MATEC Web Conf.
Volume 232, 20182018 2nd International Conference on Electronic Information Technology and Computer Engineering (EITCE 2018)
|Number of page(s)||6|
|Section||Circuit Simulation, Electric Modules and Displacement Sensor|
|Published online||19 November 2018|
Intelligent Routing Control for MANET Based on Reinforcement Learning
National Digital Switching System Engineering & Technology Research Centre, Zhengzhou 450000, China
* Corresponding author: firstname.lastname@example.org
With the rapid development and wide use of MANET, the quality of service for various businesses is much higher than before. Aiming at the adaptive routing control with multiple parameters for universal scenes, we propose an intelligent routing control algorithm for MANET based on reinforcement learning, which can constantly optimize the node selection strategy through the interaction with the environment and converge to the optimal transmission paths gradually. There is no need to update the network state frequently, which can save the cost of routing maintenance while improving the transmission performance. Simulation results show that, compared with other algorithms, the proposed approach can choose appropriate paths under constraint conditions, and can obtain better optimization objective.
© The Authors, published by EDP Sciences, 2018
This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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