The Fourier-series method for inverting transforms of probability distributions
Queueing Systems: Theory and Applications - Numerical computations in queues
Analysis of a nonpreemptive priority queue with SPP arrivals of high class
Performance Evaluation
Computing distributions and moments in polling models by numerical transform inversion
Performance Evaluation
Systems of functional equations
Random Structures & Algorithms - Special issue: average-case analysis of algorithms
Numerical inversion of multidimensional Laplace transforms by the Laguerre method
Performance Evaluation
Discrete-time multiserver queues with priorities
Performance Evaluation
Asymptotics for M/G/1 low-priority waiting-time tail probabilities
Queueing Systems: Theory and Applications
Tail probabilities of low-priority waiting times and queue lengths in {MAP}/{GI}/1 queues
Queueing Systems: Theory and Applications
Many-Sources Delay Asymptotics with Applications to Priority Queues
Queueing Systems: Theory and Applications
INFOCOM '95 Proceedings of the Fourteenth Annual Joint Conference of the IEEE Computer and Communication Societies (Vol. 2)-Volume - Volume 2
Performance analysis of a single-server ATM queue with a priority scheduling
Computers and Operations Research
A Unified Framework for Numerically Inverting Laplace Transforms
INFORMS Journal on Computing
On priority queues with priority jumps
Performance Evaluation
On the numerical inversion of busy-period related transforms
Operations Research Letters
Controlling the delay trade-off between packet flows using multiple reserved places
Performance Evaluation
Exact tail asymptotics in a priority queue--characterizations of the preemptive model
Queueing Systems: Theory and Applications
Performance analysis of priority queueing systems in discrete time
Network performance engineering
Exact tail asymptotics in a priority queue--characterizations of the non-preemptive model
Queueing Systems: Theory and Applications
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Obtaining (tail) probabilities from a transform function is an important topic in queueing theory. To obtain these probabilities in discrete-time queueing systems, we have to invert probability generating functions, since most important distributions in discrete-time queueing systems can be determined in the form of probability generating functions. In this paper, we calculate the tail probabilities of two particular random variables in discrete-time priority queueing systems, by means of the dominant singularity approximation. We show that obtaining these tail probabilities can be a complex task, and that the obtained tail probabilities are not necessarily exponential (as in most `traditional' queueing systems). Further, we show the impact and significance of the various system parameters on the type of tail behavior. Finally, we compare our approximation results with simulations.