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Incremental Model Synchronization for Efficient Run-Time Monitoring

Authors: Thomas Vogel 0001; Stefan Neumann 0002; Stephan Hildebrandt; Holger Giese; Basil Becker;

Incremental Model Synchronization for Efficient Run-Time Monitoring

Abstract

The model-driven engineering community has developed expressive model transformation techniques based on meta models, which ease the specification of translations between different model types. Thus, it is attractive to also apply these techniques for autonomic and self- adaptive systems at run-time to enable a comprehensive monitoring of their architectures while reducing development efforts. This requires spe- cial solutions for model transformation techniques as they are applied at run-time instead of their traditional usage at development time. In this paper we present an approach to ease the development of architectural monitoring based on the incremental model synchronization with triple graph grammars. We show that the provided incremental synchronization between a running system and models for different self-management capabilities provides a significantly better compromise between performance and development costs than manually developed solutions.

In: International Workshop on Models@run.time. Vol. 509. CEUR Workshop Proceedings. CEUR-WS.org, 2009, pp. 1-10.

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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