TT 09 - Real-time and networked embedded computing, industrial iot technologies and applications

Track Chairs

Reza Abrishambaf, Miami University, USA and  Frank Golatowski, University of Rostock, Germany and  Gaetano Patti, University of Catania, Italy and  Paulo Pedreiras, Universidade de Aveiro, Portugal

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Real-time systems bring significant challenges and opportunities in embedded computing techniques to speed up industrial and commercial services. The emergence of Internet-of-Things (IoT) – a smart high-level concept of progressing the world through connecting and integrating all things into a huge network - has also been improving the communication efficiency for these services. A networked embedded computing has thus gradually been drawing developers’ attention to be widely applied in abundant applications. This track focuses on models, techniques, methods, analysis and applications that are related to real-time and embedded computing and IoT based networking and technologies.

Topics under this track include (but not limited to)

  • Innovations in real-time capable networks
  • Software Defined Networks (SDN) and Time-Sensitive Networking (TSN)
  • Deterministic IoT technologies
  • Hard Real-time SOA and RESTful industrial communication
  • Real-time issues of distributed control in industrial cyber-physical systems
  • Industrial IoT protocols (OPC UA, DDS, MQTT, AMQP, COAP, IEEE 11073 SDC, …)
  • Real-time analysis of location-based systems
  • Verification and validation of distributed embedded applications
  • Security verification of real-time (operating) systems and industrial automation systems
  • Factors influencing latencies in emerging industrial communication systems
  • Combining legacy real-time networks (e.g. CAN) with emerging real-time IP-based networks (TSN, SDN)
  • Blockchain and distributed ledger technologies in networked embedded systems and IoT applications
  • Deep learning technologies for distributed real-time embedded systems
  • Performance analysis (of distributed real-time systems)
  • Emerging real-time operating systems and real-time hypervisors
  • Hard real-time services in edge and cloud
  • Timing and resource analysis of (distributed) resource-constrained AI
  • 5G for industrial applications

Track Committee

  • Luis Almeida, Univ. of Porto, PT
  • Mohammad Ashjaei, Mälardalen Univ., SE
  • Paulo Bartolomeu, Univ. of Aveiro, PT
  • Moris Behnam, Mälardalen Univ., SE
  • Reinder Bril, Tech. Univ. Eindhoven (TU/e), NL
  • Wenbin Dai, Shanghai Jiao Tong Univ., CN
  • Peter Danielis, Univ. of Rostock, DE
  • Ramez Daoud, American Univ. in Cairo, EG
  • Michael Ditze, Stihl GmbH, DE
  • Antonio Espirito-Santo, Univ. of Beira Interior, PT
  • Tullio Fachinnetti, Univ. of Pavia, IT
  • Paolo Ferrari, Univ. of Brescia, IT
  • Marisol García Valls, Univ. Polit. de València, ES
  • Yacine Ghamri-Doudane, La Rochelle Univ., FR
  • Rafia Inam, Ericsson, SE
  • Stavros Koubias, Univ. of Patras, GR
  • Luca Leonardi, Univ. of Catania, IT
  • Michele Luvisotto, ABB Power Grids Sweden – AB Power Grids Research, SE
  • Ahlem Mifdaoui, Univ. of Toulouse, FR
  • Christoph Niedermeier, Siemens AG, DE
  • Borislav Nikolic, Continental Autom. GmbH, DE
  • Roman Obermaisser, Univ. of Siegen, DE
  • Zhibo Pang, ABB Corporate Research and Royal Institute of Technology, SE
  • Michael Paulitsch, Intel, AT
  • Paul Pop, Technical Univ. of Denmark, DK
  • Bruno Quoitin, Univ. of Mons, BE
  • Markus Rentschler, Balluff GmbH, DE
  • Achim Rettberg, Univ. App. Sc. Hamm-Lippstadt, DE
  • Stefano Rinaldi, Univ. of Brescia, IT
  • Yang Shi, Univ. of Victoria, US
  • Michael Short, Teesside Univ., UK
  • Luis Silva, Instituto de Telecomunicacoes and Bosch/Ovar, PT
  • Federico Tramarin, Univ. Modena e Reggio Emilia, IT
  • Stavros Tripakis, Northeastern Univ., US
  • Pal Varga, Budapest Univ. of Technology and Economics, HU
  • Alexander Viehl, FZI Forschungszentrum Informatik, DE
  • Feisheng Yang , Northwestern Polyt. Univ., CN
  • Daesub Yoon, ETRI, KR
  • Janusz Zalewski, Florida Gulf Coast Univ., US