A new approach for power management in sensor node based on reinforcement learning

Wireless sensor networks are composed of small nodes with limited battery life and computational ability. Energy reduction in these networks is an important issue to extend network lifetime. Dynamic power management is a technique to conserve energy. DPM uses dynamic programming to manage power in sensor nodes. This approach is model based and exploiting it in a multi hop scenario is difficult. In this paper, we propose RLPM which is based on reinforcement learning. It is model free and easily applicable in both single hop and multi hop scenario. Experiments show that RLPM behaves similar to DPM while it does not have those constraints of DPM.