Prioritized Multistream Traffic in Uplink IoT Networks: Spatially Interacting Vacation Queues

Massive Internet of Things (IoT) is foreseen to introduce a plethora of applications for a fully connected world. Heterogeneous traffic is envisaged, where packets generated at each device should be differentiated and served according to their priority. This article develops a novel priority-aware spatiotemporal mathematical model to characterize massive IoT networks with uplink prioritized multistream traffic (PMT). Stochastic geometry is utilized to account for the macroscopic network-wide mutual interference between the coexisting devices. Discrete-time Markov chains (DTMCs) are employed to track the microscopic evolution of packets within each priority queue. To provide a systematic and tractable model, we decompose the prioritized queueing model at each device to a single-queue system with a server vacation. To this end, the IoT PMT network is modeled as spatially interacting vacation queues. Dedicated and shared channel priority-aware access strategies are presented. A priority-agnostic scheme is used as a benchmark to highlight the impact of prioritized uplink transmission on the performance of different priorities in terms of transmission probabilities and delays. Additional performance metrics as the average number of packets, the peak age of information, delay distribution, and Pareto frontiers for different parameters are presented, which give insights on the stable operation of uplink IoT networks with PMT.