An Intelligent Agent-Based Industrial IoT Framework for Time-Critical Data Stream Processing
Autor: | Ines Gharbi, Kamel Barkaoui, Ben Ahmed Samir |
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Přispěvatelé: | CEDRIC. Systèmes sûrs (CEDRIC - SYS), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Faculté des Sciences Mathématiques, Physiques et Naturelles de Tunis (FST), Université de Tunis El Manar (UTM), Bouzefrane S., Laurent M., Boumerdassi S., Renault E. (eds) |
Rok vydání: | 2021 |
Předmět: |
business.industry
Computer science Data stream mining Smart objects Multi-agent system Node (networking) Distributed computing 020206 networking & telecommunications Cloud computing 02 engineering and technology Petri net computer.software_genre Intelligent agent 0202 electrical engineering electronic engineering information engineering [INFO]Computer Science [cs] 020201 artificial intelligence & image processing Digital manufacturing business computer ComputingMilieux_MISCELLANEOUS |
Zdroj: | Mobile, Secure, and Programmable Networking ISBN: 9783030675493 MSPN 6th International Conference on Mobile, Secure and Programmable Networking (MSPN), 2020 6th International Conference on Mobile, Secure and Programmable Networking (MSPN), 2020, Oct 2020, Paris (virtual), France. pp.195-208, ⟨10.1007/978-3-030-67550-9_13⟩ |
Popis: | The Industrial Internet of Things (IIoT) intends to speed up digital manufacturing transformation. As a crucial role, Industrial IoT aims to improve the performance and reliability of the processing of massive time-critical data continually generated by heterogeneous smart objects. To resolve these challenges, Industrial IoT incorporates the Fog computing paradigm to support intelligence near the Edge level as an additional alternative to Cloud computing. However, a Fog node allows dealing with only limited data processing, storage, and communications. Indeed, a heavy load processing task requires multiple Fog nodes to achieve its execution and may need an intelligent dynamic pooling of Cloud resources. In this paper, we propose PIAF (A Processing Intelligent Agent Running on Fog Infrastructure). An intelligent agent-based IIoT framework that runs on the Fog infrastructure to distribute the processing of time-critical data streams. We outline its several components and their interactions. Then, for this purpose, we model the PIAF framework using the Time Petri Nets modeling. |
Databáze: | OpenAIRE |
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