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Massive Internet of Things (IoT) is foreseen to introduce plethora ofapplications for a fully connected world. Heterogeneous traffic is envisaged,where packets generated at each IoT device should be differentiated and servedaccording to their priority. This paper develops a novel priority-awarespatiotemporal mathematical model to characterize massive IoT networks withuplink prioritized multistream traffic (PMT). Particularly, stochastic geometryis utilized to account for the macroscopic network wide mutual interferencebetween the coexisting IoT devices. Discrete time Markov chains (DTMCs) areemployed to track the microscopic evolution of packets within each prioritystream at each device. To alleviate the curse of dimensionality, we decomposethe prioritized queueing model at each device to a single-queue system withserver vacation. To this end, the IoT network with PMT is modeled as spatiallyinteracting vacation queues. Interactions between queues, in terms of thepacket departure probabilities, occur due to mutual interference. Servicevacations occur to lower priority packets to address higher priority packets.Based on the proposed model, dedicated and shared channel access strategies fordifferent priority classes are presented and compared. The results show thatshared access provides better performance when considering the transmissionsuccess probability, queues overflow probability and latency.

Prioritized Multi-stream Traffic in Uplink IoT Networks: Spatially Interacting Vacation Queues