IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0228086.html
   My bibliography  Save this article

Cost-aware orchestration of applications over heterogeneous clouds

Author

Listed:
  • Kena Alexander
  • Muhammad Hanif
  • Choonhwa Lee
  • Eunsam Kim
  • Sumi Helal

Abstract

The orchestration of applications and their components over heterogeneous clouds is recognized as being critical in solving the problem of vendor lock-in with regards to distributed and cloud computing. There have been recent strides made in the area of cloud application orchestration with emergence of the TOSCA standard being a definitive one. Although orchestration by itself provides a considerable amount of benefit to consumers of cloud computing services, it remains impractical without a compelling reason to ensure its utilization by cloud computing consumers. If there is no measurable benefit in using orchestration, then it is likely that clients may opt out of using it altogether. In this paper, we present an approach to cloud orchestration that aims to combine an orchestration model with a cost and policy model in order to allow for cost-aware application orchestration across heterogeneous clouds. Our approach takes into consideration the operating cost of the application on each provider, while performing a forward projection of the operating cost over a period of time to ensure that cost constraints remain unviolated. This allows us to leverage the existing state of the art with regards to orchestration and model-driven approaches as well as tie it to the operations of cloud clients in order to improve utility. Through this study, we were able to show that our approach was capable of providing not only scaling features but also orchestration features of application components distributed across heterogeneous cloud platforms.

Suggested Citation

  • Kena Alexander & Muhammad Hanif & Choonhwa Lee & Eunsam Kim & Sumi Helal, 2020. "Cost-aware orchestration of applications over heterogeneous clouds," PLOS ONE, Public Library of Science, vol. 15(2), pages 1-21, February.
    • Handle: RePEc:plo:pone00:0228086
    DOI: 10.1371/journal.pone.0228086
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0228086
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0228086&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0228086?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
    ---><---

    References listed on IDEAS

    as
    1. Jingqi Yang & Chuanchang Liu & Yanlei Shang & Bo Cheng & Zexiang Mao & Chunhong Liu & Lisha Niu & Junliang Chen, 2014. "A cost-aware auto-scaling approach using the workload prediction in service clouds," Information Systems Frontiers, Springer, vol. 16(1), pages 7-18, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shuai Yuan & Sanjukta Das & Ram Ramesh & Chunming Qiao, 2023. "Availability-Aware Virtual Resource Provisioning for Infrastructure Service Agreements in the Cloud," Information Systems Frontiers, Springer, vol. 25(4), pages 1495-1512, August.
    2. Ching-Hsien Hsu & Jianhua Ma & Mohammad S. Obaidat, 2014. "Dynamic intelligence towards merging cloud and communication services," Information Systems Frontiers, Springer, vol. 16(1), pages 1-5, March.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0228086. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.