Parameter Training in MANET using Artificial Neural Network

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Author(s)

Baisakhi Chatterjee 1,* Himadri Nath Saha 1

1. Computer Science & Engineering Department, Institute of Engineering and Management, Kolkata, City, 700 091, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijcnis.2019.09.01

Received: 10 Jun. 2019 / Revised: 15 Jul. 2019 / Accepted: 27 Aug. 2019 / Published: 8 Sep. 2019

Index Terms

Clustering, MANET, Artificial Intelligence, Artificial Neural Network

Abstract

The study of convenient methods of information dissemination has been a vital research area for years. Mobile ad hoc networks (MANET) have revolutionized our society due to their self-configuring, infrastructure-less decentralized modes of communication and thus researchers have focused on finding better and better ways to fully utilize the potential of MANETs. The recent advent of modern machine learning techniques has made it possible to apply artificial intelligence to develop better protocols for this purpose. In this paper, we expand our previous work which developed a clustering algorithm that used weight-based parameters to select cluster heads and use Artificial Neural Network to train a model to accurately predict the scale of the weights required for different network topologies.

Cite This Paper

Baisakhi Chatterjee, Himadri Nath Saha, "Parameter Training in MANET using Artificial Neural Network", International Journal of Computer Network and Information Security(IJCNIS), Vol.11, No.9, pp.1-8, 2019.DOI:10.5815/ijcnis.2019.09.01

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