Abstract
We study age of information in a status updating system that consists of a single sampler, i.e., source node, that sends time-sensitive status updates to a single monitor node through a server node. We first consider a Gilbert-Elliot service profile at the server node. In this model, service times at the server node follow a finite state Markov chain with two states: state and state where the server is faster in state . We determine the time average age experienced by the monitor node and characterize the age-optimal state transition matrix with and without an average cost constraint on the service operation. Next, we consider a Gilbert-Elliot sampling profile at the source. In this model, the interarrival times follow a finite state Markov chain with two states: state and state where samples are more frequent in state . We find the time average age experienced by the monitor node and characterize the age-optimal state transition matrix .
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