Real-time scheduling interfaces and contracts for the design of distributed embedded systems

Stierand, Ingo; Reinkemeier, Philipp; Gezgin, Tayfun; Bhaduri, Purandar

doi:10.1109/sies.2013.6601485

Cited by 12 publications

(10 citation statements)

References 25 publications

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“…Real-time scheduling has also been combined with timed automata in [2,7] and with process algebra in [26,31]. In addition, a number of automata-and actor-oriented scheduling interfaces have also been developed [6,10,41,20]. However, the above approaches are not only expensive in terms of analysis complexity but also assume a very simple model of resources -for instance, the processor is assumed to have unit speed and be fully available.…”

Section: The Gap Between Real-time Scheduling Theory and High-level Fmentioning

confidence: 99%

“…Timing constraints of a component can then be guaranteed by ensuring that the platform satisfies the component's interface. Several interface models and interface computation techniques have been developed (see e.g., [39,9,16,27,34,38,21,14,42,30,6,10,41,20]), which enable efficient integration and isolation of independently-developed cyber-physical components. However, these existing theories face several important limitations: they ignore the platform overhead and the correlation between scheduling * This research was supported in part by the ARO grant W911NF-11-1-0403, ONR grant N00014-13-1-0802, and NSF grants CNS-1117185, ECCS-1135630 and CNS-1329984.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Proceedings of the 4th Analytic Virtual Integration of Cyber-Physical Systems Workshop December 3 Vancouver Canada

Broman¹,

Karsai²

2013

Linköping Electronic Conference Proceedings

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Section: The Gap Between Real-time Scheduling Theory and High-level Fmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Proceedings of the 4th Analytic Virtual Integration of Cyber-Physical Systems Workshop December 3 Vancouver Canada

Broman¹,

Karsai²

2013

Linköping Electronic Conference Proceedings

View full text Add to dashboard Cite

“…Existing work on the implementability of timed automata incorporates the platform information by explicitly modeling the execution platform (Abdellatif et al 2010;Altisen and Tripakis 2005;Triki et al 2013) or by modifying the semantics to reflect the implementation platform semantics (e.g., Krčál et al (2004); Krčál and Pelánek (2005); Wulf et al (2004)). Real-time scheduling has also been combined with timed automata in Abdeddaïm et al (2006), and a number of automata-and actororiented scheduling interfaces have also been developed (Alur and Weiss 2008;Geilen et al 2011;Stierand et al 2013). However, these existing techniques consider rather restrictive platform semantics, such as assuming only a small subset of possible implementations (Altisen and Tripakis 2005) or ignoring various sources of timing delays (Abdellatif et al 2010;Triki et al 2013;Wulf et al 2004).…”

Section: Introductionmentioning

confidence: 99%

Determining Timing Parameters for the Code Generation from Platform-Independent Timed Models

Kim¹,

Sokolsky

et al. 2019

ACM Trans. Cyber-Phys. Syst.

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Safety-critical embedded systems often need to meet dependability requirements such as strict input/output timing constraints. To meet the timing requirements, the code generation (e.g., C code) from timed models needs to determine the timing parameters that indicate when the code has to perform I/O with its platform. We propose a novel framework to determine such timing parameters from platform-independent timed models. Our framework involves two transformations. The first transformation systematically extends the platformindependent model by explicitly modeling input/output processing (e.g., sampling or interrupt-based) and the code invocation (e.g., periodic or aperiodic) mechanisms. Then, we verify if the resulting platform-specific model meets the timing requirements. In the case that the resulting model does not satisfy the timing requirements, we apply the second transformation to compensate the platform delay via adjusting the timing parameters at the code level. We formulate the adjustment mechanism using integer linear programming. If such an adjustment is feasible, generating the code with the new timing parameters guarantees the implemented system to meet the timing requirements. We validate our framework with case studies running on Patient-Controlled Analgesia (PCA) infusion pump platforms.

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“…Most notably, existing work on the implementability of timed automata (TA) incorporates the platform information by explicitly modeling the execution platform [3], [4], [18] or by modifying the TA semantics to reflect the implementation platform semantics (e.g., [13], [14], [19]). Real-time scheduling has also been combined with TA in [2], and a number of automata-and actor-oriented scheduling interfaces have also been developed [5], [8], [17]. However, these existing techniques consider rather restrictive platform semantics, such as assuming only a small subset of possible implementations [4] or ignoring various sources of timing delays [3], [18], [19].…”

Section: Introductionmentioning

confidence: 99%

Platform-Specific Timing Verification Framework in Model-Based Implementation

Kim¹,

Liu²,

Phan³

et al. 2015

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2015

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In the model-based implementation methodology, the timed behavior of the software is typically modeled independently of the platform-specific timing semantics such as the delay due to scheduling or I/O handling. Although this approach helps to reduce the complexity of the model, it leads to timing gaps between the model and its implementation. This paper proposes a platform-specific timing verification framework that can be used to formally verify the timed behavior of an implementation that has been developed from a platformindependent model. We first describe a way to categorize the interactions among the software, a platform, and the environment in the form of implementation schemes. We then present an algorithm that systematically transforms a platform-independent model into a platform-specific model under a given implementation scheme. This transformation algorithm ensures that the timed behavior of the platform-specific model is close to that of the corresponding implementation. Our case study of an infusion pump system shows that the measured timing delay of the system is bounded by the formally verified bound of its platform-specific model. Keywordsformal specification, program verification, scheduling, software metrics, timing, I/O handling, formal verification, infusion pump system, model complexity, model-based implementation methodology, platformindependent model, platform-specific model, platform-specific timing semantics, platform-specific timing verification framework, scheduling, timing delay, Automata, Computational modeling, Delays, Semantics, Software, Synchronization Abstract-In the model-based implementation methodology, the timed behavior of the software is typically modeled independently of the platform-specific timing semantics such as the delay due to scheduling or I/O handling. Although this approach helps to reduce the complexity of the model, it leads to timing gaps between the model and its implementation. This paper proposes a platform-specific timing verification framework that can be used to formally verify the timed behavior of an implementation that has been developed from a platform-independent model. We first describe a way to categorize the interactions among the software, a platform, and the environment in the form of implementation schemes. We then present an algorithm that systematically transforms a platform-independent model into a platform-specific model under a given implementation scheme. This transformation algorithm ensures that the timed behavior of the platform-specific model is close to that of the corresponding implementation. Our case study of an infusion pump system shows that the measured timing delay of the system is bounded by the formally verified bound of its platform-specific model.

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Real-time scheduling interfaces and contracts for the design of distributed embedded systems

Cited by 12 publications

References 25 publications

Proceedings of the 4th Analytic Virtual Integration of Cyber-Physical Systems Workshop December 3 Vancouver Canada

Proceedings of the 4th Analytic Virtual Integration of Cyber-Physical Systems Workshop December 3 Vancouver Canada

Determining Timing Parameters for the Code Generation from Platform-Independent Timed Models

Platform-Specific Timing Verification Framework in Model-Based Implementation

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