IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/387083.html
   My bibliography  Save this article

A QoS-Satisfied Prediction Model for Cloud-Service Composition Based on a Hidden Markov Model

Author

Listed:
  • Qingtao Wu
  • Mingchuan Zhang
  • Ruijuan Zheng
  • Ying Lou
  • Wangyang Wei

Abstract

Various significant issues in cloud computing, such as service provision, service matching, and service assessment, have attracted researchers’ attention recently. Quality of service (QoS) plays an increasingly important role in the provision of cloud-based services, by aiming for the seamless and dynamic integration of cloud-service components. In this paper, we focus on QoS-satisfied predictions about the composition of cloud-service components and present a QoS-satisfied prediction model based on a hidden Markov model. In providing a cloud-based service for a user, if the user’s QoS cannot be satisfied by a single cloud-service component, component composition should be considered, where its QoS-satisfied capability needs to be proactively predicted to be able to guarantee the user’s QoS. We discuss the proposed model in detail and prove some aspects of the model. Simulation results show that our model can achieve high prediction accuracies.

Suggested Citation

  • Qingtao Wu & Mingchuan Zhang & Ruijuan Zheng & Ying Lou & Wangyang Wei, 2013. "A QoS-Satisfied Prediction Model for Cloud-Service Composition Based on a Hidden Markov Model," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-7, July.
    • Handle: RePEc:hin:jnlmpe:387083
    DOI: 10.1155/2013/387083
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2013/387083.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/MPE/2013/387083.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2013/387083?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
    ---><---

    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:hin:jnlmpe:387083. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.