Queuing Theory in Modern Technology, Areas Covered, and Challenges
DOI:
https://doi.org/10.54097/ddya1z44Keywords:
Queuing theory; computer optimization; server optimization; resource utilization; efficiency increased.Abstract
In the context of accelerated scientific and technological advancement, allocating resources and optimizing services have emerged as significant challenges for numerous industries. This paper aims to examine the potential applications of queuing theory in the context of modern technology. The paper commences with a summary of the fundamental concepts and definitions of queuing theory. Subsequently, the paper illustrates the implementation of queuing theory in a multitude of practical domains and its pivotal function in optimizing the distribution of resources and enhancing efficiency through the examination of illustrative examples. It has been demonstrated that queuing theory significantly improves system performance and resource utilization. However, it also presents a number of challenges, including those associated with modelling optimization, uncertainties and dynamic data. Integrating queuing theory with artificial intelligence and machine learning will facilitate its expanded role in multidisciplinary operations and real-time data processing, thereby providing crucial support for advancing modern science and technology. The research in this paper can provide appreciation for researchers in related fields to better understand or apply queuing theory.
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[1] Mas, L., Vilaplana, J., Mateo, J., & Solsona, F. (2022). A queuing theory model for fog computing. The Journal of Supercomputing, 78(8), 11138-11155.
[2] Afolalu, S. A., Ikumapayi, O. M., Abdulkareem, A., Emetere, M. E., & Adejumo, O. (2021). A short review on queuing theory as a deterministic tool in sustainable telecommunication system. Materials Today: Proceedings, 44, 2884-2888.
[3] Proudlove, N. C. (2020). The 85% bed occupancy fallacy: The use, misuse and insights of queuing theory. Health services management research, 33(3), 110-121.
[4] Olu, O. T. (2019). Application of queuing theory to a bank’s automated teller machine (ATM) service optimization. Mathematics Letters, 5(1), 8-12.
[5] Yu, P., Zhou, F., Zhang, X., Qiu, X., Kadoch, M., & Cheriet, M. (2020). Deep learning-based resource allocation for 5G broadband TV service. IEEE Transactions on Broadcasting, 66(4), 800-813.
[6] Harahap, E., Darmawan, D., Fajar, Y., Ceha, R., & Rachmiatie, A. (2019, March). Modeling and simulation of queue waiting time at traffic light intersection. In Journal of Physics: Conference Series (Vol. 1188, No. 1, p. 012001). IOP Publishing.
[7] Li, Y., Chen, H., & Feng, M. (2020, December). A novel model for the traffic of urban roads based on queuing theory. In 2020 International Conference on Intelligent Computing, Automation and Systems (ICICAS) (pp. 190-194). IEEE.
[8] Wang, P., Zhao, J., Gao, Y., Sotelo, M. A., & Li, Z. (2020). Lane work-schedule of toll station based on queuing theory and PSO-LSTM model. Ieee Access, 8, 84434-84443.
[9] Hu, J., Hu, G., Cai, J., Xu, L., & Wang, Q. (2020). Hospital Bed Allocation Strategy Based on Queuing Theory during the COVID-19 Epidemic. Computers, Materials & Continua.
[10] Rece, L., Vlase, S., Ciuiu, D., Neculoiu, G., Mocanu, S., & Modrea, A. (2022). Queueing Theory-Based Mathematical Models Applied to Enterprise Organization and Industrial Production Optimization. Mathematics, 10(14), 2520.
[11] Wortsman, M., Ilharco, G., Gadre, S. Y., Roelofs, R., Gontijo-Lopes, R., Morcos, A. S., ... & Schmidt, L. (2022, June). Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time. In International conference on machine learning (pp. 23965-23998). PMLR.
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