  Data aggregation is an efficient approach to handle the congestion introduced
by a massive number of machine type devices (MTDs). The aggregators not only
collect data but also implement scheduling mechanisms to cope with scarce
network resources. We use the concept of meta distribution (MD) of the
signal-to-interference ratio (SIR) to gain a complete understanding of the
per-link reliability and describe the performance of two scheduling methods for
data aggregation of machine type communication (MTC): random resource
scheduling (RRS) and channel-aware resource scheduling (CRS). The results show
the fraction of users in the network that achieves a target reliability, which
is an important aspect to consider when designing wireless systems with
stringent service requirements.
