Very Large Parallel Data Flow

Abstract

This report describes a three-phase effort to investigate the use of parallel processing in very large data/knowledge database management systems (D/ KBMS) as a means of attaining required performance levels. Phase one involved investigation of parallel processing techniques for inference processing, parallel processing techniques for very large database management and fault tolerant techniques for very large databases. During phase two, the results of ix investigation studies were combined to develop a methodology for specifying high performance, highly available D/KBMS computer architecture architectures for very large data/knowledge base (D/KB) environments. During phase three, a data/knowledge base management testbed was designed and implemented to serve both as a demonstration and performance measurement and evaluation platform. The testbed was used to perform several experiments designed to quantitatively measure D/KBMS performance and understand D/KBMS performance sensitivity and behavior with respect to various system paramounts. Several key results and conclusions have been identified from this work and directions for future work have been identified.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1988
Accession Number
ADA196205

Entities

People

  • Christine M. Baker
  • H. Lu
  • Jean L. Richardson
  • K. Mikkilineni
  • R. Ramnarayan

Organizations

  • Honeywell International, Inc.

Tags

Communities of Interest

  • C4I
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Application Software
  • Artificial Intelligence
  • Computer Program Documentation
  • Computer Programming
  • Computers
  • Database Management Systems
  • Databases
  • Expert Systems
  • Information Systems
  • Object Oriented Programming
  • Operating Systems
  • Parallel Computing
  • Parallel Processing
  • Programming Languages
  • Relational Database Management Systems
  • Relational Databases
  • Trees (Data Structures)

Fields of Study

  • Computer science

Readers

  • Database Systems and Applications
  • Software Engineering
  • Systems Analysis and Design

Technology Areas

  • AI & ML