WO2024037745A1

WO2024037745A1 - 5g-tsn bridge, bridge, apparatus, method, and computer program for assigning quality of service flows

Info

Publication number: WO2024037745A1
Application number: PCT/EP2023/054620
Authority: WO
Inventors: Niklas AMBROSY
Original assignee: Volkswagen Aktiengesellschaft
Priority date: 2022-08-15
Filing date: 2023-02-23
Publication date: 2024-02-22

Abstract

Embodiments relate to a 5G-TSN (5th Generation- Time-Sensitive-Network) bridge, a bridge, an apparatus, a method and a computer program for assigning quality of service, QoS, flows between a first network and a second network. The method (10) for assigning QoS flows between a first network and a second network, wherein the first and second networks form a convergent network, comprises receiving (12) a first QoS profile for a data flow from the first network; determining (14) a second QoS profile for the data flow in the second network based on fitting the first QoS profile to QoS profiles of the second network; and assigning (14) the QoS flows for the data flow in the first and second network to each other based on the first and second QoS profiles.

Description

5G-TSN Bridge, Bridge, Apparatus, Method, and Computer Program for Assigning Quality of Service Flows

The present invention relates to the field of inter-network service handling. Embodiments relate to a 5G-TSN (5^th Generation- Time-Sensitive-Network) bridge, a bridge, an apparatus, a method and a computer program for assigning quality of service, QoS, flows between a first network and a second network, more particularly, but not exclusively, to a concept for assigning QoS profiles for a data flow between networks.

Flexible production processes for Industry 4.0 require simple reconfigurability and mobility and therefore a combination of wired and wireless real-time capable communication technologies. In particular, this is the case for time-critical machine communication. Possible use cases include, wireless human-machine interfaces (HMIs) with emergency stop or Automated Guided Vehicles (AGVs) in order to guarantee personal safety in mobile applications. Time-Sensitive Networking (TSN) and 5G mobile radio are considered suitable candidates to meet the communication requirements of these use cases.

TSN is an umbrella term for several IEEE 802.1 sub-standards that enable real-time capabilities and determinism for Ethernet. TSN includes mechanism for time synchronization, bounded latency, high reliability, and dedicated resource management, e.g. IEEE: Time-Sensitive Networking (TSN) Task Group, 1. ieee802.org/tsn, accessed 29 Mar 2022.

The IEC/IEEE 60802 TSN Industrial Automation Profile intends to explicitly standardize the use of TSN in industrial automation, but is currently still in the draft stage, cf. IEC/IEEE 60802: TSN Profile for Industrial Automation, 2021.

Further details can be found in:

[3G21a] 3GPP: TS 23.501: System architecture for the 5G System (V17.3.0), 2021 ;

[3G21b] 3GPP: TS 23.503: Policy and charging control framework for the 5G System

(V17.3.0), 2021 ; [5G19] 5G-ACIA: 5G Non-Public Networks for Industrial Scenarios, 2019;

[5G21a] 5G-ACIA: Integration of 5G with Time-Sensitive Networking for Industrial Communications, 2021;

[5G21b] 5G-ACIA: 5G QoS for Industrial Automation, 2021 ;

[Br19] Bruckner, D. et al.: An Introduction to OPC UA TSN for Industrial Communication

Systems. Proceedings of the IEEE 6/107, pp. 1121—1131, 2019;

[I E21] IEC/IEEE 60802: TSN Profile for Industrial Automation, 2021;

[I E22] IEEE: Time-Sensitive Networking (TSN) Task Group. 1. ieee802.org/tsn, accessed 29 Mar 2022;

[In19] Industrial Internet Consortium: Time Sensitive Networks for Flexible Manufacturing Testbed - Characterization and Mapping of Converged Traffic Types, 2019;

[Ma20] Martenvormfelde, L. et al.: A Simulation Model for Integrating 5G into Time Sensitive Networking as a Transparent Bridge: 25th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), pp. 1103-1106, 2020;

[Ma21] Martenvormfelde, L. et al.: Co-configuration of 5G and TSN enabling end-to-end quality of service in industrial communications: Kommunikation in der Automation (KommA 2021) 12. Jahreskolloquium, 18.11.2021 in Verbindung mit dem Industrial Radio Day, 17.11.2021 Tagungsband, Magdeburg, 2021 ;

[MP21] Magnusson, A.; Pantzar, D.: Integrating 5G Components into a TSN Discrete Event Simulation Framework. Master thesis, Vasteras, Sweden, 2021 ;

