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Modeling and Analysis of Inter-Process Communication Delay in ROS 2

  • Xiantong Luo
  • , Xu Jiang*
  • , Nan Guan
  • , Haochun Liang
  • , Songran Liu
  • , Wang Yi
  • *Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

Abstract

ROS 2, the second-generation ROS, is a popular development framework for real-time robotic software. To ensure the timing correctness of applications based on ROS 2, one must model the time delay incurred by two aspects: computation and communication. While significant work has been conducted on computing delay, formal modeling and analysis of communication delay in ROS 2 is still an open issue. In this paper, we first present a formal description on the timing behavior of inter-process communication in ROS 2 with two typical communication policies, namely the InterestTree policy and FIFO policy, and then develop analysis techniques to upper-bound the incurred delay. We conduct experiments to validate the correctness and evaluate the efficacy of our method with case studies on realistic platform. © 2023 IEEE.
Original languageEnglish
Title of host publicationProceedings - 44th IEEE Real-Time Systems Symposium
Subtitle of host publicationRTSS 2023
PublisherIEEE
Pages198-209
ISBN (Electronic)9798350328578
ISBN (Print)979-8-3503-2858-5
DOIs
Publication statusPublished - Dec 2023
Event44th IEEE Real-Time Systems Symposium (RTSS 2023) - Howard Plaza Hotel Taipei, Taipei, Taiwan, China
Duration: 5 Dec 20238 Dec 2023
https://2023.rtss.org/

Publication series

NameProceedings - Real-Time Systems Symposium
ISSN (Print)1052-8725
ISSN (Electronic)2576-3172

Conference

Conference44th IEEE Real-Time Systems Symposium (RTSS 2023)
Abbreviated titleRTSS ’23
PlaceTaiwan, China
CityTaipei
Period5/12/238/12/23
Internet address

Bibliographical note

Full text of this publication does not contain sufficient affiliation information. With consent from the author(s) concerned, the Research Unit(s) information for this record is based on the existing academic department affiliation of the author(s).

Funding

This work was supported in part by the National Natural Science Foundation of China (NSFC 62102072) and the Research Council of Hong Kong GRF under Grants 11208522 and 15206221.

RGC Funding Information

  • RGC-funded

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