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Title: Time-Varying Queues
Service systems abound with queues, but the most natural direct models are often time-varying queues, which may require nonstandard analysis methods beyond stochastic textbooks. This paper provides an overview of time-varying queues. Most of the recent literature concerns many-server queues, which arise in large-scale service systems, such as in customer contact centers and hospital emergency departments, but there also has been some new work on single-server queues with time-varying arrivals, which arise in some settings, such as airplanes coming to land at an airport, cars coming to a traffic intersection and medical staff waiting for the availability of special operating rooms in a hospital. The understanding of many-server queues and single-server queues is enhanced by heavy-traffic limits, which have been extended to time-varying models as well as stationary models.
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Queueing models and service management
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National Science Foundation
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Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the official views of any of these organizations. REFERENCES [1] I. Obeid and J. Picone, “The Temple University Hospital EEG Data Corpus,” in Augmentation of Brain Function: Facts, Fiction and Controversy. Volume I: Brain-Machine Interfaces, 1st ed., vol. 10, M. A. Lebedev, Ed. Lausanne, Switzerland: Frontiers Media S.A., 2016, pp. 394 398. [2] V. Shah et al., “The Temple University Hospital Seizure Detection Corpus,” Frontiers in Neuroinformatics, vol. 12, pp. 1–6, 2018. [3] A. Hamid et, al., “The Temple University Artifact Corpus: An Annotated Corpus of EEG Artifacts.” in Proceedings of the IEEE Signal Processing in Medicine and Biology Symposium (SPMB), 2020, pp. 1-3. [4] Y. Roy, R. Iskander, and J. Picone, “The NeurekaTM 2020 Epilepsy Challenge,” NeuroTechX, 2020. [Online]. Available: [Accessed: 01-Dec-2021]. [5] S. Rahman, A. Hamid, D. 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