IDEAS home Printed from https://ideas.repec.org/a/ids/ijnvor/v30y2024i3p257-281.html
   My bibliography  Save this article

Deep learning-based decision-making system for cooperative routing in wireless multimedia sensor network

Author

Listed:
  • M. Nagalingayya
  • Basavaraj S. Mathpati

Abstract

This research aims to present a deep belief network (DBN) based a technique for choosing the most suitable cooperative nodes. Additionally, constraints such as: 1) tri-level energy consumption of nodes (text at level 1 has a lower energy level than information; at level 2, which has a medium energy level for text, image and multimedia data; level 3: higher energy levels for high-definition pictures); 2) reliability; 3) delay are examined while sending multimedia data across the network. Making the right decision, a novel hybrid dragon integrated firefly (DIFF) schemes that integrate the ideas of firefly optimisation (FF) and dragonfly optimisation (DA) method is intended to adjust the optimal weight of DBN. The chosen scheme's efficiency is then compared to other traditional methods in terms of alive nodes, delay, residual energy, network lifespan and analysis method.

Suggested Citation

  • M. Nagalingayya & Basavaraj S. Mathpati, 2024. "Deep learning-based decision-making system for cooperative routing in wireless multimedia sensor network," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 30(3), pages 257-281.
    • Handle: RePEc:ids:ijnvor:v:30:y:2024:i:3:p:257-281
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=138491
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    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:ids:ijnvor:v:30:y:2024:i:3:p:257-281. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=22 .

    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.