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Safety Manager: Servicio Iot Para Asegurar El Buen Comportamiento De Las Máquinas Y Controles En La Fábrica Digital (digital Safety Manager: Iot Service To Assure The Safe Behaviour Of Machines And Controls In The Digital Industry)

Author(s): ORCID


ORCID
ORCID
Medium: journal article
Language(s): Spanish
Published in: DYNA, , n. 1, v. 97
Page(s): 18-22
DOI: 10.6036/10243
Abstract:

The digital industry requires increasingly complex and reliable software systems. They need to control and make critical decisions at runtime. As a consequence, the verification and validation of these systems has become a major research challenge. At design and development time, model testing techniques are used while run-time verification aims at verifying that a system satisfies a given property. The latter technique complements the former. The solution presented in this paper targets embedded systems whose software components are designed by state machines defined by Unified Modelling Language (UML). The CRESCO (C++ REflective State-Machines based observable software COmponents) platform generates software components that provide internal information at runtime and the verifier uses this information to check system-level reliability/safety contracts. The verifier detects when a system contract is violated and initiates a safeState process to prevent dangerous scenarios. These contracts are defined by internal information from the software components that make up the system. Thus, as demonstrated in the tested experiment, the robustness of the system is increased. All software components (controllers), such as the verifier, have been deployed as services (producers/consumers) of the Arrowhead IoT platform: the controllers are deployed on local Arrowhead platforms (Edge) and the verifier (Safety Manager) is deployed on an Arrowhead platform (Cloud) that will consume controllers on the Edge and ensure the proper functioning of the plant controllers. Keywords: run-time monitoring, robustness, software components, contracts, software models, state machines

Structurae cannot make the full text of this publication available at this time. The full text can be accessed through the publisher via the DOI: 10.6036/10243.
  • About this
    data sheet
  • Reference-ID
    10648736
  • Published on:
    07/01/2022
  • Last updated on:
    07/01/2022
 
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