Reference : Weaving Rules into Models@run.time for Embedded Smart Systems
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
http://hdl.handle.net/10993/31647
Weaving Rules into Models@run.time for Embedded Smart Systems
English
Mouline, Ludovic mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Hartmann, Thomas mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Fouquet, François mailto [University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > >]
Le Traon, Yves mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Bourcier, Johann mailto [University of Rennes 1 > Irisa > DiverSE > Associate Professor]
Barais, Olivier mailto [University of Rennes 1 > Irisa > DiverSE > Professor]
Apr-2017
Weaving Rules into Models@run.time for Embedded Smart Systems
Mouline, Ludovic mailto
Hartmann, Thomas mailto
Fouquet, François mailto
Le Traon, Yves mailto
Bourcier, Johann mailto
Barais, Olivier mailto
ACM
Yes
International
978-1-4503-4836-2
Brussels
Belgium
Second International Modularity in Modelling Workshop
from 03-04-2017 to 04-04-2017
Brussels
Belgium
[en] Models@run.time ; Reactive systems ; Rule engines ; Lazy loading ; Smart systems ; Embedded Systems
[en] Smart systems are characterised by their ability to analyse measured data in live and to react to changes according to expert rules. Therefore, such systems exploit appropriate data models together with actions, triggered by domain-related conditions. The challenge at hand is that smart systems usually need to process thousands of updates to detect which rules need to be triggered, often even on restricted hardware like a Raspberry Pi. Despite various approaches have been investigated to efficiently check conditions on data models, they either assume to fit into main memory or rely on high latency persistence storage systems that severely damage the reactivity of smart systems. To tackle this challenge, we propose a novel composition process, which weaves executable rules into a data model with lazy loading abilities. We quantitatively show, on a smart building case study, that our approach can handle, at low latency, big sets of rules on top of large-scale data models on restricted hardware.
SnT
POST Telecom
Researchers
http://hdl.handle.net/10993/31647
10.1145/3079368.3079394

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