Dynamic Scheduling for Minimizing AoI in Resource-Constrained Multi-Source Relaying Systems with Stochastic Arrivals
The paper considers a multi-source relaying status update system with stochastic arrivals and develops three scheduling policies to minimize the sum average age of information subject to transmission capacity and long-run average resource constraints. Namely, we provide these policies under two different scenarios regarding the knowledge of system statistics: known environment and unknown environment. For the known environment, a constrained Markov decision process approach and a drift-plus-penalty method are proposed, and for the unknown environment, a deep learning policy is developed. The structure of an optimal policy is analyzed, and simulation results are provided.