Abstract
We give stationary estimates for the derivative of the expectation of a nonsmooth function of bounded variationf of the workload in a G/G/1/∞ queue, with respect to a parameter influencing the distribution of the input process. For this, we use an idea of Konstantopoulos and Zazanis [1992] based on the Palm inversion formula, however avoiding a limiting argument by performing the level-crossing analysis thereof globally, via Fubini's theorem. This method of proof allows to treat the case where the workload distribution has a mass at discontinuities off and where the formula of Konstantopoulos and Zazanis [1992] has to be modified. The case where the parameter is the speed of service or/and the time scale factor of the input process is also treated using the same approach.
Similar content being viewed by others
References
Baccelli, F., and Brémaud, P., 1987.Palm Probabilities and Stationary Queues. Lecture Notes in Statistics, vol. 41, Springer-Verlag: New York.
Brémaud, P. 1992. Maximal coupling and rare perturbation analysis.Queueing Sys. Theory Appl., 11, pp. 307–333.
Brémaud, P. 1993. A Swiss Army formula of Palm calculus.J. Appl. Prob. 30, pp. 40–51.
Brémaud, P., and Lasgouttes, J.-M. 1992. Stationary IPA estimates for non-smooth functions of the GI/G/1/∞ workload. Rapport de Recherche 1677, INRIA, Domaine de Voluceau, Rocquencourt B.P. 105 78153 Le Chesnay Cedex, France.
Brémaud, P., and Vázquez-Abad, F.J. 1992. On the pathwise computation of derivatives with respect to the rate of a point process: the phantom RPA method.Queueing Syst. Theory Appl. 10, pp. 249–270.
Cao, X.-R. 1985. Convergence of parameter sensitivity estimates in a stochastic experiment.IEEE Trans. Automat. Control 30, pp. 834–843.
Fu, M.C., and Hu, J.-Q. 1992. Extensions and generalizations of smoothed perturbation analysis in a generalized semi-Markov process framework.IEEE Trans. Automat. Control 37, pp. 1483–1500.
Glasserman, P. 1991.Gradient Estimation via Perturbation Analysis. Kluwer: Boston.
Glasserman, P., and Gong, W.-B. 1991. Smoothed perturbation analysis for a class of discrete event systems.IEEE Trans. Automat. Control 35, pp. 1218–1230.
Glynn, P.W. 1990. Likelihood ratio gradient estimation for stochastic systems.Comm. ACM 33, pp. 76–84.
Glynn, P.W., and Whitt, W. 1989. Indirect estimation viaL=λW.Oper. Res. 37, pp. 82–103.
Gong, W.-B., and Ho, Y.-C. 1987. Smoothed (conditional) perturbation analysis of discrete event dynamic system.IEEE Trans. Automat. Control 32, pp. 858–866.
Ho, Y.-C., and Cao, X.-R. 1983. Optimization and perturbation analysis of queueing networks.J. Optim. Theory Appl. 40, pp. 559–582.
Ho, Y.-C. and Cao, X.-R. 1991.Perturbation Analysis of Discrete Event Dynamic Systems. Kluwer: Boston.
Konstantopoulos, P., and Zazanis, M. 1992. Sensitivity analysis for stationary and ergodic queues.Adv. Appl. Prob. 24, pp. 738–750.
Neveu, J. 1976. Sur les mesures de Palm de deux processus ponctuels stationnaires.Z. Wahrsch. verw. Geb. 34, pp. 199–203.
Reiman, M.I., and Weiss, A. 1989. Sensitivity analysis for simulations via likelihood ratios.Oper. Res. 37, pp. 830–844.
Suri, R. 1983. Implementation of sensitivity calculations on a Monte Carlo experiment.J. Optim. Theory Appl. 40, pp. 625–630.
Suri, R., and Zazanis, M. 1988. Perturbation analysis gives strongly consistent sensitivity estimates for the M/G/1 queue.Management Sci. 34, pp. 39–64.
Zazanis, M.A., and Suri, R. 1985. Estimating first and second derivatives of response time for G/G/1 queues from a single sample path. Technical report. Division of Applied Sciences, Harvard University, Cambridge, MA.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Brémaud, P., Lasgouttes, JM. Stationary IPA estimates for nonsmooth G/G/1/∞ functionals via palm inversion and level-crossing analysis. Discrete Event Dyn Syst 3, 347–374 (1993). https://doi.org/10.1007/BF01439159
Received:
Revised:
Issue Date:
DOI: https://doi.org/10.1007/BF01439159