Worst-Case Latency Analysis of Message Synchronization in ROS

Ruoxiang Li; Xu Jiang; Zheng Dong; Jen-Ming Wu; Chun Jason Xue; Nan Guan

doi:10.1109/RTSS59052.2023.00025

Worst-Case Latency Analysis of Message Synchronization in ROS

Ruoxiang Li
, Xu Jiang
, Zheng Dong
, Jen-Ming Wu
, Chun Jason Xue
, Nan Guan

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

13 Citations (Scopus)

Abstract

Multi-sensor data fusion is crucial for modern autonomous systems to accurately perceive their surrounding environments and make intelligent decisions. However, as different sensor sources may have significant time disparity, it is necessary to synchronize their data before sending them to the fusion algorithm, in order to control such differences and get meaningful fusion results. This paper discusses the message synchronization policy in ROS, a popular framework for robotic systems. The ROS message synchronization policy has proven to be highly effective in reducing the time disparity, but it introduces a certain level of latency. Therefore, to use it for real-time systems, it is essential to establish an upper bound for the worst-case latency that may occur. Specifically, we analyze two key latency metrics of the ROS message synchronization policy, the passing latency and reaction latency, which are needed to analyze the end-to-end delay
and reaction time on the system level. We conduct experiments under different settings to evaluate the precision of our proposed latency upper bounds against the maximum observed latency in real execution. © 2023 IEEE

Original language	English
Title of host publication	Proceedings - 44th IEEE Real-Time Systems Symposium
Subtitle of host publication	RTSS 2023
Publisher	IEEE
Pages	185-197
ISBN (Electronic)	979-8-3503-2857-8
ISBN (Print)	979-8-3503-2858-5
DOIs	https://doi.org/10.1109/RTSS59052.2023.00025
Publication status	Published - Dec 2023
Event	44th IEEE Real-Time Systems Symposium (RTSS 2023) - Howard Plaza Hotel Taipei, Taipei, Taiwan, China Duration: 5 Dec 2023 → 8 Dec 2023 https://2023.rtss.org/

Publication series

Name
ISSN (Print)	1052-8725
ISSN (Electronic)	2576-3172

Conference

Conference	44th IEEE Real-Time Systems Symposium (RTSS 2023)
Abbreviated title	RTSS ’23
Place	Taiwan, China
City	Taipei
Period	5/12/23 → 8/12/23
Internet address	https://2023.rtss.org/

Bibliographical note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Funding

This work was supported in part by the Research Council of Hong Kong GRF under Grants 11208522 and 15206221. This work was also partially supported by the National Natural Science Foundation of China (NSFC 62102072). The authors also thank the anonymous reviewers for their helpful comments.

RGC Funding Information

RGC-funded

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10.1109/RTSS59052.2023.00025

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1 Finished
1 Active

GRF: Managing Information Synchronicity in Real-Time Systems
GUAN, N. (Principal Investigator / Project Coordinator)
1/01/23 → …
Project: Research
GRF: Building a Theoretical Foundation for Real-time ROS
GUAN, N. (Principal Investigator / Project Coordinator)
1/01/22 → 18/11/25
Project: Research

Cite this

@inproceedings{e23d8f44404544e9ab45c0d78f9d32d6,

title = "Worst-Case Latency Analysis of Message Synchronization in ROS",

abstract = "Multi-sensor data fusion is crucial for modern autonomous systems to accurately perceive their surrounding environments and make intelligent decisions. However, as different sensor sources may have significant time disparity, it is necessary to synchronize their data before sending them to the fusion algorithm, in order to control such differences and get meaningful fusion results. This paper discusses the message synchronization policy in ROS, a popular framework for robotic systems. The ROS message synchronization policy has proven to be highly effective in reducing the time disparity, but it introduces a certain level of latency. Therefore, to use it for real-time systems, it is essential to establish an upper bound for the worst-case latency that may occur. Specifically, we analyze two key latency metrics of the ROS message synchronization policy, the passing latency and reaction latency, which are needed to analyze the end-to-end delay and reaction time on the system level. We conduct experiments under different settings to evaluate the precision of our proposed latency upper bounds against the maximum observed latency in real execution. {\textcopyright} 2023 IEEE",

author = "Ruoxiang Li and Xu Jiang and Zheng Dong and Jen-Ming Wu and Xue, \{Chun Jason\} and Nan Guan",

note = "Research Unit(s) information for this publication is provided by the author(s) concerned.; 44th IEEE Real-Time Systems Symposium (RTSS 2023), RTSS {\textquoteright}23 ; Conference date: 05-12-2023 Through 08-12-2023",

year = "2023",

month = dec,

doi = "10.1109/RTSS59052.2023.00025",

language = "English",

isbn = "979-8-3503-2858-5",

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TY - GEN

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AU - Li, Ruoxiang

AU - Jiang, Xu

AU - Dong, Zheng

AU - Wu, Jen-Ming

AU - Xue, Chun Jason

AU - Guan, Nan

N1 - Research Unit(s) information for this publication is provided by the author(s) concerned.

PY - 2023/12

Y1 - 2023/12

N2 - Multi-sensor data fusion is crucial for modern autonomous systems to accurately perceive their surrounding environments and make intelligent decisions. However, as different sensor sources may have significant time disparity, it is necessary to synchronize their data before sending them to the fusion algorithm, in order to control such differences and get meaningful fusion results. This paper discusses the message synchronization policy in ROS, a popular framework for robotic systems. The ROS message synchronization policy has proven to be highly effective in reducing the time disparity, but it introduces a certain level of latency. Therefore, to use it for real-time systems, it is essential to establish an upper bound for the worst-case latency that may occur. Specifically, we analyze two key latency metrics of the ROS message synchronization policy, the passing latency and reaction latency, which are needed to analyze the end-to-end delay and reaction time on the system level. We conduct experiments under different settings to evaluate the precision of our proposed latency upper bounds against the maximum observed latency in real execution. © 2023 IEEE

AB - Multi-sensor data fusion is crucial for modern autonomous systems to accurately perceive their surrounding environments and make intelligent decisions. However, as different sensor sources may have significant time disparity, it is necessary to synchronize their data before sending them to the fusion algorithm, in order to control such differences and get meaningful fusion results. This paper discusses the message synchronization policy in ROS, a popular framework for robotic systems. The ROS message synchronization policy has proven to be highly effective in reducing the time disparity, but it introduces a certain level of latency. Therefore, to use it for real-time systems, it is essential to establish an upper bound for the worst-case latency that may occur. Specifically, we analyze two key latency metrics of the ROS message synchronization policy, the passing latency and reaction latency, which are needed to analyze the end-to-end delay and reaction time on the system level. We conduct experiments under different settings to evaluate the precision of our proposed latency upper bounds against the maximum observed latency in real execution. © 2023 IEEE

U2 - 10.1109/RTSS59052.2023.00025

DO - 10.1109/RTSS59052.2023.00025

M3 - RGC 32 - Refereed conference paper (with host publication)

SN - 979-8-3503-2858-5

SP - 185

EP - 197

BT - Proceedings - 44th IEEE Real-Time Systems Symposium

PB - IEEE

T2 - 44th IEEE Real-Time Systems Symposium (RTSS 2023)

Y2 - 5 December 2023 through 8 December 2023

ER -

Worst-Case Latency Analysis of Message Synchronization in ROS

Abstract

Publication series

Conference

Bibliographical note

Funding

RGC Funding Information

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Projects

GRF: Managing Information Synchronicity in Real-Time Systems

GRF: Building a Theoretical Foundation for Real-time ROS

Cite this