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We consider status updating under inexact knowledge of the battery level ofan energy harvesting (EH) sensor that sends status updates about a randomprocess to users via a cache-enabled edge node. More precisely, the controldecisions are performed by relying only on the battery level knowledge capturedfrom the last received status update packet. Upon receiving on-demand requestsfor fresh information from the users, the edge node uses the availableinformation to decide whether to command the sensor to send a status update orto retrieve the most recently received measurement from the cache. We seek forthe best actions of the edge node to minimize the average AoI of the servedmeasurements, i.e., average on-demand AoI. Accounting for the partial batteryknowledge, we model the problem as a partially observable Markov decisionprocess (POMDP), and, through characterizing its key structures, develop adynamic programming algorithm to obtain an optimal policy. Simulation resultsillustrate the threshold-based structure of an optimal policy and show thegains obtained by the proposed optimal POMDP-based policy compared to arequest-aware greedy (myopic) policy.

Status Updating with an Energy Harvesting Sensor under Partial Battery Knowledge