Improving Stochastic Communication Network Performance: Reliability vs. Throughput

Abstract

This research investigated the measurement and improvement of two performance parameters, expected flow and reliability, for stochastic communication networks. There were three objectives of this research. The first was to measure the reliability of large stochastic networks. This was accomplished through an investigation into the current methodologies in the literature, with a subsequent selection and application of a factoring program developed by Page and Perry. The second objective was to develop a reliability improvement model given that a mathematical reliability expression did not exist. This was accomplished modeling a heuristic by Jain and Gopal, into a linear improvement model. Finally, the third objective was to examine the trade- off between maximizing expected flow and reliability. This was accomplished through generating bounds for the efficient frontier in a modified multicriteria optimization approach. Using the methodologies formulated in this research, the performance parameters of both expected flow and reliability can be measured and subsequent improvements made providing insight into the operational capabilities of stochastic communication networks.

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Document Details

Document Type
Technical Report
Publication Date
Dec 01, 1991
Accession Number
ADA243655

Entities

People

  • Leonard J. Jansen

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Space

DTIC Thesaurus Topics

  • Algorithms
  • Artificial Intelligence
  • Birds
  • Communication Networks
  • Computer Programming
  • Computer Programs
  • Computers
  • Heuristic Methods
  • Integer Programming
  • Mathematical Programming
  • Measurement
  • Multiobjective Optimization
  • Operations Research
  • Optimization
  • Personal Computers
  • Reliability
  • Throughput

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Mathematical Modeling and Probability Theory.
  • Software Engineering