Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

Timing constraints for runtime adaptation in real-time, networked embedded systems

: Zeller, Marc; Prehofer, Christian


Müller, H.A. ; Institute of Electrical and Electronics Engineers -IEEE-; Association for Computing Machinery -ACM-; Association for Computing Machinery -ACM-, Special Interest Group on Software Engineering -SIGSOFT-; IEEE Computer Society, Technical Council on Software Engineering:
7th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, SEAMS 2012. Proceedings : Zürich, Switzerland, June 4-5, 2012; Co-located with ICSE 2012, 34th International Conference on Software Engineering
Los Alamitos: IEEE Computer Society, 2012
ISBN: 978-1-4673-1788-7 (Print)
ISBN: 978-1-4673-2373-4
ISBN: 978-1-4673-1787-0
International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS) <7, 2012, Zürich>
International Conference on Software Engineering (ICSE) <34, 2012, Zurich>
Conference Paper
Fraunhofer ESK ()
networked embedded system; runtime adaptation; planning

In this work, we consider runtime adaption in networked embedded systems with tight real-time constraints. For such systems, we aim to adapt the placement of software components on networked hardware components at runtime withou5t violating real-time constraints. We develop constraints for such an adaptation process and show the applicability to networked embedded systems like automotive in-vehicle networks. Then, we analyze two approaches for finding solutions in the resulting search space for adaptations, one based on planning algorithms and the other based on constraint solving. While planning approaches start from the current configuration and aim to find a migration sequence and valid configuration, constraint solving approaches first find solutions and then check for a possible migration sequence. Based on simulations for the automotive domain, we show that approaches based on planning algorithms scale poorly, while constraint solving approaches can find solutions effectively.