Priority assignment for event-triggered systems using mathematical programming

M. Lukasiewycz, S. Steinhorst, S. Chakraborty
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引用次数: 10

Abstract

This paper presents a methodology based on mathematical programming for the priority assignment of processes and messages in event-triggered systems with tight end-to-end real-time deadlines. For this purpose, the problem is converted into a Quadratically Constrained Quadratic Program (QCQP) and addressed with a state-of-the-art solver. The formulation includes preemptive as well as non-preemptive schedulers and avoids cyclic dependencies that may lead to intractable real-time analysis problems. For problems with stringent real-time requirements, the proposed mathematical programming method is capable of finding a feasible solution efficiently where other approaches suffer from a poor scalability. In case there exists no feasible solution, an algorithm is presented that uses the proposed method to find a minimal reason for the infeasibility which may be used as a feedback to the designer. To give evidence of the scalability of the proposed method and in order to show the clear benefit over existing approaches, a set of synthetic test cases is evaluated. Finally, a large realistic case study is introduced and solved, showing the applicability of the proposed method in the automotive domain.
使用数学规划的事件触发系统的优先级分配
本文提出了一种基于数学规划的方法,用于在具有严格的端到端实时截止日期的事件触发系统中分配进程和消息的优先级。为此,将该问题转换为二次约束二次规划(QCQP),并使用最先进的求解器进行求解。该公式包括抢占式和非抢占式调度程序,并避免了可能导致难以处理的实时分析问题的循环依赖。对于实时性要求严格的问题,本文提出的数学规划方法能够有效地找到可行的解,而其他方法的可扩展性较差。在不存在可行解的情况下,提出了一种算法,利用所提出的方法找到不可行的最小原因,并将其作为对设计者的反馈。为了证明所提出的方法的可伸缩性,并为了显示相对于现有方法的明显优势,对一组综合测试用例进行了评估。最后,通过一个大型的实际案例分析,说明了该方法在汽车领域的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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