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Efficient IaC-Based Resource Allocation for Virtualized Cloud Platforms

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Part of the Communications in Computer and Information Science book series (CCIS,volume 1534)

Abstract

Cloud computing has become an inevitable part of information technology (IT) and other non-IT businesses. Every computational facility is now provided as computing services by the cloud service providers (CSPs). While providing these services, CSPs try to maintain efficiency by keeping the performance index as high as possible. Although virtualization technology has made this possible by applying resource provisioning techniques, but this approach is still hectic and expertise-dependent. In this paper, we propose an efficient infrastructure as code (IaC) based novel framework for optimizing resource utilization percentage through an automatic provisioning approach. This framework maximizes the resource utilization and performance metrics of virtualized cloud platforms. In this context, we have presented some mathematical formulations and considering those, we addressed our designed programming model for the proposed IaC-based framework. Extensive simulations have been performed to establish the novelty of the proposed approach. We have also presented a comparative study by considering two data centers, one with IaC based proposed model and the other is a conventional contemporary model. Result analysis confirms the performance of our proposed IaC-based framework.

Keywords

  • Infrastructure as code (IaC)
  • Virtualization
  • Performance analysis in cloud
  • Performance optimization technique
  • Cloud computing
  • Resource allocation in cloud

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Correspondence to Babul P. Tewari .

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Mukhopadhyay, N., Tewari, B.P. (2022). Efficient IaC-Based Resource Allocation for Virtualized Cloud Platforms. In: Woungang, I., Dhurandher, S.K., Pattanaik, K.K., Verma, A., Verma, P. (eds) Advanced Network Technologies and Intelligent Computing. ANTIC 2021. Communications in Computer and Information Science, vol 1534. Springer, Cham. https://doi.org/10.1007/978-3-030-96040-7_16

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  • DOI: https://doi.org/10.1007/978-3-030-96040-7_16

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