  The evolution of fifth generation (5G) networks needs to support the latest
use cases, which demand robust network connectivity for the collaborative
performance of the network agents, like multi-robot systems and vehicle to
anything (V2X) communication. Unfortunately, the user device's limited
communication range and battery constraint confirm the unfitness of known
robustness metrics suggested for fixed networks, when applied to time-switching
communication graphs. Furthermore, the calculation of most of the existing
robustness metrics involves non-deterministic polynomial-time complexity, and
hence are best-fitted only for small networks. Despite a large volume of works,
the complete analysis of a $\textit{low-complexity}$ temporal robustness metric
for a communication network is absent in the literature, and the present work
aims to fill this gap. More in detail, our work provides a stochastic analysis
of network robustness for a massive machine type communication (mMTC) network.
The numerical investigation corroborates the exactness of the proposed
analytical framework for temporal robustness metric. Along with studying the
impact on network robustness of various system parameters, such as cluster head
(CH) probability, power threshold value, network size, and node failure
probability, we justify the observed trend of numerical results
probabilistically.
