Proceedings of the 29th ACM/IEEE International Conference on Automated Software Engineering 2014
DOI: 10.1145/2642937.2643015
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Assigning time budgets to component functions in the design of time-critical automotive systems

Abstract: The adoption of AUTOSAR and Model Driven Engineering (MDE) for the design of automotive software architectures allows an early analysis of system properties and the automatic synthesis of architecture and software implementation. To select and configure the architecture with respect to timing constraints, knowledge about the worst case execution times (WCET) of functions is required. An accurate evaluation of the WCET is only possible when reusing legacy functionality or very late in the development and procur… Show more

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Cited by 8 publications
(14 citation statements)
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“…Task period synthesis is presented in [22,23], task WCET synthesis in [24] and job-level dependencies synthesis in [20].…”
Section: Related Workmentioning
confidence: 99%
“…Task period synthesis is presented in [22,23], task WCET synthesis in [24] and job-level dependencies synthesis in [20].…”
Section: Related Workmentioning
confidence: 99%
“…System level decisions include function to ECU allocation (All the selected papers considered this. ), ECU to sub-network allocation [13], selection and addition of ECUs [17], [18], signal to message packing [11], [12], [26] and message scheduling [11], [12], [26]. ECU level decisions include function to task allocation [11], [12], task scheduling [8]- [12], [24]- [26] and task partitioning for the sake of reliability [8], [23] or energy saving [6], [7], [24].…”
Section: A Generic Contextmentioning
confidence: 99%
“…The rationale for this choice is that we do not want the algorithm (a local search) to end prematurely and we try to ease schedulability (and provide for maximum allocation freedom) as much as possible in the first step. Details of the algorithm can be found in (Wozniak, E. et al (2014)). …”
Section: Algorithm 1 Algorithm For the One-dimensional Binary Searchmentioning
confidence: 99%