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Using Reference Attribute Grammar-Controlled Rewriting for Energy Auto-Tuning

Bürger, Christoff LU ; Mey, Johannes; Schöne, René and Karol, Sven (2015) 10th International Workshop on Models@run.time In CEUR Workshop Proceedings (CEUR-WS.org) 1474. p.31-40
Abstract
Cyber-physical systems react on events reported by sensors and interact with objects of the real world according to their current state and their view of the world. This view is naturally represented by a model which is continuously analysed and updated at runtime. Model analyses should be ideally concise and efficient, requiring well-founded, comprehensible implementations with efficient reasoning mechanisms. In this paper, we apply reference attribute grammar controlled rewriting to concisely implement the runtime model of an auto-tuning case study for energy optimization. Attribute functions are used to interactively perform analyses. In case of an update, our system incrementally—and, thus, efficiently—recomputes depending analyses.... (More)
Cyber-physical systems react on events reported by sensors and interact with objects of the real world according to their current state and their view of the world. This view is naturally represented by a model which is continuously analysed and updated at runtime. Model analyses should be ideally concise and efficient, requiring well-founded, comprehensible implementations with efficient reasoning mechanisms. In this paper, we apply reference attribute grammar controlled rewriting to concisely implement the runtime model of an auto-tuning case study for energy optimization. Attribute functions are used to interactively perform analyses. In case of an update, our system incrementally—and, thus, efficiently—recomputes depending analyses. Since reference attribute grammar controlled rewriting builds the required dependency graphs automatically, incremental analysis comes for free. (Less)
Please use this url to cite or link to this publication:
author
organization
publishing date
type
Chapter in Book/Report/Conference proceeding
publication status
published
subject
keywords
attribute grammar, graph rewriting, incremental analyses, runtime model, cyber-physical system, energy auto-tuning
in
CEUR Workshop Proceedings (CEUR-WS.org)
editor
Götz, Sebastian; Bencomo, Nelly; Blair, Gordon; Song, Hui; ; ; and
volume
1474
pages
10 pages
publisher
CEUR
conference name
10th International Workshop on Models@run.time
external identifiers
  • scopus:84954465991
ISSN
1613-0073
language
English
LU publication?
yes
id
8f593af9-7e8b-4ec4-9a03-529b4b639013 (old id 7890470)
alternative location
http://ceur-ws.org/Vol-1474/
http://ceur-ws.org/Vol-1474/MRT15_paper_1.pdf
date added to LUP
2015-09-21 14:02:15
date last changed
2017-01-01 06:08:04
@inproceedings{8f593af9-7e8b-4ec4-9a03-529b4b639013,
  abstract     = {Cyber-physical systems react on events reported by sensors and interact with objects of the real world according to their current state and their view of the world. This view is naturally represented by a model which is continuously analysed and updated at runtime. Model analyses should be ideally concise and efficient, requiring well-founded, comprehensible implementations with efficient reasoning mechanisms. In this paper, we apply reference attribute grammar controlled rewriting to concisely implement the runtime model of an auto-tuning case study for energy optimization. Attribute functions are used to interactively perform analyses. In case of an update, our system incrementally—and, thus, efficiently—recomputes depending analyses. Since reference attribute grammar controlled rewriting builds the required dependency graphs automatically, incremental analysis comes for free.},
  author       = {Bürger, Christoff and Mey, Johannes and Schöne, René and Karol, Sven},
  booktitle    = {CEUR Workshop Proceedings (CEUR-WS.org)},
  editor       = {Götz, Sebastian and Bencomo, Nelly and Blair, Gordon and Song, Hui},
  issn         = {1613-0073},
  keyword      = {attribute grammar,graph rewriting,incremental analyses,runtime model,cyber-physical system,energy auto-tuning},
  language     = {eng},
  pages        = {31--40},
  publisher    = {CEUR},
  title        = {Using Reference Attribute Grammar-Controlled Rewriting for Energy Auto-Tuning},
  volume       = {1474},
  year         = {2015},
}