Age of information: Design and analysis of optimal scheduling algorithms

Age of information is a newly proposed metric that captures delay from an application layer perspective. The age measures the amount of time that elapsed from the moment the mostly recently received update was generated until the present time. In this paper, we study an age minimization problem over a wireless broadcast network with many users, where only one user can be served at a time. We formulate a Markov decision process (MDP) to find dynamic transmission scheduling schemes, with the purpose of minimizing the long-run average age. While showing that an optimal scheduling algorithm for the MDP is a simple stationary switch-type, we propose a sequence of finite-state approximations for our infinite-state MDP and prove its convergence. We then propose both optimal off-line and online scheduling algorithms for the finite-approximate MDPs, depending on knowledge of time-varying arrivals.