ATER: Adaptive Task Execution Rate Regulation for Enhanced Real-Time Performance in ROS 2
Li, Ruoxiang Song, Ziwei Lv, Mingsong Wu, Jen-Ming Xue, Chun Jason Wang, Jianping Guan, Nan
Li, Ruoxiang
Song, Ziwei
Lv, Mingsong
Wu, Jen-Ming
Xue, Chun Jason
Wang, Jianping
Guan, Nan
Supervisor
Department
Computer Science
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Type
Conference proceeding
Date
2025
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Language
English
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Abstract
Autonomous systems, such as autonomous vehicles and robots, typically use middleware like Robot Operating System (ROS) to manage communication, execution, and functionality. These systems sample sensing data at fixed rates from various sources and propagate it among independently developed tasks using a publish-subscribe scheme. A common issue is the nature of dynamic fluctuations in task execution time for processing this data, exacerbated by resource contention, dynamic environments, and scheduling strategies. This dynamism, combined with the lack of runtime coordination of task execution at the operating system level, leads to misaligned task execution rates, which is undetected by both middleware and operating systems. As a result, this misalignment (i.e., uncoordinated task execution) causes message drops, resource wastage, and degraded realtime performance. To address these challenges, we propose an Adaptive Task Execution rate Regulation (ATER) framework specifically designed for ROS 2-based systems. ATER consists of two key components: a runtime observer and a task regulator. It seamlessly integrates with the ROS 2 system without affecting its execution or requiring any modifications to its source code. By adapting the sensor data sampling rates at runtime, our framework effectively enhances the real-time performance of ROS 2-based systems through reduced message drops, efficient utilization of computational resources, and improved end-to-end latency.
Citation
R. Li et al., "ATER: Adaptive Task Execution Rate Regulation for Enhanced Real-Time Performance in ROS 2," 2025 IEEE 31st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA), Singapore, Singapore, 2025, pp. 90-101, doi: 10.1109/RTCSA66114.2025.00019
Source
2025 IEEE 31st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)
Conference
31st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)
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Source
31st International Conference on Embedded and Real-Time Computing Systems and Applications (RTCSA)
Publisher
IEEE