EBR-RL: energy balancing routing protocol based on reinforcement learning for WSN

A Wireless Sensor Network (WSN) is a wireless network that monitors physical environment conditions through resource-constrained sensor nodes and delivers data to a sink node through the network. One of the most important constraints on sensor nodes is their limited power source, which consists of small and irreplaceable batteries. Energy conservation is thus a dominant factor in WSN. Therefore, when designing a routing protocol for WSNs, it is necessary to consider the energy constraint of sensor nodes. In this paper, we consider the energy constraint of sensor nodes and propose an Energy Balancing Routing Protocol using reinforcement learning. The performance of the proposed protocol is compared to other existing energy-efficient routing protocols and the results show that the proposed protocol performs better with regards to energy saving and network lifetime.