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Analyzing End-to-End Delays in Automotive Systems at Various Levels of Timing Information
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1276-3609
Research and Technology Centre, Robert Bosch, India.
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0003-3242-6113
Mälardalen University, School of Innovation, Design and Engineering, Embedded Systems.ORCID iD: 0000-0002-1687-930X
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2016 (English)In: IEEE 4th International Workshop on Real-Time Computing and Distributed systems in Emerging Applications REACTION'16, Porto, Portugal, 2016Conference paper, Published paper (Refereed)
Abstract [en]

Software design for automotive systems is highly complex due to the presence of strict data age constraints for event chains in addition to task specific requirements. These age constraints define the maximum time for the propagation of data through an event chain consisting of independently triggered tasks. Tasks in event chains can have different periods, introducing over- and under-sampling effects, which additionally aggravates their timing analysis. Furthermore, different functionality in these systems, is developed by different suppliers before the final system integration on the ECU. The software itself is developed in a hardware agnostic manner and this uncertainty and limited information at the early design phases may not allow effective analysis of end-to-end delays during that phase. In this paper, we present a method to compute end-to-end delays given the information available in the design phases, thereby enabling timing analysis throughout the development process. The presented methods are evaluated with extensive experiments where the decreasing pessimism with increasing system information is shown.

Place, publisher, year, edition, pages
Porto, Portugal, 2016.
Keyword [en]
Multi-Rate Effect ChainsReal-TimeAutomotiveAnalysis
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:mdh:diva-34074OAI: oai:DiVA.org:mdh-34074DiVA: diva2:1056892
Conference
IEEE 4th International Workshop on Real-Time Computing and Distributed systems in Emerging Applications REACTION'16, 29 Nov 2016, Porto, Portugal
Projects
PREMISE - Predictable Multicore SystemsDPAC - Dependable Platforms for Autonomous systems and ControlPreView: Developing Predictable Vehicle Software on Multi-core
Available from: 2016-12-15 Created: 2016-12-13 Last updated: 2016-12-15Bibliographically approved

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CiteExportLink to record
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