  The freshness of status updates is imperative in mission-critical Internet of
things (IoT) applications. Recently, Age of Information (AoI) has been proposed
to measure the freshness of updates at the receiver. However, AoI only
characterizes the freshness over time, but ignores the freshness in the
content. In this paper, we introduce a new performance metric, Age of Changed
Information (AoCI), which captures both the passage of time and the change of
information content. Also, we examine the AoCI in a time-slotted status update
system, where a sensor samples the physical process and transmits the update
packets with a cost. We formulate a Markov Decision Process (MDP) to find the
optimal updating policy that minimizes the weighted sum of the AoCI and the
update cost. Particularly, in a special case that the physical process is
modeled by a two-state discrete time Markov chain with equal transition
probability, we show that the optimal policy is of threshold type with respect
to the AoCI and derive the closed-form of the threshold. Finally, simulations
are conducted to exhibit the performance of the threshold policy and its
superiority over the zero-wait baseline policy.
