Reinforcement Learning Based Routing Protocols Analysis for Mobile Ad-Hoc Networks Global Routing Versus Local Routing

摘要

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.