Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/67
Title: Reinforcement Learning Based Routing Protocols Analysis for Mobile Ad-Hoc Networks
Authors: Mili, Redha 
Chikhi, Salim 
Affiliations: Faculty of Information and Communication Technology (ICT) 
Faculty of Information and Communication Technology (ICT) 
Keywords: Reinforcement learning;Ad-hoc Network;Q-Learning;Energy AODV;MANETs
Date: 10-May-2019
Publisher: Springer, Cham
Related Publication(s): Machine Learning for Networking
Start page: 247
End page: 256
Conference: International Conference on Machine Learning for Networking 
Abstract: 
Energy consumption and maximize lifetime routing in Mobile Ad hoc Network (MANETs) is one of the most important issues. In our paper, we compare a global routing approach with a local routing approach both using reinforcement learning to maximize lifetime routing. We first propose a global routing algorithm based on reinforcement learning algorithm called Q-learning then we compare his results with a local routing algorithm called AODV-SARSA. Average delivery ratio, End to end delay and Time to Half Energy Depletion are used like metrics to compare both approach.
URI: http://dspace.univ-constantine2.dz/handle/123456789/67
ISBN: 9783030199456
DOI: https://doi.org/10.1007/978-3-030-19945-6
Appears in Collections:Conference Paper

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