Mixed Harmonic Runnable Scheduling for Automotive Software on Multi-Core Processors

Lee, Kyung-Jung; Kim, Jae-Woo; Chang, Hyun‐Kyung; Ahn, Hyun-Sik

doi:10.1007/s12239-018-0031-2

Cited by 8 publications

(3 citation statements)

References 15 publications

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“…To our best knowledge, [12] is the unique research work addressed APS method for a multi-core architecture with a limitation (hypothesis) of only one task per core. The authors in [8] use least-loaded (LL) algorithm proposed by [12] to scheduling a mixed harmonic runnable set to one task per core.…”

Section: Related Workmentioning

confidence: 99%

Efficient mapping of runnables to tasks for embedded AUTOSAR applications

Khenfri

Chaaban

Chetto

2020

Journal of Systems Architecture

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Section: Related Workmentioning

confidence: 99%

Efficient mapping of runnables to tasks for embedded AUTOSAR applications

Khenfri

Chaaban

Chetto

2020

Journal of Systems Architecture

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“…Common optimization goals are stack memory usage [11,12] using genetic algorithms and scheduling algorithms, core load balancing [11], inter-communication overhead [13,14] using integer linear programming (ILP), data consistency using ILP and heuristic methods [15], and deadline violation [16,17] using genetic algorithms and the greedy heuristic approach for system resource clustering. Other work proposes regrouping runnables with arbitrary periods on the same task using a greedy heuristic approach combined with linear cost function and schedulability test [18,19]. This approach may lead to a minimum number of executors needed to schedule overloaded systems while minimizing the stack memory usage and context switch overhead.…”

Section: Introductionmentioning

confidence: 99%

“…The third algorithm used for comparison is the least loaded (LL) heuristic approach, used in [18]. The approach applies a deadline test schedulability similar to the one used in this paper along with a heuristic approach of least load to design the cost function, and defines the sequencing order of callbacks inside the executor with a complexity of O(n 2 ).…”

mentioning

confidence: 99%

A New Algorithm for Real-Time Scheduling and Resource Mapping for Robot Operating Systems (ROS)

Chaaban

2023

Applied Sciences

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A new version of a robot operating system (ROS-2) has been developed to address the real-time and fault constraints of distributed robotics applications. However, current implementations lack strong real-time scheduling and the optimization of response time for various tasks and applications. This may lead to inconsistent system behavior and may affect system performance. This article presents a new and efficient heuristic scheduling algorithm for the ROS-2 framework to improve resource mapping and system scheduling for robotics applications. The proposed scheduling design includes grouping callbacks into executors, assigning executor priority, and sequencing callbacks inside executors. The timing constraints and functional properties are expressed in the formal design model, and real-time scheduling is performed with respect to the timing constraints. The benefits of the proposed solution are demonstrated by a set of experimental results. Using this algorithm, it is shown that the number of executors needed to schedule a set of callbacks is minimized and the system schedulability is maximized for loaded and overloaded cases.

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