Information freshness in IoT-based status update systems has recently been studied through the Age of Information (AoI) and Peak AoI (PAoI) performance metrics. In this article, we study a discrete-time server arising in multisource IoT systems, which accepts incoming information packets from multiple information sources so as to be forwarded to a remote monitor for status update purposes. Under the assumption of Bernoulli information packet arrivals and a common general discrete phase-type service time distribution across all the sources, we numerically obtain the exact per-source distributions of AoI and PAoI in matrix-geometric form for three different queueing disciplines: 1) nonpreemptive bufferless; 2) preemptive bufferless; and 3) nonpreemptive single buffer with replacement. The proposed numerical algorithm employs the theory of discrete-time Markov chains of quasi-birth-death type and is matrix analytical. Numerical examples are provided to validate the accuracy and effectiveness of the proposed queueing model. We also present a numerical example on the optimum choice of the Bernoulli parameters in a practical IoT system with two sources with diverse AoI requirements.

Analytical modeling of Age of Information (AoI) and Peak AoI (PAoI) has recently drawn a lot of attention in the context of quantitative assessment of information freshness in status update systems. In this paper, we study a probabilistically preemptive bufferless M/PH/1/1 queue fed with information update packets from$N$separate information sources for which a new information packet arrival from source-$m$is allowed to preempt a packet from source-$n$in service, with a probability depending on$n$and$m$. To make the model even more general than the existing ones, we assume a distinct phase-type (PH-type) service time distribution, a distinct packet error and retransmission probability, for each of the information sources. Using sample path arguments and the theory of Markov Fluid Queues (MFQ), the exact distributions of the AoI and PAoI are numerically obtained for each of the sources. Numerical examples are provided to demonstrate the impact of various system parameters on AoI performance. In the context of a two-source system, we present a methodology on how to optimally choose the preemption probabilities and packet generation rates so as to minimize certain AoI-oriented cost functions.

Bufferless and single-buffer queueing systems have recently been shown to be effective in coping with escalated Age of Information (AoI) figures arising in single-source status update systems with large buffers and FCFS scheduling. In this paper, for the single-source scenario, we propose a numerical algorithm for obtaining the exact distributions of both the AoI and the peak AoI (PAoI) in (i) the bufferless PH/PH/1/1/P(p) queue with probabilistic preemption with preemption probability p, 0 ≤ p ≤ 1, and (ii) the single buffer M/P H/1/2/R(r) queue with probabilistic replacement of the packet in the queue by the new arrival with replacement probability r, 0 ≤ r ≤ 1. The proposed exact models are based on the well-established theory of Markov Fluid Queues (MFQ) and the numerical algorithms are matrix-analytical and they rely on numerically stable and efficient vector-matrix operations. Moreover, the obtained exact distributions are in matrix exponential form, making it amenable to calculate the tail probabilities and the associated moments straightforwardly. Firstly, we validate the accuracy of the proposed method with simulations, and for sume sub-cases, with existing closed-form results. We then comparatively study the AoI performance of the queueing systems of interest under varying traffic parameters.