  When making decisions in a network, it is important to have up-to-date
knowledge of the current state of the system. Obtaining this information,
however, comes at a cost. In this paper, we determine the optimal finite-time
update policy for monitoring the binary states of remote sources with a
reporting rate constraint. We first prove an upper and lower bound of the
minimal probability of error before solving the problem analytically. The error
probability is defined as the probability that the system performs differently
than it would with full system knowledge. More specifically, an error occurs
when the destination node incorrectly determines which top-K priority sources
are in the ``free'' state. We find that the optimal policy follows a specific
ordered 3-stage update pattern. We then provide the optimal transition points
for each stage for each source.
