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@inproceedings{1506125, author = {Ivanov, Dmitry and Larsen, Kim G. and Schupp, Sibylle and Srba, Jiří}, address = {Netherlands}, booktitle = {Proceedings of the 15th International Conference on Quantitative Evaluation of SysTems (QEST'18)}, doi = {http://dx.doi.org/10.1007/978-3-319-99154-2_11}, keywords = {UPPAAL SMC; battery models; statistical model checking; wireless protocols}, howpublished = {tištěná verze "print"}, language = {eng}, location = {Netherlands}, isbn = {978-3-319-99153-5}, pages = {173-189}, publisher = {Springer}, title = {Analytical Solution for Long Battery Lifetime Prediction in Nonadaptive Systems}, url = {https://link.springer.com/chapter/10.1007%2F978-3-319-99154-2_11}, year = {2018} }
TY - JOUR ID - 1506125 AU - Ivanov, Dmitry - Larsen, Kim G. - Schupp, Sibylle - Srba, Jiří PY - 2018 TI - Analytical Solution for Long Battery Lifetime Prediction in Nonadaptive Systems PB - Springer CY - Netherlands SN - 9783319991535 KW - UPPAAL SMC KW - battery models KW - statistical model checking KW - wireless protocols UR - https://link.springer.com/chapter/10.1007%2F978-3-319-99154-2_11 L2 - https://link.springer.com/chapter/10.1007%2F978-3-319-99154-2_11 N2 - 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. ER -
IVANOV, Dmitry, Kim G. LARSEN, Sibylle SCHUPP a Jiří SRBA. Analytical Solution for Long Battery Lifetime Prediction in Nonadaptive Systems. In \textit{Proceedings of the 15th International Conference on Quantitative Evaluation of SysTems (QEST'18)}. Netherlands: Springer, 2018, s.~173-189. ISBN~978-3-319-99153-5. Dostupné z: https://dx.doi.org/10.1007/978-3-319-99154-2\_{}11.
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