학술논문

Routing of Data Between the Nodes in Mobile Adhoc Networks using Machine Learning Modelling
Document Type
Conference
Source
2022 International Conference on Electronics and Renewable Systems (ICEARS) Electronics and Renewable Systems (ICEARS), 2022 International Conference on. :1404-1408 Mar, 2022
Subject
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Renewable energy sources
Costs
Machine learning
Routing
Throughput
Control systems
Data models
overhead control
genetic algorithm
Language
Abstract
The routing of data between the packets in mobile adhoc networks has severe limitations that involves communication and computational overhead, which has to be reduced for effective transmission of data packets. In this paper, we develop a machine learning assisted routing mechanism that has three different modules to serve the purpose of reduced overhead during routing. The study uses genetic algorithm to resolve the routing constraints between the source and destination nodes. The modelling is specifically designed to overcome the limitations associated with the generation of overheads. The simulation is conducted to test the efficacy of the models against various existing mechanisms. The results of simulation shows that the proposed method achieves higher rate of packet delivery rate, throughput and reduced delay.