基于模型检验和数据流分析的混合延迟最小化方法

G. Kuiper, P. Kurtin, M. Bekooij
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引用次数: 4

摘要

限制实时多处理器应用程序的延迟对于安全关键型系统至关重要。已有几种近似分析方法可以有效地分析时延。然而,这些方法会产生悲观的延迟结果,并且没有利用缓冲区大小,也没有利用额外的序列约束来减少延迟。使用时间自动机的模型检查可以获得更准确的延迟分析结果,但是,代价通常是运行时间过长。本文提出了一种基于时间自动机的循环任务图延迟分析方法,该方法减少了循环任务图的运行时间。该方法适用于使用固定优先级抢占(Fixed Priority preemptive, FPP)调度策略在共享处理器上执行任务的系统。运行时间的减少是通过使用近似数据流分析技术,对需要使用模型检查器分析的选项的搜索空间进行修剪来实现的。该方法利用缓冲区的尺寸来最小化干扰和延迟。此外,为了最小化任务图的延迟,引入并自动调整序列约束。案例研究中使用了WLAN 802.11p收发器应用程序,将这种混合分析方法与使用迭代缓冲区大小的基于最先进近似值的方法进行比较。使用我们的方法,分析的延迟从17 μs减少到15 μs,而运行时间为23分钟,而不是几分之一秒。
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Hybrid Latency Minimization Approach using Model Checking and Dataflow Analysis
Bounding the latency of real-time multiprocessor applications is crucial for safety-critical systems. Several approximative analysis approaches exist that can efficiently analyze the latency. However, these approaches produce pessimistic latency results and do not exploit buffer sizing nor exploit additional sequence constraints to reduce the latency. More accurate latency analysis results can be obtained using model checking of timed-automata, however, at the cost of a typically excessive run-time. This paper presents a latency analysis approach for cyclic task graphs using model checking of timed automata of which the run-time is reduced. The approach is applicable for systems in which tasks are executed on shared processors using a Fixed Priority Pre-emptive (FPP) scheduling policy. The reduction in run-time is achieved by pruning the search space of options that need to be analyzed using the model checker by making use of approximative dataflow analysis techniques. The approach exploits dimensioning of buffers to minimize interference and latency. Moreover, sequence constraints are introduced and automatically adapted in order to minimize the latency of the task graph. A WLAN 802.11p transceiver application is used in the case study to compare this hybrid analysis approach to a state-of-the-art approximation based approach that uses iterative buffer sizing. Using our approach, the analyzed latency decreased from 17 μs to 15 μs at the cost of a run-time of 23 minutes instead of a fraction of a second.
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