Abstract
We consider the infinite-server queueing tandem with the Markovian arrival process. The service time of requests at the first stage and the probability of their transition to the second stage are determined by the type of request that corresponds to the state of the arrival process at the time when the request arrived. A study of this system was performed under an asymptotic condition of a high rate of arrivals. A Gaussian approximation is obtained for the joint stationary probability distribution of the number of requests at the stages of the system under the condition. Based on this approximation, the problem of computing the optimal number of servers for specific values of model parameters is solved. Further, the obtained asymptotic result is extended to the case when a service at the second stage also depends on the request type, as well as on the case of systems with the number of stages greater than two.
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References
Atar, R., Mandelbaum, A., & Reiman, M. (2004). Scheduling a multi class queue with many exponential servers: Asymptotic optimality in heavy traffic. The Annals of Applied Probability, 14(3), 1084–1134.
Barron, Y., Perry, D., & Stadje, W. (2016). A make-to-stock production/inventory model with MAP arrivals and phase-type demands. Annals of Operations Research, 241, 373–409.
Blom, J., De Turck, K., & Mandjes, M. (2015). Analysis of Markov-modulated infinite-server queues in the central-limit regime. Probability in the Engineering and Informational Sciences, 29(3), 433–459.
Blom, J., Kella, O., Mandjes, M., & Thorsdottir, H. (2014). Markov-modulated infinite-server queues with general service times. Queueing Systems, 76(4), 403–424.
Boxma, O. (1984). \(M/G/\infty \) tandem queues. Stochastic Processes and their Applications, 18, 153–164.
Brandt, A. (1989). On the \(GI/M/\infty \) service system with batch arrivals and different types of service distributions. Queueing Systems, 4, 351–365.
Chakravarthy, S. (2010). Markovian arrival processes. Wiley Encyclopedia of Operations Research and Management Science.
Cochrana, J., & Rocheb, K. (2009). A multi-class queuing network analysis methodology for improving hospital emergency department performance. Computers and Operations Research, 36(5), 1497–1512.
D’Auria, B. (2007). Stochastic decomposition of the \(M/G/\infty \) queue in a random environment. Operations Research Letters, 35(6), 805–812.
Jansen, H., Mandjes, M., De Turck, K., & Wittevrongel, S. (2016). A large deviations principle for infinite-server queues in a random environment. Queueing Systems, 82, 199–235.
Kim, C., Dudin, A., Dudin, S., & Dudina, O. (2014). Analysis of \(MMAP/PH_1, PH_2/N/\infty \) queueing system operating in a random environment. International Journal Applied Mathematics and Computer Science, 24(3), 485–501.
Kim, C., Dudin, A., Dudin, S., & Dudina, O. (2016). Hysteresis control by the number of active servers in queueing system \(MMAP/PH/N\) with priority service. Performance Evaluation, 101, 20–33.
Klimenok, V., & Savko, R. (2013). A retrial tandem queue with two types of customers and reservation of channels. Communications in Computer and Information Science, 356, 105–114.
Kolmogorov, A. (1933). Sulla determinazione empirica di una legge di distribuzione. Giornale dell’ Intituto Italiano degli Attuari, 4, 83–91.
Krishnamoorthy, A., Jaya, S., & Lakshmy, B. (2015). Queues with interruption in random environment. Annals of Operations Research, 233, 201–219.
Moiseev, A., & Nazarov, A. (2014). Asymptotic analysis of a multistage queuing system with a high-rate renewal arrival process. Optoelectronics, Instrumentation and Data Processing, 50(2), 163–171.
Moiseev, A., & Nazarov, A. (2016). Queueing network \(MAP-(GI/\infty )^K\) with high-rate arrivals. European Journal of Operational Research, 254, 161–168.
Morozov, E., & Phung-Duc, T. (2017). Stability analysis of a multiclass retrial system with classical retrial policy. Performance Evaluation, 112, 15–26.
Nazarov, A., & Baymeeva, G. (2014). The \(M/G/\infty \) queue in random environment. Communications in Computer and Information Science, 487, 312–324.
Nazarov, A., Moiseev, A. (2013). Calculation of the probability that a Gaussian vector falls in the hyperellipsoid with the uniform density. In International conference on Application of Information and Communication Technology and Statistics in Economy and Education (ICAICTSEE-2013), Sofia, pp. 519–526.
O’Cinneide, C., & Purdue, P. (1986). The \(M/M/\infty \) queue in a random environment. Journal of Applied Probability, 23(1), 175–184.
Pankratova, E., & Moiseeva, S. (2014). Queueing system \(MAP/M/\infty \) with \(n\) types of customers. Communications in Computer and Information Science, 487, 356–366.
Satyam, K., Krishnamurthy, A., & Kamath, M. (2013). Solving general multi-class closed queuing networks using parametric decomposition. Computers and Operations Research, 40(7), 1777–1789.
Winkler, A. (2013). Dynamic scheduling of a single-server two-class queue with constant retrial policy. Annals of Operations Research, 202, 197–210.
Zhang, H. (1999). A multi-class cyclic arrival queue with a single server. Annals of Operations Research, 87, 333–350.
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Moiseev, A., Shklennik, M. & Polin, E. Infinite-server queueing tandem with Markovian arrival process and service depending on its state. Ann Oper Res 326, 261–279 (2023). https://doi.org/10.1007/s10479-023-05318-1
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DOI: https://doi.org/10.1007/s10479-023-05318-1