Mapping and Scheduling Automotive Applications on ADAS Platforms using Metaheuristics

Shane Daniel Geisler McLean, Silviu S. Craciunas, Emil Alexander Juul Hansen, Paul Pop

Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review

Abstract

Modern Advanced Driver-Assistance Systems (ADAS) merge critical and non-critical software functions with complex timing requirements and inter-dependencies onto the same integrated hardware platform. Real-time safety-critical automotive applications feature complex dependency chains between tasks (e.g., performing sensing, processing and actuation) which have to satisfy worst-case end-to-end latency constraints. The resulting scheduling problem requires both the assignment of tasks to the available cores of the platform and the computation static schedule tables for the real-time tasks, such that task deadlines, as well as end-to-end task chain constraints, are satisfied. We propose a heuristic approach based on Simulated Annealing (SA) which creates static schedule tables by simulating Earliest Deadline First (EDF) scheduling parameterized by task offsets and local deadlines decided by SA. We evaluate the proposed solution with real-world and synthetic test cases scaled to fit the future requirements of ADAS systems.
Original languageEnglish
Title of host publicationProceedings of 25th IEEE International Conference on Emerging Technologies and Factory Automation
Number of pages8
PublisherIEEE
Publication date2020
Article number9212029
ISBN (Print)9781728189567
DOIs
Publication statusPublished - 2020
Event25th IEEE International Conference on Emerging Technologies and Factory Automation - Virtual event, Vienna, Austria
Duration: 8 Sep 202011 Sep 2020
http://www.ieee-etfa.org/2020/

Conference

Conference25th IEEE International Conference on Emerging Technologies and Factory Automation
LocationVirtual event
CountryAustria
CityVienna
Period08/09/202011/09/2020
Internet address
SeriesIEEE International Conference on Emerging Technologies and Factory Automation, ETFA
ISSN1946-0759

Keywords

  • Automotive applications
  • Task scheduling
  • Task preemption
  • Simulation

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