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Self-adaptation in automotive embedded systems using a multi-layered control approach

: Zeller, Marc; Prehofer, Christian

Postprint urn:nbn:de:0011-n-1957837 (279 KByte PDF)
MD5 Fingerprint: b6b90508dc4abc005a03c1fa0f2a546b
Created on: 6.3.2012

Institute for Systems and Technologies of Information, Control and Communication -INSTICC-, Setubal:
PECCS 2012, 2nd International Conference on Pervasive Embedded Computing and Communication Systems. Proceedings : Rome, Italy, 24-26 February, 2012, held in conjunction with VISIGRAPP 2012 and SENSORNETS 2012
Setúbal: INSTICC, 2012
ISBN: 978-989-8565-00-6
International Conference on Pervasive Embedded Computing and Communication Systems (PECCS) <2, 2012, Rome>
International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Appications (VISIGRAPP) <7, 2012, Rome>
International Conference on Sensor Networks (SENSORNETS) <1, 2012, Rome>
Conference Paper, Electronic Publication
Fraunhofer ESK ()
self-adaptation; automotive; control architecture; networked embedded system

In this work, we present an approach for self-adaption in automotive embedded sytems using a hierachical, multilayered control approach.
We model automotive systems as a set of constraints and define a hierachy of control loops based on different criteria. Adaptations are performed at first locally on a lower layer of the architecture. If this fails due to the restrictes scope of the control cycle, the next higher layer is in charge of finding a suitable adaption.
We compare different options regarding responsibility split in multi-layered control and a version with centralized control option, in a self-healing scenario with a setup adopted from automotive in-vehicle networks. We show that a multi-layer control architecture has clear performance benefits over a central control, even though all layers work on the same set of constraints. Furthermore, we show that a responsibility split w.r.t. network topology is preferable over a functional split.