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Abstract

During the past three decades, digital transmission networks have become ubiquitous and complex. Many analytical tools and software packages have been created to analyze and evaluate the behavior of these systems. However, these tools often use simplistic models of the system elements’ behavior such as exponential distribution of the intervals between failures, Poisson distribution of packets arriving at a node, and binomial distribution of errors in a block. These models are selected to simplify the analysis, but they often differ from the actual networks sufficiently to make the computed results of doubtful value.

Keywords

Markov Chain Model Probabilistic Automaton Batch Markov Arrival Process Message Arrival Multidimensional Distribution 
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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Copyright information

© Springer Science+Business Media New York 2004

Authors and Affiliations

  • William Turin
    • 1
  1. 1.AT&T Labs—ResearchFlorham ParkNew JerseyUSA

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