Statistical Analysis of Non-Stationary Series of Events in a Data Base System

Abstract

Central problems in the performance evaluation of computer systems are the description of the behavior of the system and characterization of the workload. One approach the these problems comprises the interactive combination of data-analytic procedures with probability modelling. This paper describes methods, both old and new, for the statistical analysis of non-stationary univariate stochastic point processes and sequences of positive random variables. Such processes are frequently encountered in computer systems. As an illustration of the methodology an analysis is given of the stochastic point process of transactions initiated in a running data base system. On the basis of the statistical analysis, a non-homogeneous Poisson process model for the transaction initiation process is postulated for periods oh high system activity and found to be an adequate chracterization of the data. For periods of lower system activity, the transaction initiation process has a complex structure, with more clustering evident. Overall models of this type have application to the validation of proposed data base (sub) system models.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1976
Accession Number
ADA033708

Entities

People

  • Gerald S. Shedler
  • Peter A. W. Lewis

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Application Software
  • Computers
  • Data Analysis
  • Data Mining
  • Data Science
  • Databases
  • Information Processing
  • Information Science
  • Knowledge Management
  • Military Research
  • New York
  • Operating Systems
  • Probability
  • Random Variables
  • Statistical Analysis
  • Statistics
  • Theorems

Fields of Study

  • Engineering

Readers

  • Database Systems and Applications
  • Statistical inference.
  • Systems Analysis and Design