State-based Communication on Time-predictable Multicore Processors

Rasmus Bo Sørensen, Martin Schoeberl, Jens Sparsø

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

Abstract

Some real-time systems use a form of task-to-task communication called state-based or sample-based communication that does not impose any flow control among the communicating tasks. The concept is similar to a shared variable, where a reader may read the same value multiple times or may not read a given value at all. This paper explores time-predictable implementations of state-based communication in network-on-chip based multicore platforms through five algorithms. With the presented analysis of the implemented algorithms, the communicating tasks of one core can be scheduled independently of tasks on other cores. Assuming a specific time-predictable multicore processor, we evaluate how the read and write primitives of the five algorithms contribute to the worst-case execution time of the communicating tasks. Each of the five algorithms has specific capabilities that make them suitable for different scenarios.
Original languageEnglish
Title of host publicationProceedings of the 24th International Conference on Real-Time Networks and Systems (RTNS '16)
PublisherAssociation for Computing Machinery
Publication date2016
Pages225-234
ISBN (Print)978-1-4503-4787-7
DOIs
Publication statusPublished - 2016
Event24th International Conference on Real-Time Networks and Systems - Brest, France
Duration: 19 Oct 201621 Oct 2016
Conference number: 24
http://rtns16.univ-brest.fr/#page=home

Conference

Conference24th International Conference on Real-Time Networks and Systems
Number24
CountryFrance
CityBrest
Period19/10/201621/10/2016
Internet address

Keywords

  • Real-time systems
  • Network-on-chip
  • Multicore
  • Message-passing

Cite this

Sørensen, R. B., Schoeberl, M., & Sparsø, J. (2016). State-based Communication on Time-predictable Multicore Processors. In Proceedings of the 24th International Conference on Real-Time Networks and Systems (RTNS '16) (pp. 225-234). Association for Computing Machinery. https://doi.org/10.1145/2997465.2997480