  We study cyclic scheduling for generate-at-will (GAW) multi-source status
update systems with heterogeneous service times and packet drop probabilities,
with the aim of minimizing the weighted sum age of information (AoI), called
system AoI, or the weighted sum peak AoI (PAoI), called system PAoI. In
particular, we obtain well-performing cyclic schedulers which can easily scale
to thousands of information sources and which also have low online
implementation complexity. The proposed schedulers are comparatively studied
against existing scheduling algorithms in terms of computational load and
system AoI/PAoI performance, to validate their effectiveness.
