IDEAS home Printed from https://ideas.repec.org/a/igg/jwltt0/v16y2021i4p96-116.html
   My bibliography  Save this article

OCC: A Hybrid Multiprocessing Computing Service Decision Making Using Ontology System

Author

Listed:
  • Ashish Tiwari

    (National Institute of Technology, Kurukshetra, India)

  • Rajeev Mohan Sharma

    (National Institute of Technology, Kurukshetra, India)

Abstract

In the recent trends, cloud computing service users agreed on the concept of pay and use model by accessing all the best services provided by the providers. The major problem here is that there is no standardization so that not everyone coming into the same platform. Now cloud computing efficiently uses time, cost, and effort. In this internet, speed is playing an important role. With the development of each and every field with its proper limitations, the researchers come into the picture that the ontology concept is playing a vital role in the field of computing. The key role of ontology is supporting the knowledge sharing activities. It is giving the set of criteria to prove the use of ontology in the computing world. In the design and development of ontology for computing and mathematics, the information from data centers is very important. The selected design and decisions give efficient and effective results to prove how ontology is playing a vital role in the computing system.

Suggested Citation

  • Ashish Tiwari & Rajeev Mohan Sharma, 2021. "OCC: A Hybrid Multiprocessing Computing Service Decision Making Using Ontology System," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), IGI Global Scientific Publishing, vol. 16(4), pages 96-116, July.
  • Handle: RePEc:igg:jwltt0:v:16:y:2021:i:4:p:96-116
    as

    Download full text from publisher

    File URL: https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/IJWLTT.20210701.oa6
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sam Goundar & Akashdeep Bhardwaj, 2018. "Efficient Fault Tolerance on Cloud Environments," International Journal of Cloud Applications and Computing (IJCAC), IGI Global, vol. 8(3), pages 20-31, July.
    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. Qayyum, Abdul & Razzak, Imran & Malik, Aamir Saeed & Anwar, Sajid, 2021. "Fusion of CNN and sparse representation for threat estimation near power lines and poles infrastructure using aerial stereo imagery," Technological Forecasting and Social Change, Elsevier, vol. 168(C).

    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:jwltt0:v:16:y:2021:i:4:p:96-116. 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: 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.