IDEAS home Printed from https://ideas.repec.org/a/igg/jsita0/v10y2019i4p16-32.html
   My bibliography  Save this article

A Robust IOT-Cloud IaaS for Data Availability within Minimum Latency

Author

Listed:
  • Sarra Hammoudi

    (Ferhat Abbas University, Computer Science Department, Laboratory LRSD, Sétif, Algeria)

  • Saad Harous

    (College of Information Technology, United Arab Emirates University, Al Ain, UAE)

  • Zibouda Aliouat

    (Laboratory LRSD, University of Ferhat Abbas, Algeria)

Abstract

Sensors in Internet of Things generate a huge amount of data. The massive volume of the captured data is stored on cloud servers. Over time, the unbalanced load servers prevent better resource utilization. It also increases the input and the output response time. Hence, applying load balancing techniques is very important to achieve efficient system performance. Ensuring the critical data availability in such dynamic systems is very essential. In this article, the authors propose ROBUST for ensuring data availability mechanism and a fault-tolerance architecture. ROBUST also realises load balancing among servers within minimum latency, by avoiding the problem of the overloaded sites and unbalanced use of the resources on the servers. Comparing the response time using the ROBUST and Load Balancing in the Cloud Using Specialization (LBCS), ROBUST architecture has given satisfactory results in terms of critical data latency. Compared with LBCS, ROBUST gains 42% critical data recovery from a primary server and 45% when searching for duplicated critical data. The authors implemented the system using the JADE platform.

Suggested Citation

  • Sarra Hammoudi & Saad Harous & Zibouda Aliouat, 2019. "A Robust IOT-Cloud IaaS for Data Availability within Minimum Latency," International Journal of Strategic Information Technology and Applications (IJSITA), IGI Global, vol. 10(4), pages 16-32, October.
  • Handle: RePEc:igg:jsita0:v:10:y:2019:i:4:p:16-32
    as

    Download full text from publisher

    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJSITA.2019100102
    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:jsita0:v:10:y:2019:i:4:p:16-32. 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.