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QGeo: Q-Learning-Based Geographic Ad Hoc Routing Protocol for Unmanned Robotic Networks - 2017

Research Area:  Mobile Ad Hoc Networks


This letter proposes a novel protocol that uses Q-learning-based geographic routing (QGeo) to improve the network performance of unmanned robotic networks. A rapid and reliable network is essential for the remote control and monitoring of mobile robotic devices. However, controlling the network overhead required for route selection and repair is still a notable challenge, owing to high mobility of the devices. To alleviate this problem, we propose a machine-learning-based geographic routing scheme to reduce network overhead in high-mobility scenarios. We evaluate the performance of QGeo in comparison with other methods using the NS-3 simulator. We find that QGeo has a higher packet delivery ratio and a lower network overhead than existing methods.

Author(s) Name:  Woo-Sung Jung,Jinhyuk Yim and Young-Bae Ko

Journal name:  IEEE Communications Letters

Conferrence name:  

Publisher name:  IEEE

DOI:  10.1109/LCOMM.2017.2656879

Volume Information:  Volume: 21, Issue: 10, Oct. 2017