IDEAS home Printed from https://ideas.repec.org/a/spr/infosf/v14y2012i4d10.1007_s10796-011-9325-x.html
   My bibliography  Save this article

Economic model of a Cloud provider operating in a federated Cloud

Author

Listed:
  • Íñigo Goiri

    (Universitat Politecnica de Catalunya and Barcelona Supercomputing Center)

  • Jordi Guitart

    (Universitat Politecnica de Catalunya and Barcelona Supercomputing Center)

  • Jordi Torres

    (Universitat Politecnica de Catalunya and Barcelona Supercomputing Center)

Abstract

Resource provisioning in Cloud providers is a challenge because of the high variability of load over time. On the one hand, the providers can serve most of the requests owning only a restricted amount of resources, but this forces to reject customers during peak hours. On the other hand, valley hours incur in under-utilization of the resources, which forces the providers to increase their prices to be profitable. Federation overcomes these limitations and allows providers to dynamically outsource resources to others in response to demand variations. Furthermore, it allows providers with underused resources to rent them to other providers. Both techniques make the provider getting more profit when used adequately. Federation of Cloud providers requires having a clear understanding of the consequences of each decision. In this paper, we present a characterization of providers operating in a federated Cloud which helps to choose the most convenient decision depending on the environment conditions. These include when to outsource to other providers, rent free resources to other providers (i.e., insourcing), or turn off unused nodes to save power. We characterize these decisions as a function of several parameters and implement a federated provider that uses this characterization to exploit federation. Finally, we evaluate the profitability of using these techniques using the data from a real provider.

Suggested Citation

  • Íñigo Goiri & Jordi Guitart & Jordi Torres, 2012. "Economic model of a Cloud provider operating in a federated Cloud," Information Systems Frontiers, Springer, vol. 14(4), pages 827-843, September.
    • Handle: RePEc:spr:infosf:v:14:y:2012:i:4:d:10.1007_s10796-011-9325-x
    DOI: 10.1007/s10796-011-9325-x
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10796-011-9325-x
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10796-011-9325-x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sanjaya K. Panda & Indrajeet Gupta & Prasanta K. Jana, 0. "Task scheduling algorithms for multi-cloud systems: allocation-aware approach," Information Systems Frontiers, Springer, vol. 0, pages 1-19.
    2. Seokho Son & Kwang Mong Sim, 2015. "Adaptive and similarity-based tradeoff algorithms in a price-timeslot-QoS negotiation system to establish cloud SLAs," Information Systems Frontiers, Springer, vol. 17(3), pages 565-589, June.
    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. 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.
    5. Chulhwan Chris Bang, 2015. "Information systems frontiers: Keyword analysis and classification," Information Systems Frontiers, Springer, vol. 17(1), pages 217-237, February.
    6. Sanjaya K. Panda & Indrajeet Gupta & Prasanta K. Jana, 2019. "Task scheduling algorithms for multi-cloud systems: allocation-aware approach," Information Systems Frontiers, Springer, vol. 21(2), pages 241-259, April.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:infosf:v:14:y:2012:i:4:d:10.1007_s10796-011-9325-x. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.