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Economic aspects of hybrid cloud infrastructure: User organization perspective

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  • Oleksiy Mazhelis

    (University of Jyväskylä)

  • Pasi Tyrväinen

    (University of Jyväskylä)

Abstract

Adoption of cloud infrastructure promises enterprises numerous benefits, such as faster time-to-market and improved scalability enabled by on-demand provisioning of pooled and shared computing resources. In particular, hybrid clouds, by combining the private in-house capacity with the on-demand capacity of public clouds, promise to achieve both increased utilization rate of the in-house infrastructure and limited use of the more expensive public cloud, thereby lowering the total costs for a cloud user organization. In this paper, an analytical model of hybrid cloud costs is introduced, wherein the costs of computing and data communication are taken into account. Using this model, a cost-efficient division of the computing capacity between the private and the public portion of a hybrid cloud can be identified. By analyzing the model, it can be shown that, given fixed prices for private and public capacity, a hybrid cloud incurs the minimum costs. Furthermore, it is shown that, as the volume of data transferred to/from the public cloud increases, a greater portion of the capacity should be allocated to the private cloud. Finally, the paper illustrates analytically that, when the unit price of capacity declines with the volume of acquired capacity, a hybrid cloud may become more expensive than a private or a public cloud.

Suggested Citation

  • Oleksiy Mazhelis & Pasi Tyrväinen, 2012. "Economic aspects of hybrid cloud infrastructure: User organization perspective," Information Systems Frontiers, Springer, vol. 14(4), pages 845-869, September.
  • Handle: RePEc:spr:infosf:v:14:y:2012:i:4:d:10.1007_s10796-011-9326-9
    DOI: 10.1007/s10796-011-9326-9
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    References listed on IDEAS

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    Cited by:

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    2. Jason J. Jung & Yue-Shan Chang & Ying Liu & Chao-Chin Wu, 2012. "Advances in intelligent grid and cloud computing," Information Systems Frontiers, Springer, vol. 14(4), pages 823-825, September.
    3. Haoyi Xiong & Daqing Zhang & Daqiang Zhang & Vincent Gauthier & Kun Yang & Monique Becker, 2014. "MPaaS: Mobility prediction as a service in telecom cloud," Information Systems Frontiers, Springer, vol. 16(1), pages 59-75, March.
    4. John Oredo & Denis Dennehy, 2023. "Exploring the Role of Organizational Mindfulness on Cloud Computing and Firm Performance: The Case of Kenyan Organizations," Information Systems Frontiers, Springer, vol. 25(5), pages 2029-2050, October.
    5. Garrison, Gary & Wakefield, Robin L. & Kim, Sanghyun, 2015. "The effects of IT capabilities and delivery model on cloud computing success and firm performance for cloud supported processes and operations," International Journal of Information Management, Elsevier, vol. 35(4), pages 377-393.
    6. Wafa Bouaynaya, 2020. "Characterization of Cloud Computing Reversibility as Explored by the DELPHI Method," Information Systems Frontiers, Springer, vol. 22(6), pages 1505-1518, December.
    7. Haiying Ji & Yikai Liang, 2016. "Exploring the Determinants Affecting E-Government Cloud Adoption in China," International Journal of Business and Management, Canadian Center of Science and Education, vol. 11(4), pages 1-81, March.
    8. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.

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