  Data collected and transmitted by Internet of things (IoT) devices are
typically used for control and monitoring purposes; and hence, their timely
delivery is of utmost importance for the underlying applications. However, IoT
devices operate with very limited energy sources, severely reducing their
ability for timely collection and processing of status updates. IoT systems
make up for these limitations by employing multiple low-power low-complexity
devices that can monitor the same signal, possibly with different quality
observations and different energy costs, to create diversity against the
limitations of individual nodes. We investigate policies to minimize the
average age of information (AoI) in a monitoring system that collects data from
two sources of information denoted as primary and backup sources, respectively.
We assume that each source offers a different trade-off between the AoI and the
energy cost. The monitoring node is equipped with a finite size battery and
harvests ambient energy. For this setup, we formulate the scheduling of status
updates from the two sources as a Markov decision process (MDP), and obtain a
policy that decides on the optimal action to take (i.e., which source to query
or remain idle) depending on the current energy level and AoI. The performance
of the obtained policy is compared with an aggressive policy for different
system parameters. We identify few types of optimal solution structures and
discuss the benefits of having a backup source of information in the system.
