  We consider status updating under inexact knowledge of the battery level of
an energy harvesting (EH) sensor that sends status updates about a random
process to users via a cache-enabled edge node. More precisely, the control
decisions are performed by relying only on the battery level knowledge captured
from the last received status update packet. Upon receiving on-demand requests
for fresh information from the users, the edge node uses the available
information to decide whether to command the sensor to send a status update or
to retrieve the most recently received measurement from the cache. We seek for
the best actions of the edge node to minimize the average AoI of the served
measurements, i.e., average on-demand AoI. Accounting for the partial battery
knowledge, we model the problem as a partially observable Markov decision
process (POMDP), and, through characterizing its key structures, develop a
dynamic programming algorithm to obtain an optimal policy. Simulation results
illustrate the threshold-based structure of an optimal policy and show the
gains obtained by the proposed optimal POMDP-based policy compared to a
request-aware greedy (myopic) policy.
