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DOI: 10.4230/LIPIcs.ECRTS.2024.8

Deadline Miss Early Detection Method for DAG Tasks Considering Variable Execution Time

Authors: Hayate Toba and Takuya Azumi

Published in: LIPIcs, Volume 298, 36th Euromicro Conference on Real-Time Systems (ECRTS 2024)

Abstract

Autonomous driving systems must guarantee safety, which requires strict real-time performance. A series of processes, from sensor data input to vehicle control command output, must be completed by the end-to-end deadline. If a deadline miss occurs, the system must quickly transition to a safe state. To improve safety, an early detection method for deadline misses was proposed. The proposed method represents the autonomous driving system as a directed acyclic graph (DAG) with a mixture of timer-driven and event-driven nodes. It assigns appropriate time constraints for each node based on the end-to-end deadline. However, the existing methods assume the worst-case execution time (WCET) for calculating the time constraints of each node and do not consider the execution time variation of nodes, making the detection of deadline misses pessimistic. This paper proposes a deadline miss early detection method to determine the possibility of deadline misses quantitatively at the beginning of each node execution in a DAG task. It calculates the time constraints of each node using probabilistic execution time, which treats execution time as a random variable. Experimental evaluation shows that the proposed method reduces pessimism, which is a problem of conventional methods using WCET, and then achieves more accurate early detection of deadline misses. The evaluation also indicates that the execution time of static analysis required for deadline miss early detection is within a practical level.

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Hayate Toba and Takuya Azumi. Deadline Miss Early Detection Method for DAG Tasks Considering Variable Execution Time. In 36th Euromicro Conference on Real-Time Systems (ECRTS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 298, pp. 8:1-8:21, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{toba_et_al:LIPIcs.ECRTS.2024.8,
  author =	{Toba, Hayate and Azumi, Takuya},
  title =	{{Deadline Miss Early Detection Method for DAG Tasks Considering Variable Execution Time}},
  booktitle =	{36th Euromicro Conference on Real-Time Systems (ECRTS 2024)},
  pages =	{8:1--8:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-324-9},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{298},
  editor =	{Pellizzoni, Rodolfo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ECRTS.2024.8},
  URN =		{urn:nbn:de:0030-drops-203116},
  doi =		{10.4230/LIPIcs.ECRTS.2024.8},
  annote =	{Keywords: Autonomous driving system, deadline miss early detection, DAG, event-driven task, timer-driven task, probabilistic execution time}
}

Document

DOI: 10.4230/OASIcs.ASD.2019.3

IDF-Autoware: Integrated Development Framework for ROS-Based Self-Driving Systems Using MATLAB/Simulink

Authors: Shota Tokunaga, Yuki Horita, Yasuhiro Oda, and Takuya Azumi

Published in: OASIcs, Volume 68, Workshop on Autonomous Systems Design (ASD 2019)

Abstract

This paper proposes an integrated development framework that enables co-simulation and operation of a Robot Operating System (ROS)-based self-driving system using MATLAB/Simulink (IDF-Autoware). The management of self-driving systems is becoming more complex as the development of self-driving technology progresses. One approach to the development of self-driving systems is the use of ROS; however, the system used in the automotive industry is typically designed using MATLAB/Simulink, which can simulate and evaluate the models used for self-driving. These models are incompatible with ROS-based systems. To allow the two to be used in tandem, it is necessary to rewrite the C++ code and incorporate them into the ROS-based system, which makes development inefficient. Therefore, the proposed framework allows models created using MATLAB/Simulink to be used in a ROS-based self-driving system, thereby improving development efficiency. Furthermore, our evaluations of the proposed framework demonstrated its practical potential.

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Shota Tokunaga, Yuki Horita, Yasuhiro Oda, and Takuya Azumi. IDF-Autoware: Integrated Development Framework for ROS-Based Self-Driving Systems Using MATLAB/Simulink. In Workshop on Autonomous Systems Design (ASD 2019). Open Access Series in Informatics (OASIcs), Volume 68, pp. 3:1-3:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{tokunaga_et_al:OASIcs.ASD.2019.3,
  author =	{Tokunaga, Shota and Horita, Yuki and Oda, Yasuhiro and Azumi, Takuya},
  title =	{{IDF-Autoware: Integrated Development Framework for ROS-Based Self-Driving Systems Using MATLAB/Simulink}},
  booktitle =	{Workshop on Autonomous Systems Design (ASD 2019)},
  pages =	{3:1--3:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-102-3},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{68},
  editor =	{Saidi, Selma and Ernst, Rolf and Ziegenbein, Dirk},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ASD.2019.3},
  URN =		{urn:nbn:de:0030-drops-103367},
  doi =		{10.4230/OASIcs.ASD.2019.3},
  annote =	{Keywords: self-driving systems, framework, robot operating system (ROS), MATLAB/Simulink}
}

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Documents authored by Azumi, Takuya

Deadline Miss Early Detection Method for DAG Tasks Considering Variable Execution Time

Abstract

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IDF-Autoware: Integrated Development Framework for ROS-Based Self-Driving Systems Using MATLAB/Simulink

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