  Joint design of control and communication in Wireless Networked Control
Systems (WNCS) is a promising approach for future wireless industrial
applications. In this context, Age of Information (AoI) has been increasingly
utilized as a metric that is more representative than latency in the context of
systems with a sense-compute-actuate cycle. Nevertheless, AoI is commonly
defined for a single communication direction, Downlink or Uplink, which does
not capture the closed-loop dynamics. In this paper, we extend the concept of
AoI by defining a new metric, Age of Loop (AoL), relevant for WNCS closed-loop
systems. The AoL is defined as the time elapsed since the piece of information
causing the latest action or state (depending on the selected time origin) was
generated. We then use the proposed metric to learn the WNCS latency and
freshness bounds and we apply such learning methodology to minimize the long
term WNCS cost with the least amount of bandwidth. We show that, using the AoL,
we can learn the control system requirement and use this information to
optimize network resources.
