and use cloud services may determine cost and optimal selection of service by taking into account its own as well as provider’s perspectives into consideration. The paper consists of four stages. First stage deals with the estimation of required computing power hours in the planned duration. Second stage relates to the calculation of storage capacity. Third stage corresponds to the formation of multi objective goal programme to prioritise computing power hours and storage utilisation requirements of applications and optimise total cost of usage. Finally, fourth stage deals with the mixed integer non-linear programming to minimise total cost considering other variable factors. For small application developers who cannot afford in-house IT infrastructure, we find an optimal framework for allocating number of applications on cloud services such as Infrastructure as a Service and Platform as a Service. For ease in planning, the user company can quickly decide corresponding number of applications at appropriate services, and at the same time can reduce overall usage cost. With the help of proposed method, the service provider may keep a suitable inventory of cores to provide backup computing power and storage capacity. This adds value to developers also, as company can plan for their operations corresponding to the business growth.

Suggested Citation

  • Sanjay Sharma & Bharat Sharma, 2016. "Optimal selection of application loading on cloud services," International Journal of Production Research, Taylor & Francis Journals, vol. 54(21), pages 6512-6531, November.
  • Handle: RePEc:taf:tprsxx:v:54:y:2016:i:21:p:6512-6531
    DOI: 10.1080/00207543.2016.1173256
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