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Some asymptotic results for the transient distribution of the Halfin–Whitt diffusion process

Published online by Cambridge University Press:  20 February 2015

QIANG ZHEN
Affiliation:
Department of Mathematics and Statistics, University of North Florida, 1 UNF DR, Jacksonville, FL 32224, USA email: q.zhen@unf.edu
CHARLES KNESSL
Affiliation:
Department of Mathematics, Statistics, and Computer Science, University of Illinois at Chicago, 851 S. Morgan St.(M/C 249), Chicago, IL 60607, USA email: knessl@uic.edu

Abstract

We consider the Halfin–Whitt diffusion process Xd(t), which is used, for example, as an approximation to the m-server M/M/m queue. We use recently obtained integral representations for the transient density p(x,t) of this diffusion process, and obtain various asymptotic results for the density. The asymptotic limit assumes that a drift parameter β in the model is large, and the state variable x and the initial condition x0 (with Xd(0) = x0 > 0) are also large. We obtain some alternate representations for the density, which involve sums and/or contour integrals, and expand these using a combination of the saddle point method, Laplace method and singularity analysis. The results give some insight into how steady state is achieved, and how if x0 > 0 the probability mass migrates from Xd(t) > 0 to the range Xd(t) < 0, which is where it concentrates as t → ∞, in the limit we consider. We also discuss an alternate approach to the asymptotics, based on geometrical optics and singular perturbation techniques.

Type
Papers
Copyright
Copyright © Cambridge University Press 2015 

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References

[1]Abramowitz, M. & Stegun, I. A. (1972) Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables (Tenth Printing), Dover, New York.Google Scholar
[2]Bender, C. M. & Orszag, S. A. (1978) Advanced Mathematical Methods for Scientists and Engineers, McGraw-Hill, New York.Google Scholar
[3]Bleistein, N. & Handelsman, R. A. (1986) Asymptotic Expansions of Integrals, Dover, New York.Google Scholar
[4]Borst, S.Mandelbaum, A. & Reiman, M. (2004) Dimensioning large call centers. Oper. Res. 52, 1734.Google Scholar
[5]Brockmeyer, E.Halstrøm, H. L., & Jensen, A. (1948) The life and works of A. K. Erlang. Trans. Danish Acad. Tech. Sci. 2, 277.Google Scholar
[6]Dembo, A. & Zeitouni, O. (1993) Large Deviations Techniques and Applications, Jones and Bartlett, Boston.Google Scholar
[7]Flajolet, P. & Sedgcwick, R. (2009) Analytic Combinatorics, Cambridge University Press, Cambridge.Google Scholar
[8]Friedlin, M. A. & Wentzell, A. D. (1984) Random Perturbations of Dynamical Systems, Springer-Verlag, New York.Google Scholar
[9]Gamarnik, D. & Goldberg, D. A. (2013) On the rate of convergence to stationarity of the M/M/N queue in the Halfin–Whitt regime. Ann. Appl. Probab. 23, 18791912.Google Scholar
[10]Gans, N.Koole, G. & Mandelbaum, A. (2003) Telephone call centers: tutorial, review and research prospects. Manuf. Serv. Oper. Manag. 5, 79141.CrossRefGoogle Scholar
[11]Garnett, O.Mandelbaum, A. & Reiman, M.(2002) Designing a call center with impatient customers. Manuf. Serv. Oper. Manag. 4, 208227.Google Scholar
[12]Gradshteyn, I. S. & Ryzhik, I. M. (2007) Table of Integrals, Series and Products, 7th ed., Elsevier/Academic Press, Amsterdam.Google Scholar
[13]Halfin, S. & Whitt, W. (1981) Heavy-traffic limits for queues with many exponential servers. Oper. Res. 29, 567588.Google Scholar
[14]Janssen, A. J. E. M., van Leeuwaarden, J. S. H. & Zwart, B. (2011) Refining square-root safety staffing by expanding Erlang C. Oper. Res. 59, 15121522.Google Scholar
[15]Jelenković, P.Mandelbaum, A. & Momčilović, P. (2004) Heavy traffic limits for queues with many deterministic servers. Queueing Syst. 47, 5369.Google Scholar
[16]van Leewaarden, J. S. H. & Knessl, C. (2011) Transient behavior of the Halfin–Whitt diffusion. Stoch. Process. Appl. 121, 15241545.Google Scholar
[17]Maglaras, C. & Zeevi, A. (2004) Diffusion approximations for a multiclass Markovian service system with “guaranteed" and “best-effort" service levels. Math. Oper. Res. 29, 786813.Google Scholar
[18]Magnus, W.Oberhettinger, F. & Soni, R. P. (2008) Formulas and Theorems for the Special Functions of Mathematical Physics, Springer-Verlag, New York.Google Scholar
[19]Mandelbaum, A. & Momčilović, P. (2008) Queues with many servers: The virtual waiting-time process in the QED regime. Math. Oper. Res. 33, 561586.Google Scholar
[20]Olver, F. W. J. (1959) Uniform asymptotic expansions for Weber parabolic cylinder functions of large orders. J. Res. Nat. Bur. Standards Sect. 63B, 131169.CrossRefGoogle Scholar
[21]Pollaczek, F. (1931) Über zwei Formeln aus der Theorie des Wartens vor Schaltergruppen. Elektr. Nachr. 8, 256268.Google Scholar
[22]Reed, J. (2009) The G/GI/N queue in the Halfin–Whitt regime. Ann. Appl. Probab. 19, 22112269.Google Scholar
[23]Shwartz, A. & Weiss, A. (1995) Large Deviations of Performance Analysis, Chapman & Hall, London.Google Scholar
[24]Szpankowski, W. (2001) Average Case Analysis of Algorithms on Sequences, Wiley-Interscience, New York.Google Scholar
[25]Temme, N. M. (2010) Parabolic cylinder function. In: NIST Handbook of Mathematical Functions, U. S. Dept. Commerce, Washington, DC, pp. 303319.Google Scholar
[26]Varadhan, S. R. S. (1984) Large deviations and applications. In: CBMS-NSF Regional Conference Series in Applied Mathematics, Vol. 46, SIAM, Philadelphia.Google Scholar
[27]Wong, R. (2001) Asymptotic Approximation of Integrals, SIAM, Philadelphia, PA.Google Scholar