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.
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Mili, R., Chikhi, S. (2019). Reinforcement Learning Based Routing Protocols Analysis for Mobile Ad-Hoc Networks. In: Renault, É., Mühlethaler, P., Boumerdassi, S. (eds) Machine Learning for Networking. MLN 2018. Lecture Notes in Computer Science(), vol 11407. Springer, Cham. https://doi.org/10.1007/978-3-030-19945-6_17
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DOI: https://doi.org/10.1007/978-3-030-19945-6_17
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