Analytical Solution for Long Battery Lifetime Prediction in Nonadaptive Systems

Dmitry Ivanov, Kim Guldstrand Larsen, Sibylle Schupp, Jiri Srba

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

2 Citations (Scopus)

Abstract

Uppaal SMC is a state-of-the-art tool for modelling and statistical analysis of hybrid systems, allowing the user to directly model the expected battery consumption in battery-operated devices. The tool employs a numerical approach for solving differential equations describing the continuous evolution of a hybrid system, however, the addition of a battery model significantly slows down the simulation and decreases the precision of the analysis. Moreover, Uppaal SMC is not optimized for obtaining simulations with durations of realistic battery lifetimes. We propose an analytical approach to address the performance and precision issues of battery modelling, and a trace extrapolation technique for extending the prediction horizon of Uppaal SMC. Our approach shows a performance gain of up to 80% on two industrial wireless sensor protocol models, while improving the precision with up to 55%. As a proof of concept, we develop a tool prototype where we apply our extrapolation technique for predicting battery lifetimes and show that the expected battery lifetime for several months of device operation can be computed within a reasonable computation time.
Original languageEnglish
Title of host publicationQuantitative Evaluation of Systems : 15th International Conference, QEST 2018, Beijing, China, September 4-7, 2018, Proceedings
EditorsAnnabelle McIver, Andreas Horvath
Number of pages17
PublisherSpringer
Publication date2018
Pages173-189
ISBN (Print)978-3-319-99153-5
ISBN (Electronic)978-3-319-99154-2
DOIs
Publication statusPublished - 2018
EventInternational Conference on Quantitative Evaluation of Systems - Beijing, China September 4-7, 2018, Beijing, China
Duration: 4 Sep 20187 Sep 2018
http://www.qest.org/qest2018/

Conference

ConferenceInternational Conference on Quantitative Evaluation of Systems
Location Beijing, China September 4-7, 2018
CountryChina
CityBeijing
Period04/09/201807/09/2018
Internet address
SeriesLecture Notes in Computer Science
Volume11024
ISSN0302-9743

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Keywords

  • Uppaal
  • Energy efficency
  • Battery behaviour
  • statistical model checking

Cite this

Ivanov, D., Larsen, K. G., Schupp, S., & Srba, J. (2018). Analytical Solution for Long Battery Lifetime Prediction in Nonadaptive Systems. In A. McIver, & A. Horvath (Eds.), Quantitative Evaluation of Systems: 15th International Conference, QEST 2018, Beijing, China, September 4-7, 2018, Proceedings (pp. 173-189). Springer. Lecture Notes in Computer Science, Vol.. 11024 https://doi.org/10.1007/978-3-319-99154-2_11