A Metaheuristic Approach for Best Effort Timing Analysis Targeting Complex Legacy Real-Time Systems

J. Kraft, Yue Lu, C. Norström, A. Wall
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Abstract

Many companies developing real-time systems today have today no means for response time analysis, as their systems violate the assumptions of traditional analytical methods for response-time analysis and are too complex for exhaustive analysis using model checking. This paper presents a novel approach for best effort response time analysis targeting such systems, where probabilistic simulation is guided by a search algorithm of metaheuristic type, similar to genetic algorithms. The best effort approach means that the result is not guaranteed to be the worst-case response time, but also that the method scales to large industrial systems. The proposed method should be regarded as a form of testing, focusing on timing properties. An evaluation is presented which indicates that the proposed approach is significantly more efficient than traditional probabilistic simulation in finding extreme task response times. The paper also presents a method for finding good parameters for the search algorithm, in order to improve its efficiency.
针对复杂遗留实时系统的最佳努力时间分析的元启发式方法
许多开发实时系统的公司目前没有办法进行响应时间分析,因为他们的系统违反了传统的响应时间分析方法的假设,而且对于使用模型检查进行详尽的分析来说太复杂了。本文提出了一种针对此类系统的最佳努力响应时间分析的新方法,其中概率模拟由类似于遗传算法的元启发式搜索算法指导。最佳努力方法意味着不能保证结果是最坏情况下的响应时间,但该方法也适用于大型工业系统。所提出的方法应被视为一种测试形式,重点关注时序特性。结果表明,该方法在寻找极端任务响应时间方面明显优于传统的概率模拟方法。为了提高搜索算法的效率,本文还提出了一种为搜索算法寻找合适参数的方法。
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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