Timely Monitoring of Dynamic Sources With Observations From Multiple Wireless Sensors

Age of Information (AoI) has recently received much attention due to its relevance for IoT sensing and monitoring. In this paper, we consider the problem of minimizing the AoI in a system in which a set of sources are observed by multiple sensors in a many-to-many relationship, and the probability that a sensor observes a source depends on the source's state. This model represents many practical scenarios, such as when multiple cameras or microphones are deployed to monitor objects moving in certain areas. We formulate the scheduling problem as a Markov Decision Process, and show how the age-optimal scheduling policy can be obtained. We further consider partially observable variants of the problem, and devise approximate policies for large state spaces. The evaluations show that the approximate policies work well in the considered scenarios, while the fact that sensors can observe multiple sources is beneficial, especially when there is high uncertainty of the source states.