EEERP-RL: Enhanced energy-efficient routing protocol based on reinforcement learning for wireless sensor network

Wireless Sensor Networks (WSN) efficiently monitors and record environmental conditions, transmitting this data to central locations via widely distributed, sensor nodes. One major challenge in WSN involves creating an energy-efficient routing protocol that minimizes energy consumption and extends the network's longevity. In this paper, we propose EEERP-RL, an enhanced energy-efficient QoS routing protocol for WSNs, based on reinforcement learning (RL). The proposed protocol has been compared with two other protocols to determine which one gives the best performance in the network OSPF and SDN-Q. There is an investigation of packet delivery ratios and delays (m), as well as the impact of alive nodes, dead nodes, and energy consumption. Based on simulation results, the proposed protocol outperforms as compared to existing protocol in terms of different network traffic loads and node mobility.