Matrix-geometric solutions of M/G a unifying generalized state-space approach.

Matrix-geometric solutions of M/G a unifying generalized state-space approach.

We present an algorithmic approach to find the stationary probability distribution of M/G/1-type Markov chains which arise frequently in performance analysis of computer and communication networks. The approach unifies finite- and infinite-level Markov chains of this type through a generalized state...

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Publié dans:IEEE Journal on selected areas in communications 16, 5 (1998).
Auteur principal: Akar, N.
Format: Article
Langue:English
Sujets:
M/G/1-type Markov chains.
Backward subsystem.
Communication networks.
Computer networks.
Finite-level Markov chains.
Forward subsystem.
Generalized invariant subspaces.
Generalized state-space representation.
Infinite-level Markov chains.
Level distribution moments.
Linear algebra.
Matrix parameters.
Matrix-geometric solutions.
Matrix-sign function iterations.
Ordered generalized Schur decomposition.
Overflow probabilities.
Performance analysis.
Probability generating function.
Quadratic convergence rates.
Rational probability generating matrices.
Recursive methods.
Solution vector.
Stationary probability distribution.
Stationary solution.
Unifying generalized state-space approach.