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An adaptive energy-aware routing protocol for MANETs using the SARSA reinforcement learning algorithm

In MANETs (Mobile Ad-hoc NETworks), communicating nodes are powered by batteries which could not be re-charged in many practical usage scenarios. Hence, maximizing network lifetime is a critical optimization objective in routing protocols design for MANETs. To meet this objective, energy-consumption should be balanced among all mobile nodes. In this paper, we formulate the energy-aware route discovery problem in a reactive routing protocol as a Reinforcement Learning (RL) problem that we solve using the SARSA RL algorithm. We have implemented our proposed RL-model on the top of AODV a well-known reactive routing protocol for MANETs. Furthermore, we show through simulations the efficiency of our proposal, against an implementation of the Energy-Aware Probability routing protocol.