Abstract: Delay-Tolerant Networking (DTN) or Disruptive-Tolerant Networking comes under the category of networks that works without infrastructure wireless networks. DTN is one type of computer network that provides solutions for several applications. Delay tolerant network communications are networks that are accomplished by storing packets briefly in intermediate nodes till a certain time an end-to-end route is been re-setup or regenerated. This leads to thought as Delay Tolerant Networks. The paper presents the developed models using Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) for predicting the best alpha, beta, and gamma parameters of Probabilistic Routing Protocol for Intermittently Connected Networks (PROPHET) protocol for delay tolerant networks. The first data set is generated using ONE simulator, and the generated data is analyzed using python panda’s module. From the above dataset, 80% was used for training and the remaining 20% each has been used for testing and validation. The models were developed and tested using the r2 score for both models to predict alpha, beta, and gamma parameters. Based on the predicted parameters extensive experiments were done and it was found that the ANN model is better than the CNN model. The ANN model can predict optimum alpha, beta, and gamma whereas CNN Model failed to produce accurate prediction.

Bonu Satish Kumar, Sailaja Vishnubhatla, Chevuru Madhu Babu and S. Pallam Shetty. “Performance Analysis of Prophet Routing Protocol in Delay Tolerant Network by using Machine Learning Models”. International Journal of Advanced Computer Science and Applications (IJACSA) 14.5 (2023). http://dx.doi.org/10.14569/IJACSA.2023.0140522

@article{Kumar2023,
title = {Performance Analysis of Prophet Routing Protocol in Delay Tolerant Network by using Machine Learning Models},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2023.0140522},
url = {http://dx.doi.org/10.14569/IJACSA.2023.0140522},
year = {2023},
publisher = {The Science and Information Organization},
volume = {14},
number = {5},
author = {Bonu Satish Kumar and Sailaja Vishnubhatla and Chevuru Madhu Babu and S. Pallam Shetty}
}