[Pa21] Patel, D. et al.: Time error analysis of 5G time synchronization solutions for time aware industrial networks: 2021 IEEE International Symposium on Precision Clock Synchronization for Measurement, Control, and Communication (ISPCS). IEEE, pp. 1-6, 2021;

[RCK20] Rost, P. M.; Chandramouli, D.; Kolding, T.: 5G plug-and-produce - How the 3GPP 5G System facilitates Industrial Ethernet, 2020;

[Sa22] Satka, Z. et al.: Developing a Translation Technique for Converged TSN-5G Communication: 2022 IEEE 18th International Conference on Factory Communication Systems (WFCS). IEEE, pp. 1-8, 2022;

[SJ21] Schriegel, S.; Jasperneite, J.: A Migration Strategy for Profinet Toward Ethernet TSN-Based Field-Level Communication: An Approach to Accelerate the Adoption of Converged IT/OT Communication. IEEE Industrial Electronics Magazine 4/15, pp. 43-53, 2021 ; and

[SS21] Striffler, T.; Schotten, H. D.: The 5G Transparent Clock: Synchronization Errors in Integrated 5G-TSN Industrial Networks: 2021 IEEE 19th International Conference on Industrial Informatics (INDIN). IEEE, pp. 1-6, 2021.

There is a demand for an improved concept for managing QoS requirements between networks. This demand is met by the appended independent claims.

Embodiments are based on the finding of a traffic priority mapping for a joint 5G-TSN QoS model. In order to integrate 5G mobile radio into Time-Sensitive Networking (TSN), the 3rd Generation Partnership Project (3GPP) specified the model of a virtual 5G-TSN bridge. This contains TSN translators which map principles such as time synchronization and Quality of Service (QoS) mechanisms from TSN to 5G. Embodiments provide a concrete implementation for assigning quality of service, QoS, flows between a first network and a second network.

Embodiments may identify the differences of TSN and 5G in the prioritization of data traffic and provide possible solutions to map the priorities to each other. This may serve as a basis for the development of TSN translators and finally for a joint QoS model.

Embodiments provide a method for assigning quality of service, QoS, flows between a first network and a second network. The first and second networks form a convergent network. The method comprises receiving a first QoS profile for a data flow from the first network and determining a second QoS profile for the data flow in the second network based on fitting the first QoS profile to QoS profiles of the second network. The method further comprises assigning the QoS flows for the data flow in the first and second networks to each other based on the first and second QoS profiles. Embodiments may therewith provide an effective mechanism for assigning QoS flows.

In embodiments, the first network may be a wired Time Sensitive Network, TSN, according to IEEE, Institute of Electrical and Electronics Engineers, 802.1 standards. The second network may be a wireless 5th Generation, 5G, system as specified by the 3rd Generation Partnership Project. Embodiments may hence provide a bridging mechanism between a TSN and a 5G network.

For example, the determining of the second QoS profile may comprise fitting the first QoS profile to a predefined or standardized QoS profile of the second network. Embodiments may therefore provide an efficient mapping of the QoS profiles of different networks. For example, the second network is a public network integrated non-public network.

In further embodiments, the determining of the second QoS profile may comprise fitting the first QoS profile to a QoS profile of the second network by configuring an according QoS profile in the second network. Embodiments may therefore be able to provide an effective adaptation mechanism for QoS of different networks. For example, the second network is a standalone non-public network.

The first and the second QoS profiles comprise a priority level for the data flow. Embodiments may provide an inter-network priority matching mechanism for convergent networks.

The first and the second QoS profiles comprise one or more requirements of the group of latency, packet error rate, frame length, periodicity, or data rate for the data flow. Embodiments may therewith enable assignments of one or more QoS parameters.

For example, the first QoS profile comprises a TSN Traffic class and priority, and the second QoS profile comprises a 5G quality indicator, 5QI, and a 5G priority level. The fitting of the first QoS profile to QoS profiles of the second network may comprise one or more mappings of the table of

wherein the values given in parenthesis indicate a fallback option for isochronous uplink time division duplex traffic.

In some embodiments, the first QoS profile comprises a TSN priority, and the second QoS profile comprises a 5G quality indicator, 5QI, and a priority level. The fitting of the first QoS profile to QoS profiles of the second network may comprise one or more mappings of the table of

, wherein

GBR is Guaranteed Bit Rate,

DC-GBR is Delay-Critical GBR,

PDB is Packet Delay Budget,

PER is Packet Error Rate, and

MDBV is Maximum Data Burst Volume, as defined by 3GPP. A further embodiment is a computer program having a program code for performing a method as described herein, when the computer program is executed on a computer, a processor, or a programmable hardware component.

