| 1. |
- Conceicao, Filipe, et al.
(författare)
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Empowering industry 4.0 and autonomous drone scouting use cases through 5G-DIVE solution
- 2021
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Ingår i: 2021 Joint European Conference on Networks and Communications and 6G Summit, EuCNC/6G Summit 2021. - 2575-4912. - 9781665415262 ; , s. 265-270
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Konferensbidrag (refereegranskat)abstract
- The 5G Edge Intelligence for Vertical Experimentation (5G-DIVE) project aims at demonstrating the technical merits and business value proposition of 5G technologies in two vertical pilots, namely the Industry 4.0 (I4.0) and Autonomous Drones Scout (ADS) pilots. This paper presents an overview of the overall 5G-DIVE solution and reports the results of the initial validation campaign of the selected use case, featuring 5G connectivity, distributed Edge computing, and artificial intelligence. The initial results for the I4.0 provide a baseline for next step validation campaign targeting a broader scale 5G implementation, while the ADS results provides promising results for enhancing the autonomous navigation in real-time.
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| 2. |
- Pettersson, K., et al.
(författare)
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AI-based enhancement of access and mobility procedures in cellular networks : An experimental study
- 2021
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Ingår i: 2021 Joint European Conference on Networks and Communications and 6G Summit, EuCNC/6G Summit 2021. - : IEEE. - 9781665415262 ; , s. 454-459
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Konferensbidrag (refereegranskat)abstract
- The 5G wireless networks support diverse use-cases particularly ultra-reliable low-latency communications (URLLC). One of the key challenges in supporting URLLC services is to enhance the performance of the random access procedure to guarantee the stringent latency requirements. This is not only challenging for URLLC services but any delay sensitive services like voice over LTE (VoLTE) or voice over New Radio (VoNR). The access and mobility procedures rely on the random access procedure. Enhancing this procedure using artificial intelligence can thus support even more stringent latency requirements. In this paper, we present an experimental study aiming at performance evaluation of the access and mobility procedures based on an experimentation and data collection from the Monroe platform. We study the main causes of the delay induced to the access and mobility procedures, and evaluate machine learning based techniques to classify different procedures in terms of experienced delay and failure. Such results take step towards enabling the User Equipment (UE) to take appropriate actions for coping with predicted sub-optimal access or mobility procedures.
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| 3. |
- Vilalta, Ricard, et al.
(författare)
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TeraFlow: Secured autonomic traffic management for a tera of SDN flows
- 2021
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Ingår i: 2021 Joint European Conference on Networks and Communications and 6G Summit, EuCNC/6G Summit 2021. - 9781665415262 ; , s. 377-382
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Konferensbidrag (refereegranskat)abstract
- TeraFlow proposes a new type of secure, cloud-native Software Defined Networking (SDN) controller that will radically advance the state-of-the-art in beyond 5G networks by introducing novel micro-services architecture, and provide revolutionary features for both flow management (service layer) and optical/microwave network equipment integration (infras-tructure layer) by adapting new data models. TeraFlow will also incorporate security using Machine Learning (ML) and forensic evidence for multi-tenancy based on Distributed Ledgers. Finally, this new SDN controller shall be able to integrate with the current Network Function Virtualization (NFV) and Multi-access Edge Computing (MEC) frameworks as well as to other networks. The target pool of TeraFlow stakeholders expands beyond the traditional telecom operators towards edge and hyperscale cloud providers.
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