Title: Machine learning-based routing protocols for wireless sensor

Authors: Ravi Kumar

Addresses: Department of ECE, Jaypee University of Engineering and Technology, Guna, 473226, Madhya Pradesh, India

Abstract: An important part of intelligent transportation systems (ITS) is the use of car ad hoc networks, or vehicular ad hoc networks (VANET). There are still a lot of security issues with VANETs, including catastrophic blackhole threats, even though they have a lot of benefits. The deep-learning-based secure routing (DLSR) protocol and the deep-learning-based clustering (DLC) protocol are the part of this work. The DLSR protocol uses deep learning (DL) at each node to decide between secure routing and normal routing. It also builds safe routes at the same time. It's also possible to find out what bad nodes are doing, which helps us choose the best next hop based on how well its fitness function works. To make the fitness function better in both the protocols, we build a deep neural network (DNN) model. The proposed system improves the localisation accuracy.

Keywords: routing protocol; WSN; wireless sensor network; machine learning; deep learning.

DOI: 10.1504/IJMNDI.2024.144005

International Journal of Mobile Network Design and Innovation, 2024 Vol.11 No.2, pp.88 - 93

Received: 10 May 2024
Accepted: 29 Aug 2024
Published online: 20 Jan 2025 *

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