The aim of the research programme is twofold:
(1) to advance the state of the art and practice in predictable realtime and Internet networking and
(2) training of early stage researchers to prepare them for careers in advanced technical development and research.
By (1) the programme will contribute to strengthening the competitiveness of European industry and engineering research. By (2) the programme will provide competence that could play key roles in the European research and development of advanced products for many years to come.
The technological basis for RetNet is the predictable communication network technology that has been developed into products by the private sector partner TTTech. This programme aims to substantially broaden the applicability of this technology by
(1) developing a wireless version of TTTech’s TTEthernet technology, addressing the fundamental scientific challenge of providing dependable wireless communication, and
(2) increasing the flexibility of TTTech’s TTEthernet technology by extending it with on-line adaption and admission of traffic, thereby making the technology applicable in more dynamic “Internet-like” settings.
Use cases from multiple industrial domains will guide the research and form the basis for evaluation and demonstration.
Full partners in the project are:
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Associated partners are:
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Funded by: The European Commission under the 7th Framework Programme FP7-PEOPLE-ITN call 2013. Grant agreement 607727
Dependable real-time communications for systems with integrated wired and wireless connectivity (Sep 2024) Pablo Gutiérrez Peón
Runtime Monitoring for Safe Automated Driving Systems (Nov 2020) Ayhan Mehmed
Systematic False Positive Mitigation in Safe Automated Driving Systems (Nov 2020) Ayhan Mehmed, Wilfried Steiner , Aida Causevic 2020 International Symposium on Industrial Electronics and Applications (INDEL 2020)
Formal Verification of an Approach for Systematic False Positive Mitigation in Safe Automated Driving System (Apr 2020) Ayhan Mehmed, Wilfried Steiner , Aida Causevic
Methods for Efficient and Adaptive Scheduling of Next-Generation Time-Triggered Networks (Oct 2019) Francisco Pozo
Runtime Monitoring of Automated Driving Systems (Oct 2019) Ayhan Mehmed
Partner | Type |
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Technische Universität Wien | Academic |
ABB AB | Industrial |
Ericsson AB | Industrial |
Mallorca WiFi | Industrial |
TTTech Computertechnik AG | Industrial |
Volvo Construction Equipment AB | Industrial |