Abstract
The availability of functionality is a crucial aspect of mission- and safety-critical systems. This is for instance demonstrated by the pursuit to automate road transportation. Here, the driver is not obligated to be part of the control loop, thereby requiring the underlying system to remain operational even after a critical component failure. Advances in the field of mixed-criticality research have allowed to address this topic of fail-operational system behaviour more efficiently. For instance, general purpose computing platforms may relinquish the need for dedicated backup units, as their purpose can be redefined at runtime. Based on this, a deterministic and resource-efficient reconfiguration mechanism is developed, in order to address safety concerns with respect to availability in a generic manner. To find a configuration for this mechanism that can ensure all availability-related safety properties, a design-time method to automatically generate schedules for different modes of operations from declaratively defined requirements is established. To cope with the inherent computational complexity, heuristics are developed to effectively narrow the problem space. Subsequently, this method’s applicability and scalability are respectively evaluated qualitatively within an automotive case study and quantitatively by means of a tool performance analysis.
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Acknowledgment
The research leading to these results has partially received funding from the European Commission within the Seventh Framework Programme as part of the SafeAdapt project (grant agreement 608945) and from the Bavarian Ministry of Economic Affairs and Media, Energy and Technology.
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Schleiss, P., Drabek, C., Weiss, G., Bauer, B. (2017). Generic Management of Availability in Fail-Operational Automotive Systems. In: Tonetta, S., Schoitsch, E., Bitsch, F. (eds) Computer Safety, Reliability, and Security. SAFECOMP 2017. Lecture Notes in Computer Science(), vol 10488. Springer, Cham. https://doi.org/10.1007/978-3-319-66266-4_12
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DOI: https://doi.org/10.1007/978-3-319-66266-4_12
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