15-16 July 2021
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Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.
Evaluation of Agent-Network Environment Mapping on Open-AI Gym for Q-Routing Algorithm
Digital Object Identifier (DOI) : 10.14569/IJACSA.2021.0120652
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 12 Issue 6, 2021.
Abstract: The changes in network dynamics demands a routing algorithm that adapts intelligently with the changing requirements and parameters. In this regard, an efficient routing mechanism plays an essential role in supporting such requirements of dynamic and QoS-aware network services. This paper has introduced a self-learning intelligent approach to route selection in the network. A Q-Routing approach is designed based on a reinforcement learning algorithm to provide reliable and stable packet transmission for different network services with minimal delay and low routing overhead. The novelty of the proposed work is that a new customized environment for the network, namely Net-AI-Gym, has been integrated into Open-AI Gym. Besides, the proposed Q-routing with Net-AI-Gym offers optimization in exploring the path to support multi-QoS aware services in the different networking applications. The performance assessment of the NET-AI Gym is carried out with less, medium, and a high number of nodes. Also, the results of the proposed system are compared with the existing rule-based method. The study outcome shows the Net-AI-Gym's potential that effectively supports the varied scale of nodes in the network. Apart from this, the proposed Q-routing approach outperforms the rule-based routing technique regarding episodes vs. Rewards and path length.
Keywords: Reinforcement learning; environment; agent; network; Net-AI-Gym; Q-routing; rule-based routing
Varshini Vidyadhar and R. Nagaraja, “Evaluation of Agent-Network Environment Mapping on Open-AI Gym for Q-Routing Algorithm” International Journal of Advanced Computer Science and Applications(IJACSA), 12(6), 2021. http://dx.doi.org/10.14569/IJACSA.2021.0120652
@article{Vidyadhar2021,
title = {Evaluation of Agent-Network Environment Mapping on Open-AI Gym for Q-Routing Algorithm},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2021.0120652},
url = {http://dx.doi.org/10.14569/IJACSA.2021.0120652},
year = {2021},
publisher = {The Science and Information Organization},
volume = {12},
number = {6},
author = {Varshini Vidyadhar and R. Nagaraja}
}
