Green energy optimization in energy harvesting wireless sensor networks

This article studies the sensor activation control for the optimization of green energy utilization in an EH-WSN, where both energy generation and target distribution exhibit temporal and spatial diversities. Decentralized operation is considered for the green energy optimization in the EH-WSN. The optimization is achieved in two dimensions: dynamic (activation) mode adaptation in the temporal dimension and energy balancing in the spatial dimension. Due to the interactions among autonomous distributed sensors, game theory is applied to the local information based decentralized optimization for the spatial energy balancing problem. In addition, reinforcement learning techniques are proposed to address the temporal mode adaptation in the dynamic and unknown environment. Simulation results are provided to demonstrate the effectiveness of the proposed approaches.