Scheduling Algorithms for Minimizing Age of Information in Wireless Broadcast Networks with Random Arrivals

Age of information is a newly proposed metric that captures the freshness of information at end-users. The age measures the amount of time that elapsed since the latest information was generated at a source. In this context, we study an age minimization problem over a wireless broadcast network to keep many users updated on timely information, where only one user can be served at a time. We formulate a Markov decision process (MDP) to find dynamic scheduling algorithms, with the purpose of minimizing the long-run average age. We show that an optimal scheduling algorithm for the MDP is a simple stationary switch type. However, the optimal scheduling algorithm is not easy to implement because of the MDP’s infinite state space. Using a sequence of finite-state approximate MDPs, we successfully develop both optimal off-line and on-line scheduling algorithms. We validate the algorithms via numerical studies, and surprisingly show that the performance of no-buffer networks is very close to that of networks with buffers.