IDEAS home Printed from https://ideas.repec.org/a/bjb/journl/v14y2025i7p704-712.html
   My bibliography  Save this article

Intelligent Route Adaptation in Manets Using AI Techniques for Scalable Network Performance

Author

Listed:
  • Sachin Chaudhary

    (School of Computer Science and Applications, IFTM University, Moradabad U.P India)

  • Dr. Lalit Johari

    (School of Computer Science and Applications, IFTM University, Moradabad U.P India)

Abstract

Mobile Ad Hoc Networks (MANETs) are prone to frequent topology changes and scalability issues due to their decentralized and mobile nature. As network size and node mobility increase, traditional routing protocols become inefficient, leading to degraded network performance. This paper introduces a novel AI-driven approach to route optimization that enables MANETs to self-adjust to dynamic conditions. The proposed method leverages machine learning algorithms to analyze real-time mobility patterns and link quality, allowing for predictive route selection and rapid reconfiguration. By dynamically adapting to varying network states, the system significantly enhances scalability, reduces latency, and improves packet delivery. Experimental results demonstrate that the AI-based model consistently outperforms conventional routing protocols under diverse network scenarios, making it a promising solution for future mobile and mission-critical applications.

Suggested Citation

  • Sachin Chaudhary & Dr. Lalit Johari, 2025. "Intelligent Route Adaptation in Manets Using AI Techniques for Scalable Network Performance," International Journal of Latest Technology in Engineering, Management & Applied Science, International Journal of Latest Technology in Engineering, Management & Applied Science (IJLTEMAS), vol. 14(7), pages 704-712, July.
    • Handle: RePEc:bjb:journl:v:14:y:2025:i:7:p:704-712
    as

    Download full text from publisher

    File URL: https://www.ijltemas.in/DigitalLibrary/Vol.14Issue7/704-712.pdf
    Download Restriction: no
    File URL: https://www.ijltemas.in/papers/volume-14-issue-7/704-712.html
    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:bjb:journl:v:14:y:2025:i:7:p:704-712. 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: Dr. Pawan Verma (email available below). General contact details of provider: https://www.ijltemas.in/ .

    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.