Freshness and Reactivity Analysis in Globally Asynchronous Locally Time-Triggered Systems

Boniol, Frédéric; Lauer, Michaël; Pagetti, Claire

doi:10.1007/978-3-642-38088-4_7

Cited by 5 publications

(2 citation statements)

References 15 publications

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“…using backtracking. Another approach to estimating end-to-end latencies is based on mixed integer linear programming (MILP) and was presented in [22], [23]. There, the system's behavior and the timing properties of functional chains are modeled in terms of linear constraints.…”

Section: Related Workmentioning

confidence: 99%

Estimating Latencies of Task Sequences in Multi-Core Automotive ECUs

Friese

Ehlers

Nowotka

2018

2018 IEEE 13th International Symposium on Industrial Embedded Systems (SIES)

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The computation of a cyber-physical system's reaction to a stimulus typically involves the execution of several tasks. The delay between stimulus and reaction thus depends on the interaction of these tasks and is subject to timing constraints. Such constraints exist for a number of reasons and range from possible impacts on customer experiences to safety requirements. We present a technique to determine end-to-end latencies of such task sequences. The technique is demonstrated on the example of electronic control units (ECUs) in automotive embedded realtime systems. Our approach is able to deal with multi-core architectures and supports four different activation patterns, including interrupts. It is the first formal analysis approach making use of load assumptions in order to exclude infeasible data propagation paths without the knowledge of worst-case execution times or worst-case response times. We employ a constraint programming solver to compute bounds on end-toend latencies.

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Section: Related Workmentioning

confidence: 99%

Estimating Latencies of Task Sequences in Multi-Core Automotive ECUs

Friese

Ehlers

Nowotka

2018

2018 IEEE 13th International Symposium on Industrial Embedded Systems (SIES)

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“…Another holistic approach to estimating end-to-end latencies is based on mixed integer linear programming (MILP) and was presented in [25,83]. However, the scheduling mechanism considered differs from static priority preemptive scheduling as it assigns different, fixed time intervals for each task instance within one hyper period of the processing resource.…”

Section: Related Workmentioning

confidence: 99%

Modeling and Analysis of Automotive Cyber-physical Systems

Friese¹

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Based on advances in scheduling analysis in the 1970s, a whole area of research has evolved: formal end-to-end latency analysis in real-time systems. Although multiple approaches from the scientific community have successfully been applied in industrial practice, a gap is emerging between the means provided by formally backed approaches and the need of the automotive industry where cyber-physical systems have taken over from classic embedded systems. They are accompanied by a shift to heterogeneous platforms build upon multicore architectures. Scien- tific techniques are often still based on too simple system models and estimations on important end-to-end latencies have only been tightened recently. To this end, we present an expressive system model and formally describe the problem of end-to-end latency analysis in modern automotive cyber-physical systems. Based on this we examine approaches to formally estimate tight end-to-end latencies in Chapter 4 and Chapter 5. The de- veloped approaches include a wide range of relevant systems. We show that our approach for the estimation of latencies of task chains dominates existing approaches in terms of tightness of the results. In the last chapter we make a brief digression to measurement analysis since measuring and simulation is an important part of verification in current industrial practice.

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