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In this work, we consider a real-time IoT monitoring system in which anenergy harvesting sensor with a finite-size battery measures a physical processand transmits the status updates to an aggregator. The aggregator, equippedwith caching capabilities, can serve the external requests of a destinationnetwork with either a stored update or a fresh update from the sensor. Weassume the destination network acts as a gossiping network in which the updatepackets are forwarded among the nodes in a randomized setting. We utilize theMarkov Decision Process framework to model and optimize the network's averageVersion Age of Information (AoI) and obtain the optimal policy at theaggregator. The structure of the optimal policy is analytically demonstratedand numerically verified. Numerical results highlight the effect of the systemparameters on the average Version AoI. The simulations reveal the superiorperformance of the optimal policy compared to a set of baseline policies.

Version Age-Optimal Cached Status Updates in a Gossiping Network with Energy Harvesting Sensor