Closed-Form Characterization of the MGF of AoI in Energy Harvesting Status Update Systems

This paper considers a real-time status update system in which an energy harvesting (EH)-powered transmitter node observes some physical process, and sends its sensed measurements the form of status updates to destination node. The harvested packets are assumed arrive at according independent Poisson processes, service time each is be exponentially distributed. We quantify xmlns:xlink="http://www.w3.org/1999/xlink">freshness updates when they reach using concept xmlns:xlink="http://www.w3.org/1999/xlink">Age Information (AoI) . Unlike most existing analyses AoI focusing on evaluation average value not subject constraints, our analysis focused understanding xmlns:xlink="http://www.w3.org/1999/xlink">distributional properties through characterization moment generating function (MGF). In particular, we use stochastic hybrid systems (SHS) framework derive closed-form expressions MGF under several queueing disciplines transmitter, including non-preemptive preemptive service/waiting strategies. Using these results, further obtain for first second moments discipline. demonstrate generality this by recovering results corresponding with no constraints as special cases new results. Our numerical verify analytical findings, necessity incorporating higher implementation/optimization rather than just relying value.