IDEAS home Printed from https://ideas.repec.org/a/igg/jssmet/v7y2016i2p46-60.html
   My bibliography  Save this article

Replication and Resubmission Based Adaptive Decision for Fault Tolerance in Real Time Cloud Computing: A New Approach

Author

Listed:
  • Prasenjit Kumar Patra

    (Department of CSE, Bengal College of Engineering and Technology, Durgapur, India)

  • Harshpreet Singh

    (Department of CSE, Lovely Professional University, Phagwara, India)

  • Rajwinder Singh

    (Department of CSE, Lovely Professional University, Phagwara, India)

  • Saptarshi Das

    (Department of CSE, Saroj Mohan Institute of Technology, Guptipara, India)

  • Nilanjan Dey

    (Department of IT, Techno India College of Technology, Rajarhat, India)

  • Anghel Drugarin Cornelia Victoria

    (Department of Electrics and Informatics Engineering, “Eftimie Murgu” University of Resita, Resita, Romania)

Abstract

Cloud computing an adoptable technology is the upshot evolution of on demand service in the computing epitome of immense scale distributed computing. With the raising asks and welfares of cloud computing infrastructure, society can take leverage of intensive computing capability services and scalable, virtualized vicinity of cloud computing to carry out real time tasks executed on a remote cloud computing node. Due to the indeterminate latency and minimal control over computing node, sway the reliability factor. Therefore, there is a raise of requisite for fault tolerance to achieve reliability in the real time cloud infrastructure. In this paper, a model which provides fault tolerance named “Replication and resubmission based adaptive decision for fault tolerance in real-time cloud computing (RRADFTRC)” for real time cloud computing is projected with result. In the projected model, the system endure the faults and makes the adaptive decision on the basis of proper resource allocation of tasks with a new style of approach in real time cloud vicinity.

Suggested Citation

  • Prasenjit Kumar Patra & Harshpreet Singh & Rajwinder Singh & Saptarshi Das & Nilanjan Dey & Anghel Drugarin Cornelia Victoria, 2016. "Replication and Resubmission Based Adaptive Decision for Fault Tolerance in Real Time Cloud Computing: A New Approach," International Journal of Service Science, Management, Engineering, and Technology (IJSSMET), IGI Global, vol. 7(2), pages 46-60, April.
    • Handle: RePEc:igg:jssmet:v:7:y:2016:i:2:p:46-60
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSSMET.2016040104
    Download Restriction: no
    ---><---

    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:igg:jssmet:v:7:y:2016:i:2:p:46-60. 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: Journal Editor (email available below). General contact details of provider: https://www.igi-global.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.