On Recurrence and Transience in Heavy-Tailed Generalized Semi-Markov Processes

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  • Date/Time:
    • Thursday December 16, 2010
      10:00 am - 11:00 am
  • Location: ISyE Executive classroom
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Summary Sentence: On Recurrence and Transience in Heavy-Tailed Generalized Semi-Markov Processes

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TITLE:  On Recurrence and Transience in Heavy-Tailed Generalized Semi-Markov Processes

SPEAKER:  Peter J. Haas, IBM Research

ABSTRACT:

The generalized semi-Markov process (GSMP) is the usual model for the underlying stochastic process of a complex discrete-event system. It is important to understand fundamental behavioral properties of the GSMP model, such as the conditions under which the states of a GSMP are recurrent. For example, recurrence is necessary for the validity of steady-state simulation output analysis methods such as the regenerative method, spectral method, and the method of batch means. We review some sufficient conditions for recurrence in irreducible finite-state GSMPs. These conditions include requirements on the "clocks" that govern the occurrence times of state transitions. For example, each clock-setting distribution must have finite mean. We then show that, in contrast to ordinary semi-Markov processes, an
irreducible finite-state GSMP can have transient states in the presence of multiple clock-setting distributions with heavy tails. (Joint work with Peter Glynn.)


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H. Milton Stewart School of Industrial and Systems Engineering (ISYE)

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  • Created By: Anita Race
  • Workflow Status: Published
  • Created On: Dec 15, 2010 - 5:28am
  • Last Updated: Oct 7, 2016 - 9:53pm