Prediction free energy neutral power management for energy harvesting wireless sensor nodes
Current power management mechanisms for energy harvesting wireless sensors typically rely on predicted information about the amount of energy that can be harvested in the future. However, such mechanisms suffer from inevitable prediction errors, which in turn degrade the overall performance in real implementations. To circumvent such problems, we propose a fundamental framework to efficiently manage the harvested energy in a prediction free manner. In particular, we theoretically derive a set of Budget Assigning Principles (BAPs) to maximize the amount of harvested energy that can be utilized by a sensor in the presence of battery energy storage inefficiencies, which in turn maximize the sensors performance level in terms of the sensors average duty cycle. A Prediction FREE Energy Neutral (P-FREEN) power management mechanism is then proposed to implement the BAPs based solely on current observed energy harvesting rate and battery residual energy level. The performance of P-FREEN is verified via theoretical analysis and extensive computer simulations using real life energy harvesting data sets.
prediction free power management energy harvesting wireless sensor networks