Analysis of Temporal Robustness in Massive Machine Type Communications

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