Simulation-Based Timing Analysis of Complex Real-Time Systems

Bohlin, Markus; Lu, Yue; Kraft, Johan; Kreuger, Per; Nolte, Thomas

doi:10.1109/rtcsa.2009.41

Cited by 16 publications

(11 citation statements)

References 9 publications

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“…The following example illustrates why it can be difficult or infeasible to automatically derive timing properties for complex embedded systems (Bohlin et al, 2009). Imagine a system that has a task that processes messages that arrive in a queue:…”

Section: Complex Embedded Systemsmentioning

confidence: 99%

“…The genetic algorithm determines how the simulation parameters are changed for the next search iteration. HCRR (Bohlin et al, 2009), in contrast, uses a hill climbing algorithm. It is based on the idea of starting at a random point and then repeatedly taking small steps pointing "upwards", i.e., to nearby input combinations giving higher response times.…”

Section: Simulation-based Timing Analysismentioning

confidence: 99%

“…Random restarts are used to avoid getting stuck in local maxima. In a study that involved a subset of an industrial complex embedded system, HCRR performed substantially better than both Monte Carlo simulation and the MABERA (Bohlin et al, 2009). It is desirable to have a model that is substantially smaller than the real system.…”

Section: Simulation-based Timing Analysismentioning

confidence: 99%

See 2 more Smart Citations

Software Reverse Engineering in the Domain of Complex Embedded Systems

Kienle¹,

Kraft²,

Müller³

2012

Reverse Engineering - Recent Advances and Applications

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Section: Complex Embedded Systemsmentioning

confidence: 99%

Section: Simulation-based Timing Analysismentioning

confidence: 99%

Section: Simulation-based Timing Analysismentioning

confidence: 99%

See 1 more Smart Citation

Software Reverse Engineering in the Domain of Complex Embedded Systems

Kienle¹,

Kraft²,

Müller³

2012

Reverse Engineering - Recent Advances and Applications

Self Cite

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“…Simulation-based timing analysis methods have expanded both in terms of Response-Time Analysis (RTA) for more complex systems [13,5] and how the results are subsequently used, e.g., by analyzing the timing properties of the existing code and wrapping it into components, which facilitate migration towards a component-based real-time system. Simulation-based methods provide a powerful augmentation to RTA as they allow the user to analyze the impact of changes on a system's temporal behavior, before introducing changes to the system, which is referred to as timing impact analysis [2].…”

Section: Introductionmentioning

confidence: 99%

A statistical approach to simulation model validation in response-time analysis of complex real-time embedded systems

Kraft

Nolte

et al. 2011

Proceedings of the 2011 ACM Symposium on Applied Computing

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As simulation-based analysis methods make few restrictions on the system design and scale to very large and complex systems, they are widely used in, e.g., timing analysis of complex real-time embedded systems (CRTES) in industrial circles. However, before such methods are used, the analysis simulation models have to be validated in order to assess if they represent the actual system or not, which also matters to the confidence in the simulation results. This paper presents a statistical approach to validation of temporal simulation models extracted from CRTES, by introducing existing mature statistical hypothesis tests to the context. Moreover, our evaluation using simulation models depicting a fictive but representative industrial robotic control system indicates that the proposed method can successfully identify temporal differences between different simulation models, hence it has the potential to be considered as an effective simulation model validation technique.

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“…Simulationbased techniques have been introduced for the timing analysis of complex real-time systems [2], where the classic real-time models didn't apply successfully. In [3] the authors present a simulation methodology for the estimation of worst case response time in real-time distributed systems.…”

Section: Introductionmentioning

confidence: 99%

Simulation-based evaluation of real-time multiprocessor scheduling strategies

Hângan

Sebestyen

2010

Proceedings of the 2010 IEEE 6th International Conference on Intelligent Computer Communication and Processing

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Simulation can be an approximate performance evaluation method of real-time scheduling strategies. This method is useful when the analytical evaluation is too complex to be put in practice. In this paper we use simulation to evaluate the performance of Rate Monotonic and FIFO scheduling algorithms in different multiprocessor scheduling approaches. We present the design of our real-time scheduling simulation tool and the loose clustered scheduling approach as a result of our research.

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Simulation-Based Timing Analysis of Complex Real-Time Systems

Cited by 16 publications

References 9 publications

Software Reverse Engineering in the Domain of Complex Embedded Systems

Software Reverse Engineering in the Domain of Complex Embedded Systems

A statistical approach to simulation model validation in response-time analysis of complex real-time embedded systems

Simulation-based evaluation of real-time multiprocessor scheduling strategies

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