Two New Algorithms to Compute Steady-state Bounds for Markov Models with Slow Forward and Fast Backward Transitions

  • Authors:
  • Juan A. Carrasco;Angel Calderon;Javier Escriba

  • Affiliations:
  • -;-;-

  • Venue:
  • MASCOTS '96 Proceedings of the 4th International Workshop on Modeling, Analysis, and Simulation of Computer and Telecommunications Systems
  • Year:
  • 1996

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Abstract

Two new algorithms are proposed for the computation of bounds for the steady-state reward rate of irreducible finite Markov models with slow forward and fast backward transitions. The algorithms use detailed knowledge of the model in a subset of generated states G and partial information about the model in the non-generated portion U of the state space. U is assumed partitioned into subsets U_{k}, 1