Location

Hilton Waikoloa Village, Hawaii

Event Website

http://hicss.hawaii.edu/

Start Date

1-3-2018

End Date

1-6-2018

Description

For studying the effects of deviations for uncertain inputs of systems, often multi-run simulation is employed, which is time-consuming. Unfortunately, such simulations also do not directly support the traceability of such effects. A semi-symbolic modeling approach based on Affine Arithmetic Forms allows the representation of uncertainty in terms of ranges. Simulations of such models directly include propagation of deviations and their traceability. This paper presents such a semi-symbolic model of a cyber-physical system including coordination of safety-critical and interacting features. For feature coordination, this model introduces handling discrete uncertainty with two different behavioral modes and their integration. Based on this model, a single simulation run allowed us studying the effects of several deviations. In addition, this modeling approach facilitates specific analyses of deviations based on the traceability information. As a result from simulation and analyses, we got a better understanding of the different deviation propagations within our model.

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Jan 3rd, 12:00 AM Jan 6th, 12:00 AM

Semi-symbolic Simulation and Analysis of Deviation Propagation of Feature Coordination in Cyber-physical Systems

Hilton Waikoloa Village, Hawaii

For studying the effects of deviations for uncertain inputs of systems, often multi-run simulation is employed, which is time-consuming. Unfortunately, such simulations also do not directly support the traceability of such effects. A semi-symbolic modeling approach based on Affine Arithmetic Forms allows the representation of uncertainty in terms of ranges. Simulations of such models directly include propagation of deviations and their traceability. This paper presents such a semi-symbolic model of a cyber-physical system including coordination of safety-critical and interacting features. For feature coordination, this model introduces handling discrete uncertainty with two different behavioral modes and their integration. Based on this model, a single simulation run allowed us studying the effects of several deviations. In addition, this modeling approach facilitates specific analyses of deviations based on the traceability information. As a result from simulation and analyses, we got a better understanding of the different deviation propagations within our model.

http://aisel.aisnet.org/hicss-51/st/metrics_and_models_for_systems/3