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| Content Provider | ACM Digital Library |
|---|---|
| Author | Hartmann, Thomas Le Traon, Yves Barais, Olivier Fouquet, Francois Bourcier, Johann Mouline, Ludovic |
| Abstract | 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. |
| Starting Page | 1 |
| Ending Page | 6 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781450348362 |
| DOI | 10.1145/3079368.3079394 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2017-04-03 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Reactive systems Embedded systems Lazy loading Models@run.time Rule engines Smart systems |
| Content Type | Text |
| Resource Type | Article |
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