Outstanding Paper Award of IEEE Real-Time Systems Symposium (RTSS) 2024
![Outstanding Paper of RTSS 2024](/storages/daes-cs/_processed_/1/0/csm_RTSS2024-Outstanding_35061480ff.jpg)
This paper proposes analysis, which derives response-time distributions to infer upper bounds on deadline-failure probabilities, applies to a novel task model that incorporates information about both intra- and inter-task dependencies.
Together with MPI, the researchers of DAES received an Outstanding Paper Award of IEEE Real-Time System Symposium (RTSS), took place on December 10-13, 2024 / York, United Kingdom.
Authors: Filip Markovic, Georg von der Brüggen, Mario Günzel, Jian-Jia Chen and Björn Brandenburg
Title: A Distribution-Agnostic and Correlation-Aware Analysis of Periodic Tasks