2018
DOI: 10.1007/s40998-018-0091-3
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Modeling, Simulation and Verification of Probabilistic Reconfigurable Discrete-Event Systems Under Energy and Memory Constraints

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Cited by 4 publications
(6 citation statements)
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“…We distinguish two parts for designing DESs: the configurations that specify different system behaviors, and the controller that handles the reconfiguration scenarios by switching from a configuration to another. These models can be validated with the object constraint language OCL [29] or with formal methods [28] (Figure 3). We define (i) A general profile R-UML extending UML for specifying hardware and software reconfiguration scenarios [115] extended to [116], (ii) A general framework to adapt reconfigurable distributed intelligent systems under functional and real-time constraints [52], (iii) A new specific event-triggered component named R-FB that extends Function Blocks in the industrial standard IEC61499 [24], (iv) A new component named RA2DL extending the architecture analysis and design language (AADL) [22], (v) A specific meta-model for reconfigurable wireless sensor networks for handling all possible reconfigurable forms [21], (vi) A specific model for reconfigurable smart grids that react and cover possible faults in distribution lines [12], and (vi) a specific model for reconfigurable microgrids to predict weather conditions for estimating the future energy availability [8].…”
Section: Overview On Design and Validation Of Rdesmentioning
confidence: 99%
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“…We distinguish two parts for designing DESs: the configurations that specify different system behaviors, and the controller that handles the reconfiguration scenarios by switching from a configuration to another. These models can be validated with the object constraint language OCL [29] or with formal methods [28] (Figure 3). We define (i) A general profile R-UML extending UML for specifying hardware and software reconfiguration scenarios [115] extended to [116], (ii) A general framework to adapt reconfigurable distributed intelligent systems under functional and real-time constraints [52], (iii) A new specific event-triggered component named R-FB that extends Function Blocks in the industrial standard IEC61499 [24], (iv) A new component named RA2DL extending the architecture analysis and design language (AADL) [22], (v) A specific meta-model for reconfigurable wireless sensor networks for handling all possible reconfigurable forms [21], (vi) A specific model for reconfigurable smart grids that react and cover possible faults in distribution lines [12], and (vi) a specific model for reconfigurable microgrids to predict weather conditions for estimating the future energy availability [8].…”
Section: Overview On Design and Validation Of Rdesmentioning
confidence: 99%
“…The work reported in [133] extended to [28] extends R-TNCES to generalized reconfigurable timed net condition event systems (GR-TNCES) for formal modeling and verification of unpredictible reconfiguration scenarios characterized with probabilistic distributions. We characterize also the different system behaviors with probabilities.…”
Section: B Modeling With Reconfigurable Stochastic Petri Netsmentioning
confidence: 99%
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“…The lifetime of WSN is determined by the battery reserves of the sensor nodes composing it. When a sensor node runs with insufficient energy, the QoS degrades and the deadline of messages will not be met [12]- [14]. Due to these constraints, WSN should be highly flexible and reconfigurable so they can adapt their behavior to the environment according to circumstances at run time [15]- [21].…”
Section: Introductionmentioning
confidence: 99%
“…The reconfiguration of such a system can culminate with a blocking problem that is sometimes unsafe or does not respect real-time properties [74], [76], [77]. We check a safe behavior of this reconfigurable architecture [78]- [80] after unexpected hardware conflicts using PRISM model checker [42]. It applies an exhaustive CTL-formal verification to ensure a safe reconfiguration [83], [85] of sources, tests, and decisions.…”
mentioning
confidence: 99%