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Analyzing End-to-End Delays in Automotive Systems at Various Levels of Timing Information

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Publication Type:

Journal article

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ACM SIGBED Review: Special Issue on 4th International Workshop on Real-time Computing and Distributed Systems in Emergent Applications


Abstract

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.

Bibtex

@article{Becker4531,
author = {Matthias Becker and Dakshina Dasari and Saad Mubeen and Moris Behnam and Thomas Nolte},
title = {Analyzing End-to-End Delays in Automotive Systems at Various Levels of Timing Information},
volume = {14},
number = {4},
pages = {1--6},
month = {November},
year = {2017},
journal = {ACM SIGBED Review: Special Issue on 4th International Workshop on Real-time Computing and Distributed Systems in Emergent Applications},
url = {http://www.es.mdu.se/publications/4531-}
}