Another embodiment is an apparatus, which comprises one or more interfaces configured to communicate with one or more components of a network and processing circuitry configured to control the one or more interfaces and to perform a method as described herein.

Yet another embodiment is a bridge between a first network and a second network comprising an embodiment of the apparatus. A further embodiment is a 5G-TSN bridge comprising an embodiment of the bridge.

Some examples of apparatuses and/or methods will be described in the following by way of example only, and with reference to the accompanying figures, in which

Fig. 1 shows a block diagram of an embodiment of a method for assigning quality of service, QoS, flows between a first network and a second network;

Fig. 2 shows a block diagram of an embodiment of an apparatus for assigning QoS flows between a first network and a second network, and an embodiment of a bridge; and

Fig. 3 shows an embodiment of a 5G system as a virtual TSN bridge.

Some embodiments are now described in more detail with reference to the enclosed figures. However, other possible embodiments are not limited to the features of these embodiments described in detail. Other embodiments may include modifications of the features as well as equivalents and alternatives to the features. Furthermore, the terminology used herein to describe certain embodiments should not be restrictive of further possible embodiments.

Throughout the description of the figures, same or similar reference numerals refer to same or similar elements and/or features, which may be identical or implemented in a modified form while providing the same or a similar function. The thickness of lines, layers and/or areas in the figures may also be exaggerated for clarification. When two elements A and B are combined using an 'or', this is to be understood as disclosing all possible combinations, e.g., only A, only B as well as A and B, unless expressly defined otherwise in the individual case. As an alternative wording for the same combinations, "at least one of A and B" or "A and/or B" may be used. This applies equivalently to combinations of more than two elements.

If a singular form, such as “a”, “an” and “the” is used and the use of only a single element is not defined as mandatory either explicitly or implicitly, further examples may also use several elements to implement the same function. If a function is described below as implemented using multiple elements, further examples may implement the same function using a single element or a single processing entity. It is further understood that the terms "include", "including", "comprise" and/or "comprising", when used, describe the presence of the specified features, integers, steps, operations, processes, elements, components and/or a group thereof, but do not exclude the presence or addition of one or more other features, integers, steps, operations, processes, elements, components and/or a group thereof.

Fig. 1 shows a block diagram of an embodiment of a method 10 for assigning quality of service, QoS, flows between a first network and a second network. The first and second networks form a convergent network. Here and in the following, convergence or convergent networks means using of one medium across all types of network instead of carrying information separately within distinct networks. In the convergent networks, different forms of information can be reengineered to provide better, more flexible service to the user. For example, telephone networks can transmit data and video and cable networks are able to provide voice services. The reason media convergence occurs is due to both corporation and consumer developments. Here convergent network means that a service with a data flow uses both networks.

The method 10 comprises receiving 12 a first QoS profile for a data flow from the first network and determining 14 a second QoS profile for the data flow in the second network based on fitting the first QoS profile to QoS profiles of the second network. The method 10 further comprises assigning the QoS flows for the data flow in the first and second networks to each other based on the first and second QoS profiles.

Fig. 2 shows a block diagram of an embodiment of an apparatus 20 for assigning QoS flows between a first network and a second network, and an embodiment of a bridge 200. The apparatus 20 comprises one or more interfaces 22 configured to communicate with one or more components of a network. The apparatus 20 further comprises processing circuitry 24, which is coupled to the one or more interfaces 22, and which is configured to control the one or more interfaces 22 and to perform a method 10 as described herein. Yet another embodiment is a bridge 200 between a first network and a second network comprising an embodiment of the apparatus 20. The bridge 200 is shown in broken lines as it is optional from the perspective of the apparatus 20.

For example, the first network is a wired Time Sensitive Network, TSN, according to IEEE, Institute of Electrical and Electronics Engineers, 802.1 standards. The second network may be a wireless 5th Generation, 5G, system as specified by the 3rd Generation Partnership Project. Hence, the bridge 200 may be a 5G-TSN bridge 300 as will be detailed subsequently.

The one or more interfaces 22 may be implemented as any means for communicating information, e. g. transmitting, receiving, or transmitting and receiving. For example, the one or more interfaces 22 may correspond to one or more contacts, inputs/outputs, and/or modules to communicate physical signals. The one or more interfaces 22 may comprise a software interface/module and/or an interface to a transmission medium. The one or more interfaces 22 may be configured to take as input and/or provide as output any data that is processed by the processing circuitry 24. The one or more interfaces 22 may enable communication with components of a network or device, e.g. a server, a router, a translator a gateway, etc.

