Stochastic Models for Performance Analysis of Database Recovery Control

Paulo B. Goes, Ushio Sumita

Research output: Contribution to journalArticle

20 Scopus citations

Abstract

In this paper we develop three analytical models for a comprehensive analysis of database recovery. These models, based on semi-Markov stochastic analysis and queueing networks, not only capture the details of modern recovery mechanisms, but take the complex stochastic behavior of the system into account. Furthermore, we use multiple performance measures to analyze different recovery mechanisms, the impact of environment characteristics and the effect of tunable system parameters, thus offering database designers and administrators a better understanding of the recovery system to be designed or managed. A special case of database recovery that has been studied by previous researchers is analyzed in detail; numerical experiments offer evidence of the effectiveness of our approach. The models developed in this paper, however, are applicable to much more general systems and environments.

Original languageEnglish (US)
Pages (from-to)561-576
Number of pages16
JournalIEEE Transactions on Computers
Volume44
Issue number4
DOIs
StatePublished - Apr 1995
Externally publishedYes

Keywords

  • Database recovery
  • availability
  • checkpointing
  • database management
  • performance evaluation
  • queueing networks
  • semi-Markov models
  • stochastic analysis

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Hardware and Architecture
  • Computational Theory and Mathematics

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