Wireless scheduling for information freshness and synchrony: Drift-based design and heavy-traffic analysis

We consider the problem of scheduling in wireless networks with the aim of maintaining up-to-date and synchronized (also called, aligned) information at the receiver across multiple flows. This is in contrast to the more conventional approach of scheduling for optimizing long-term performance metrics such as throughput, fairness, or average delay. Maintaining the age of information at a low and roughly equal level is particularly important for distributed cyber-physical systems, in which the effectiveness of the control decisions depends critically on the freshness and synchrony of information from multiple sources/sensors. In this work, we first expose the weakness of several popular MaxWeight scheduling solutions that utilize queue-length, delay, and age information as their weights. Then, we develop a novel age-based scheduler that combines age with the interarrival times of incoming packets in its decisions, which yields significant gains in the information freshness at the receiver. We characterize the performance of our strategy through a heavy-traffic analysis that establishes upper and lower bounds on the freshness of system information.