RAPLET:揭开ROS应用程序发布/订阅延迟的神秘面纱

Keisuke Nishimura, T. Ishikawa, Hiroshi Sasaki, S. Kato
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引用次数: 4

摘要

基于有向无环图(DAG)任务模型的实时调度问题已经得到了广泛的研究。大多数研究的目的是开发有效的调度算法,以减少最后期限错过和/或提高给定任务系统的可调度性界限。为了在实际应用中保证DAG任务模型的实时性,必须系统地考虑DAG节点之间通信的延迟。本文旨在揭示机器人操作系统(ROS)作为一种实用的DAG任务模型的延迟,ROS利用发布/订阅机制在节点之间发送和接收数据。为此,我们提出了ROS感知发布/订阅延迟评估工具(RAPLET),该工具旨在测量和可视化ROS中发布/订阅延迟的细节。RAPLET由(i)在用户层插入函数钩子的LD PRELOAD方案和(ii)扩展的伯克利包过滤(eBPF)方案组成,该方案监视运行队列级别和内核层的网络状态。对ROS应用程序(包括真实世界的自动驾驶软件)的性能分析使用RAPLET进行,以证明可以根据系统问题(包括消息大小和网络带宽消耗)对强加于节点间通信的发布/订阅延迟进行解密和推理。
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RAPLET: Demystifying Publish/Subscribe Latency for ROS Applications
The problem of real-time scheduling based on the Directed Acyclic Graph (DAG) task model has been extensively studied in the literature. Most of the studies are aimed at the development of efficient scheduling algorithms to reduce deadline misses and/or improve schedulability bounds on the given task system. In order to guarantee real-time performance of the DAG task model in practice, the latency imposed on the communication between the DAG nodes must be systematically taken into account. This paper aims at demystifying the latency of the Robot Operating System (ROS) as a practical DAG task model, which leverages the publish/subscribe mechanism to send and receive data between the nodes. To this end we present the ROS-Aware Publish/Subscribe Latency Evaluation Tool (RAPLET) which is designed to measure and visualize the details of the publish/subscribe latency in ROS. RAPLET consists of (i) the LD PRELOAD scheme that inserts function hooks in user-land and (ii) the extended Berkeley Packet Filter (eBPF) scheme that monitors the run-queue level and the network states in kernel-land. The performance analysis on ROS applications, including a real-world autonomous driving software, is performed using RAPLET to demonstrate that the publish/subscribe latency imposed on inter-node communication can be demystified and reasoned with respect to system issues including the message size and network bandwidth consumption.
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来源期刊
CiteScore
1.70
自引率
14.30%
发文量
17
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