We present an approach for self-adaptation in automotive embedded systems using a hierarchical, multi-layered control approach.\r\nWe model automotive systems as a set of constraints and define a hierarchy of control loops based on different criteria. Adaptations\r\nare performed at first locally on a lower layer of the architecture. If this fails due to the restricted scope of the control cycle, the\r\nnext higher layer is in charge of finding a suitable adaptation.We compare different options regarding responsibility split in multilayered\r\ncontrol in a self-healing scenario with a setup adopted from automotive in-vehicle networks. We show that a multi-layer\r\ncontrol approach has clear performance benefits over a central control, even though all layers work on the same set of constraints.\r\nFurthermore, we show that a responsibility split with respect to network topology is preferable over a functional split.
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