Age-of-Information Aware Scheduling under Markovian Energy Arrivals

We consider the task of scheduling updates from multiple sources to a central monitoring station via a shared communication channel. Each source harvests energy from nature to measure a time-varying quantity and report these measurements to the monitoring station. Prior work in this area focuses on the setting where energy arrivals are assumed to be independent across time. Motivated by the time-correlation in energy generated by many renewable energy sources, we use a Markov process to model the energy arrivals. The goal is to minimize the time average of the weighted sum of the ages-of-information of the sources. We use Whittle’s relaxation and propose a modification of the Whittle Index to design a scheduling policy. We show that our policy outperforms other natural policies via simulations.