Analytical Solution for Long Battery Lifetime Prediction in Nonadaptive Systems

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00106626" target="_blank" >RIV/00216224:14330/18:00106626 - isvavai.cz</a>

Výsledek na webu

<a href="https://link.springer.com/chapter/10.1007%2F978-3-319-99154-2_11" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-319-99154-2_11</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-319-99154-2_11" target="_blank" >10.1007/978-3-319-99154-2_11</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Analytical Solution for Long Battery Lifetime Prediction in Nonadaptive Systems

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

Analytical Solution for Long Battery Lifetime Prediction in Nonadaptive Systems

Popis výsledku anglicky

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.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Proceedings of the 15th International Conference on Quantitative Evaluation of SysTems (QEST'18)

ISBN

9783319991535

ISSN

0302-9743

e-ISSN

—

Počet stran výsledku

17

Strana od-do

173-189

Název nakladatele

Springer

Místo vydání

Netherlands

Místo konání akce

Bejing, China

Datum konání akce

1. 1. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000548912200011