A GENERAL MODEL FOR SIMULATING INFORMATION STORAGE AND RETRIEVAL SYSTEMS

Abstract

This report presents the results of a research effort to explore the use of computer simulation as a quantitative tool for planning, analyzing and evaluating Information Retrieval systems. A general time-flow model has been developed that enables a systems engineer to simulate the interactions among personnel, equipment and data at each step in an information processing effort. The input parameters for the simulation reflect the configuration of the system, the processing load of the system, the work schedule of the system, the work schedule of the personnel, equipment availability, the likelihood and effect of errors in processing and the location and availability of the system user. Simulation output provides a study of system response time (both delay time and processing time), equipment and personnel work and idle time and the location and size of data queues. Included within this report is a discussion of the simulation rationale, the modeling methodology employed and the input and output data of the computer simulation programs. Additionally, one example of a system simulation is presented as an illustration of the capability of this kind of tool in systems analysis.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 1966
Accession Number
AD0636435

Entities

People

  • Charles R. Blunt
  • Peter T. Luckie
  • Robert T. Duquet

Organizations

  • HRB Systems

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Human Systems
  • Space

DTIC Thesaurus Topics

  • Abstracts
  • Central Processing Units
  • Computer Programming
  • Computer Programs
  • Computer Simulations
  • Computers
  • Data Processing
  • Engineering
  • Engineers
  • Information Processing
  • Information Retrieval
  • Information Systems
  • Materials
  • Plastic Explosives
  • Simulators
  • Systems Engineering
  • Time Intervals

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Computer Science.
  • Life Cycle Cost Analysis

Technology Areas

  • AI & ML
  • AI & ML - Bayesian Inference