Efficient runtime quantitative verification using caching, lookahead, and nearly-optimal reconfiguration

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

Abstract

Self-adaptive systems used in safety-critical and businesscritical applications must continue to comply with strict non-functional requirements while evolving in order to adapt to changing workloads, environments, and goals. Runtime quantitative verification (RQV) has been proposed as an effective means of enhancing self-adaptive systems with this capability. However, RQV frequently fails to provide the fast response times and low computation overheads required by real-world self-adaptive systems. In this paper, we investigate how three techniques, namely caching, lookahead and nearly-optimal reconfiguration, and combinations thereof, can help address this limitation. Extensive experiments in a case study involving the RQV-driven self-adaptation of an unmanned underwater vehicle indicate that these techniques can lead to significant reductions in RQV response times and computation overheads.

Original languageEnglish
Title of host publication9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Proceedings
PublisherACM
Pages115-124
Number of pages10
ISBN (Print)9781450328647
DOIs
Publication statusPublished - 1 Jan 2014
Event9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014 - Hyderabad, United Kingdom
Duration: 2 Jun 20143 Jun 2014

Conference

Conference9th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2014
Country/TerritoryUnited Kingdom
CityHyderabad
Period2/06/143/06/14

Keywords

  • Continuous-time Markov chains
  • Probabilistic model checking
  • Quantitative verification
  • Self-adaptation

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