Dynamic Scheduling for Minimizing AoI in Resource-Constrained
Multi-Source Relaying Systems with Stochastic Arrivals
Abstract
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.