Optimal Checkpointing of Real-Time Tasks

Kang G. Shin, Tein Hsiang Lin, Yann Hang Lee

Research output: Contribution to journalArticlepeer-review

74 Scopus citations


Analytical models for the design and evaluation of checkpointing of Real-Time tasks are developed. First, the execution of a Real-Time task is modeled under a common assumption of perfect coverage of online detection mechanisms (which is termed a basic model). Then, the model is generalized (to an extended model) to include more realistic cases, i.e., imperfect coverages of online detection mechanisms and acceptance tests. Finally, we determine an optimal placement of checkpoints to minimize the mean task execution time while the probability of an unreliable result (or lack of confidence) is kept below a specified level. In the basic model, it is shown that equidistant intercheckpoint intervals are optimal, whereas this is not necessarily true in the extended model. An algorithm for calculating the optimal number of checkpoints and intercheckpoint intervals is presented with some numerical examples for the extended model.

Original languageEnglish (US)
Pages (from-to)1328-1341
Number of pages14
JournalIEEE Transactions on Computers
Issue number11
StatePublished - Nov 1987
Externally publishedYes


  • Checkpointing
  • failure coverages
  • mean task execution time
  • on-line detection mechanisms and acceptance tests
  • optimal placement of checkpoints
  • probability of an unreliable result
  • rollback and restart failure recovery

ASJC Scopus subject areas

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


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