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  1. Pubblicazioni

Hardware/Software self-adaptation in CPS: The CERBERO project approach

Contributo in Atti di convegno
Data di Pubblicazione:
2019
Citazione:
Hardware/Software self-adaptation in CPS: The CERBERO project approach / Palumbo, F.; Fanni, T.; Sau, C.; Rodriguez, A.; Madronal, D.; Desnos, K.; Morvan, A.; Pelcat, M.; Rubattu, C.; Lazcano, R.; Raffo, L.; de la Torre, E.; Juarez, E.; Sanz, C.; Sanchez de Rojas, P.. - 11733:(2019), pp. 416-428. ( 19th International Conference on Embedded Computer Systems: Architectures, Modeling, and Simulation, SAMOS 2019 grc 2019) [10.1007/978-3-030-27562-4_30].
Abstract:
Cyber-Physical Systems (CPS) are interconnected devices, reactive and dynamic to sensed external and internal triggers. The H2020 CERBERO EU Project is developing a design environment composed by modelling, deployment and verification tools for adaptive CPS. This paper focuses on its efficient support for run-time self-adaptivity.
Tipologia CRIS:
4.1 Contributo in Atti di convegno
Keywords:
Cyber-Physical Systems; HW monitoring; HW reconfiguration; Run-time management; Self-adaptivity
Elenco autori:
Palumbo, F.; Fanni, T.; Sau, C.; Rodriguez, A.; Madronal, D.; Desnos, K.; Morvan, A.; Pelcat, M.; Rubattu, C.; Lazcano, R.; Raffo, L.; de la Torre, E.; Juarez, E.; Sanz, C.; Sanchez de Rojas, P.
Autori di Ateneo:
RUBATTU Claudio
Link alla scheda completa:
https://iris.uniss.it/handle/11388/239431
Titolo del libro:
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pubblicato in:
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
Journal
LECTURE NOTES IN ARTIFICIAL INTELLIGENCE
Series
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