The integration of Time-Sensitive Networking (TSN) and 5G communication is crucial for achieving ultra-reliable and low-latency communication (URLLC) in various domains. This includes applications like industrial automation involving mobile and collaborative robots, as well as Industrial IoT (IIoT). However, an exhaustive performance analysis of mixed 5G-TSN networks that support the unique features of TSN and 5G is lacking. Furthermore, a deeper understanding of TSN traffic scheduling in the 5G system (5GS) is necessary. To address this gap, we propose a novel 5G-TSN Quality-of-Service (QoS) aware simulation framework that incorporates priority-based scheduling in the 5GS. Our framework integrates the latest 5G and TSN simulation libraries using OMNeT++ and provides the first-ever results of the performance analysis of a 5G-TSN converged network. We implement the 5G-TSN bridge translation mechanism and introduce a QoS mapping algorithm for our framework. Through a detailed performance evaluation, we assess the impact of 5G QoS-aware scheduling methods on the overall network performance. Our open-source framework utilizes the latest Simu5G and INET4.4 libraries and simulates two different 5G-TSN scenarios to provide comprehensive insights. The results of our study demonstrate that the performance of the 5G-TSN network is significantly influenced by the scheduling in the 5G network, as a substantial portion of the overall delay originates from the 5GS. Notably, our findings reveal that the 5G-TSN network can achieve latency values within 3ms for TSN traffic, emphasizing the need for a joint scheduling mechanism to meet URLLC requirements.


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    Titel :

    5GTQ: QoS-Aware 5G-TSN Simulation Framework


    Beteiligte:


    Erscheinungsdatum :

    2023-10-10


    Format / Umfang :

    2040663 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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