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  4. Analytical solution for long battery lifetime prediction in nonadaptive systems
 
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Analytical solution for long battery lifetime prediction in nonadaptive systems

Publikationstyp
Conference Paper
Date Issued
2018
Sprache
English
Author(s)
Ivanov, Dmitry  
Larsen, Kim G.  
Schupp, Sibylle  
Srba, Jiří  
Institut
Softwaresysteme E-16  
TORE-URI
http://hdl.handle.net/11420/2739
First published in
Lecture notes in computer science  
Number in series
11024 LNCS
Start Page
173
End Page
189
Citation
International Conference on Quantitative Evaluation of Systems (QEST 2018)
Contribution to Conference
International Conference on Quantitative Evaluation of Systems, QEST 2018  
Publisher DOI
10.1007/978-3-319-99154-2_11
Scopus ID
2-s2.0-85053132275
Publisher
Springer
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.
DDC Class
004: Informatik
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