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Large Deviations and Queueing Applications

  • Michel Mandjes
Conference paper
Part of the Operations Research Proceedings book series (ORP, volume 1993)

Abstract

The theory of Large Deviations (LD) is concerned with the probability that certain stochastic processes attain extreme values, i.e., values far away from their mean value. This theory is founded by Cramér, Chernoff, and Sanov in the 1940’s and 1950’s. In particular, they applied it to stochastic problems in statistics and physics. The publications of Donsker, Varadhan, and Ellis in the 1970’s and 1980’s can also be regarded as important contributions to the development of the theory.

Keywords

Service Time Optimum Trajectory Moment Generate Function Interarrival Time Distribute Service Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. [1]
    J.A. Bucklew [1990]. Large Deviation techniques in Decision, Simulation, and Estimation. Wiley, New York.Google Scholar
  2. [2]
    R.S. Ellis [1985]. Entropy, Large Deviations, and Statistical Mechanics. Springer Verlag, Berlin.CrossRefGoogle Scholar
  3. [3]
    H.C. Tijms [1986]. Stochastic Modelling and Analysis, a Computational Approach. Wiley, New York.Google Scholar
  4. [4]
    J. Walrand [1988]. An Introduction to Queueing Networks. Prentice-Hall, New Jersey.Google Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 1994

Authors and Affiliations

  • Michel Mandjes
    • 1
  1. 1.Department of EconometricsVrije Universiteit AmsterdamThe Netherlands

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