Regenerative Simulation Methods for Local Area Computer Networks.

Abstract

Local area computer network simulations are inherently non-Markovian in that the underlying stochastic process cannot be modeled as a Markov chain with countable state space. We restrict attention to local network simulations with an underlying stochastic process that can be represented as a generalized semi-Markov process (GSMP). Using new better than used distributional assumptions and sample path properties of the GSMP, we provide a geometric trials criterion for recurrence in this setting. We also provide conditions which ensure that a GSMP is a regenerative process and that the expected time between regeneration points is finite. Steady-state estimation procedures for ring and bus network simulations follow from these results.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Jun 01, 1984
Accession Number
ADA146197

Entities

People

  • G. S. Shedler
  • P. J. Haas

Organizations

  • Stanford University

Tags

DTIC Thesaurus Topics

  • Bus Networks
  • Computer Networks
  • Computers
  • Distribution Functions
  • Equations
  • Local Area Networks
  • Markov Chains
  • Markov Processes
  • Network Simulation
  • Networks
  • Operations Research
  • Probability
  • Random Variables
  • Ring Networks
  • Simulations
  • Stochastic Processes
  • United States

Fields of Study

  • Computer science

Readers

  • Mathematical Modeling and Probability Theory.
  • Parallel and Distributed Computing.

Technology Areas

  • Space