SIMPLE STOCHASTIC NETWORKS: SOME PROBLEMS AND PROCEDURES.

Abstract

The paper provides an analysis of 'stochastic networks,' that is networks whose underlying link times are expressed as random variables. Analytic and Monte Carlo methods for finding the distribution function (or parameters thereof) of the maximal time through such a network are discussed. The first section, which considers analytical procedures, emphasizes networks whose link times are given by probability functions from an exponential family. It is shown that the Markov property of the exponential distribution may be utilized to simplify analytic computations. In the second section Monte Carlo techniques are described which provide useful information on project completion time distributions. It is argued that these easily applied techniques are more economical (fewer computations are required) than naive simulation. Throughout the paper, we suggest a blending of the analytical and simulation procedures into an efficient overall method for studying stochastic networks. (Author)

Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1968
Accession Number
AD0676891

Entities

People

  • D. P. Gaver Jr.
  • John M. Burt Jr

Organizations

  • Carnegie Mellon University

Tags

DTIC Thesaurus Topics

  • Blending
  • Computations
  • Data Science
  • Distribution Functions
  • Information Science
  • Mathematical Analysis
  • Mathematics
  • Monte Carlo Method
  • Probability
  • Probability Distributions
  • Random Variables
  • Simulations
  • Stochastic Processes

Fields of Study

  • Mathematics

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Approximation Theory.
  • Systems Analysis and Design