Abstract
We investigate clusters of extremes defined as subsequent exceedances of high thresholds in a Lindley process. The latter is usually used to model the waiting time or the length of a queue in queuing systems. Distributions of the cluster and inter-cluster sizes of the Lindley process are obtained for a given value of the threshold assuming that the process begins from the zero value. An example of a M/M/1 queue and the impact of service and arrival rates on the cluster and inter-cluster distributions are shown.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
The latter theorem is valid for a process with \(\theta =0\) not necessarily the Lindley one irrespective on its stationary distribution and under specific mixing conditions.
References
Asmussen, S.: Subexponential asymptotics for stochastic processes: extremal behavior, stationary distributions and first passage probabilities. Ann. Appl. Probab. 8, 354–374 (1998)
Asmussen, S.: Applied Probability and Queues, 2nd edn. Springer, New York (2003). https://doi.org/10.1007/b97236
Bacro, J.-N., Daudin, J.-J., Mercier, S., Robin, S.: Back to the local score in the logarithmic case: a direct and simple proof. Ann. Inst. Stat. Math. 54(4), 748–757 (2002)
O’Brien, G.L.: Extreme values for stationary and Markov sequences. Ann. Probab. 15(1), 281–291 (1987)
Beirlant, J., Goegebeur, Y., Teugels, J., Segers, J.: Statistics of Extremes: Theory and Applications. Wiley, Chichester (2004)
Ferro, C.A.T., Segers, J.: Inference for clusters of extreme values. J. Roy. Stat. Soc. Ser. B 65, 545–556 (2003)
Hooghiemstra, G., Meester, L.E.: Computing the extremal index of special Markov chains and queues. Stoch. Process. Appl. 65(2), 171–185 (1996)
Hyytiä, E., Righter, R., Virtamo, J.: Meeting soft deadlines in single-and multi-server systems. In: Proceedings of 28th International Teletraffic Congress (ITC 28), Würzburg, Germany, pp. 166–174 (2016). https://doi.org/10.1109/ITC-28.2016.129
Leadbetter, M.R., Lingren, G., Rootzén, H.: Extremes and Related Properties of Random Sequence and Processes. Springer, Heidelberg (1983). https://doi.org/10.1007/978-1-4612-5449-2
Markovich, N.M.: Modeling clusters of extreme values. Extremes 17(1), 97–125 (2014)
Markovich, N.M.: Erratum to: modeling clusters of extreme values. Extremes 19(1), 139–142 (2016)
Markovich, N.M.: Clusters of extremes: modeling and examples. Extremes 20(3), 519–538 (2017)
Rootzén, H.: Maxima and exceedances of stationary Markov chains. Adv. Appl. Prob. 20, 371–390 (1988)
Acknowledgment
The reported study was funded by RFBR, project number 19-01-00090 (recipient N. Markovich, conceptualization, mathematical model development, methodology development).The reported study was funded by RFBR, project number 17-07-00142 (recipient R. Razumchik, formal/numerical analysis, validation).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Appendix
Appendix
Proof
The expression for \(E(T_2(x_{\rho }))\) (formula (15)) follows from the application of the generating function method. Let us denote by \(\mathcal {C}(z)\) — the probability generating function of Catalan numbers \(C_j\), i.e. \(\mathcal {C}(z)=\sum _{j=0}^\infty C_j z^j\), \(0<z<1/4\). It is known that \(\mathcal {C}(z)={1-\sqrt{1-4z}\over 2z}\). Since \(\mathcal {C}(z)\) satisfies the functional equation \(\mathcal {C}(z)=1+z \mathcal {C}(z)^2\), the derivative of \(\mathcal {C}(z)\) is equal to \(\mathcal {C}'(z)={\mathcal {C}(z)^2 \over 1 - 2 z \mathcal {C}(z)}\). Thus the value of \(E(T_2(x_\rho ))\) is equal to
Now we have
We also have
By putting everything together, we obtain
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Markovich, N., Razumchik, R. (2019). Cluster Modeling of Lindley Process with Application to Queuing. In: Vishnevskiy, V., Samouylov, K., Kozyrev, D. (eds) Distributed Computer and Communication Networks. DCCN 2019. Lecture Notes in Computer Science(), vol 11965. Springer, Cham. https://doi.org/10.1007/978-3-030-36614-8_25
Download citation
DOI: https://doi.org/10.1007/978-3-030-36614-8_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-36613-1
Online ISBN: 978-3-030-36614-8
eBook Packages: Computer ScienceComputer Science (R0)