Predicting Worst-Case Execution Time Trends in Long-Lived Real-Time Systems

Research output: Chapter in Book/Report/Conference proceedingConference contribution


In some long-lived real-time systems, it is not uncommon to see that the execution times of some tasks may exhibit trends. For hard and firm real-time systems, it is important to ensure these trends will not jeopardize the system. In this paper, we first introduce the notion of dynamic worst-case execution time (dWCET), which forms a new perspective that could help a system to predict potential timing failures and optimize resource allocations. We then have a comprehensive review of trend prediction methods. In the evaluation, we make a comparative study of dWCET trend prediction. Four prediction methods, combined with three data selection processes, are applied in an evaluation framework. The result shows the importance of applying data preprocessing and suggests that non-parametric estimators perform better than parametric methods.

Original languageEnglish
Title of host publicationReliable Software Technologies - Ada-Europe 2017 - 22nd Ada-Europe International Conference on Reliable Software Technologies, Proceedings
EditorsMarkus Bader, Johann Blieberger
Number of pages15
ISBN (Electronic)978-3-319-60588-3
Publication statusPublished - 30 May 2017

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10300 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Bibliographical note

© Springer International Publishing AG 2017. This is an author-produced version of the published paper. Uploaded in accordance with the publisher’s self-archiving policy. Further copying may not be permitted; contact the publisher for details


  • Extreme value theory
  • Linear regression
  • Support vector regression
  • Trend prediction
  • Worst-case execution time

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