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A Real-time Scheduling Framework for Multi-threaded ROS 2 Applications
Seryun Kang, Jinseop Jeong, Kanghee Kim
http://doi.org/10.5626/JOK.2025.52.1.1
Real-time performance of robot applications operating in the physical world is crucial. In ROS (Robot Operating System) 2, robot applications consist of dozens or even hundreds of tasks. If the end-to-end delay from sensing to control increases, the resulting motion may be delayed, potentially leading to physical accidents. Consequently, many studies have been conducted to analyze and reduce delays in robot applications. This paper proposes a real-time scheduling framework that allows the application of the probabilistic latency analysis method, originally designed for process graphs, to thread graphs. The proposed framework groups callback functions with the same period into a single group based on a global schedule table and creates a thread graph by assigning a dedicated thread to each group. Each thread is then fixed to a CPU core as determined by the table and is scheduled using FIFO. This paper applies the proposed framework to the localization pipeline of Autoware and confirms that probabilistic latency analysis is feasible within this framework.
Stochastic Response Time Analysis for Autonomous Vehicle Computing Systems
Hyoeun Lee, Kanghee Kim, Kilho Lee
http://doi.org/10.5626/JOK.2021.48.5.486
This paper presents a method of probabilistically analyzing the end-to-end response time from sensing to actuation in autonomous vehicle computing systems. The end-to-end response time is used to evaluate vehicle responsiveness and to derive various indicators of vehicle safety. For example, given the end-to-end response time from sensing an obstacle to stopping the vehicle, an upper limit of the vehicle’s speed may be defined. In addition, the proposed analysis may be used to determine how many computing resources should be invested in improving vehicle responsiveness. This paper proposes a safe analytical method under the assumption that ERF (Earliest Release First) scheduling is used and that each task is pinned to a certain CPU, and presents the results of the responsiveness of an open source autonomous driving stack called Autoware.
Multi-core Scalable Real-time Flash Storage Simulation
Hyeon-gyu Lee, Sang Lyul Min, Kanghee Kim
http://doi.org/10.5626/JOK.2017.44.6.566
As NAND flash storage is being widely used, its simulation methodologies have been studied in various aspects such as performance, reliability, and endurance. As a result, there have been advances in NAND flash storage simulation for both functional modeling and timing modeling. However, in addition to these advances, there is a need to drastically reduce the long simulation time that is required to evaluate the aging effect on flash storage. This paper proposes a so-called multi-core scalable real-time flash storage simulation method, which can control the simulation speed according to the user’s preference. According to this method, it is possible to speed up the simulation in proportion to the number of CPU cores arbitrarily given while guaranteeing the correctness of the simulation result. Using our simulator implemented in the form of the Linux kernel module, we demonstrate the multi-core scalability and correctness of the proposed method.
Multi-core Scalable Fair I/O Scheduling for Multi-queue SSDs
Minjung Cho, Hyeongseok Kang, Kanghee Kim
The emerging NVMe-based multi-queue SSDs provides a high bandwidth by parallel I/O, i.e., each core performs I/O through its dedicated queue in parallel with other cores. To provide a bandwidth share for each application with I/O, a fair-share scheduler that provides a bandwidth share to each core is required. In this study, we proposed a multi-core scalable fair-queuing algorithm for multi-queue SSDs. The algorithm adopts randomization to minimize the inter-core synchronization overheads and provides a weight-proportional bandwidth share to each core. The results of our experiments indicated that the proposed algorithm gives accurate bandwidth partitioning and outperforms the existing FlashFQ scheduler, regardless of the number of cores for a Linux kernel with block-mq.
Flash Operation Group Scheduling for Supporting QoS of SSD I/O Request Streams
Eungyu Lee, Sun Won, Joonwoo Lee, Kanghee Kim, Eyeehyun Nam
As SSDs are increasingly being used as high-performance storage or caches, attention is increasingly paid to the provision of SSDs with Quality-of-Service for I/O request streams of various applications in server systems. Since most SSDs are using the AHCI controller interface on a SATA bus, it is not possible to provide a differentiated service by distinguishing each I/O stream from others within the SSD. However, since a new SSD interface, the NVME controller interface on a PCI Express bus, has been proposed, it is now possible to recognize each I/O stream and schedule I/O requests within the SSD for differentiated services. This paper proposes Flash Operation Group Scheduling within NVME-based flash storage devices, and demonstrates through QEMU-based simulation that we can achieve a proportional bandwidth share for each I/O stream.
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