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Model-driven runtime resource predictions for advanced mechatronic systems with dynamic data structures

  • The next generation of advanced mechatronic systems is expected to enhance their functionality and improve their performance by context-dependent behavior. Therefore, these systems require to represent information about their complex environment and changing sets of collaboration partners internally. This requirement is in contrast to the usually assumed static structures of embedded systems. In this paper, we present a model-driven approach which overcomes this situation by supporting dynamic data structures while still guaranteeing that valid worst-case execution times can be derived. It supports a flexible resource manager which avoids to operate with the prohibitive coarse worst-case boundaries but instead supports to run applications in different profiles which guarantee different resource requirements and put unused resources in a profile at other applications' disposal. By supporting the proper estimation of worst case execution time (WCET) and worst case number of iteration (WCNI) at runtime, we can further support to createThe next generation of advanced mechatronic systems is expected to enhance their functionality and improve their performance by context-dependent behavior. Therefore, these systems require to represent information about their complex environment and changing sets of collaboration partners internally. This requirement is in contrast to the usually assumed static structures of embedded systems. In this paper, we present a model-driven approach which overcomes this situation by supporting dynamic data structures while still guaranteeing that valid worst-case execution times can be derived. It supports a flexible resource manager which avoids to operate with the prohibitive coarse worst-case boundaries but instead supports to run applications in different profiles which guarantee different resource requirements and put unused resources in a profile at other applications' disposal. By supporting the proper estimation of worst case execution time (WCET) and worst case number of iteration (WCNI) at runtime, we can further support to create new profiles, add or remove them at runtime in order to minimize the over-approximation of the resource consumption resulting from the dynamic data structures required for the outlined class of advanced systems.show moreshow less

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Metadaten
Author details:Stefan Henkler, Simon Oberthuer, Holger GieseORCiDGND, Andreas Seibel
ISSN:0267-6192
Title of parent work (English):Computer systems science and engineering
Publisher:IOP Publ. Ltd.
Place of publishing:Leicester
Publication type:Article
Language:English
Year of first publication:2011
Publication year:2011
Release date:2017/03/26
Tag:Dynamic Data Structures; Flexible Resource Manager; Model-Driven Engineering; Runtime WCET Analysis; Safety Critical Systems
Volume:26
Issue:6
Number of pages:14
First page:505
Last Page:518
Organizational units:An-Institute / Hasso-Plattner-Institut für Digital Engineering gGmbH
Peer review:Referiert
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