As further shown in Fig. 2 the respective one or more interfaces 22 are coupled to the processing circuitry 24, which may comprise one or more processors, and which controls the one or more interfaces 22. In examples the processing circuitry 24 may be implemented using one or more processing units, one or more processing devices, any means for processing, such as a processor, processing circuits, a computer or a programmable hardware component being operable with accordingly adapted software. In other words, the described function of the processing circuitry may as well be implemented in software, which is then executed on one or more programmable hardware components. Such hardware components may comprise a general-purpose processor, a Digital Signal Processor (DSP), a micro-controller, central processing unit (CPU), etc.

5G as the fifth generation of mobile radio communication promises performance that meets industrial requirements. The Ultra-Reliable Low Latency Communication (URLLC) feature supports time-critical communication. To achieve seamless integration of 5G into TSN, 3GPP (3^rd Generation Partnership Project) specified the 5G system as a virtual TSN bridge, cf. 3GPP: TS 23.501: System architecture for the 5G System (V17.3.0), 2021. Fig. 3 shows an embodiment of a 5G system as a virtual TSN bridge 300.

Fig. 3 shows a corresponding model in which the 5G system 500 is a black box and appears like a 5G-TSN bridge 300 in the TSN network. As shown in Fig. 3 the 5G system 500 comprises two UEs (user equipment 502 and 504), the radio access network (RAN, 506), a user plane function (UPF, 508) and a control plane 510 controlling the RAN 506 and the UPF 508.

At the system boundaries, i.e., ingress and egress ports, the Device-Side TSN Translator (DS- TT) 302 and 304, Network-Side TSN Translator (NW-TT) 306, and TSN Application Function (TSN AF) 308 translation functions are necessary. These provide integration of QoS frameworks, forwarding and topology information, with industrial network management, and with the synchronization framework [RCK20], The DS-TT 302 and 304 interface to the TSN end devices 1 and 3 (312 and 314 in Fig. 3), and the NW-TT 306 interfaces to a TSN bridge 316, which again couples to TSN end device 2 (324). The TSN AF 308 further interfaces to a TSN centralized network configuration (TSN CNC, 318), which interfaces with a TSN centralized user configuration (TSN CUC, 320) and the TSN bridge 316. Further details can be found in 3GPP TS 23.501.

The aspect of time synchronization is already part of the standardization since 3GPP Release 16 (cf. older versions of [3G21a]).

Research is currently focusing much more on time synchronization [SS21, Pa21], which forms the basis for several traffic shaping mechanisms. However, it is equally relevant to achieve a common understanding of priorities for different traffic types in both systems, especially when time-critical traffic of mobile safety applications requires preference.

Therefore, embodiments may focus on traffic prioritization, which is fundamentally different in both technologies and not explicitly standardized [3G21a], In the following, prioritization in TSN and 5G will be explained, embodiments may map the priorities of 5G QoS flows to TSN streams based on the respective parameters, and finally at least some embodiments may provide this mapping towards a joint QoS model. n the following, traffic prioritization in TSN will be explained before traffic prioritization will be detailed for 5G accordingly. After this, embodiments mapping the respective priorities to lay the foundation for a joint 5G-TSN QoS model will be detailed, distinguishing between the use of standardized and non-standardized 5G Quality Indicator (5QI) values.

The TSN mechanisms and parameters for the traffic prioritization as well as industrial protocols enabling real-time communication with TSN will be detailed in the following.

In accordance with IEEE 802.1Q - Strict Priority, the different traffic types in industrial communication are assigned to a total of eight traffic classes [I n19], as listed in Table 1 below. A traffic class is identified using the Priority Code Point (PCP) as part of the Virtual Local Area Network (VLAN) tag. Priorities range from 0 to 7, where 7 stands for the highest and 0 for the lowest priority. In some embodiments, the first and the second QoS profiles may comprise a priority level for the data flow. For example, the first and the second QoS profiles may comprise one or more requirements of the group of latency, packet error rate, frame length, periodicity, or data rate requirement for the data flow.

Prioritization based on traffic classes, together with network-wide time synchronization according to IEEE 802.1 AS, forms the basis for other TSN traffic shaping mechanisms. These include the time-aware shaper for exclusive gating (IEEE 802.1Qbv), credit-based shaping (802.1Qav), frame preemption (802.1Qbu), frame replication (802.1CB), ingress policing (802.1Qci), cut-through switching and reservation/scheduling [I E22], Although the time-aware shaper and frame preemption are able to override simple prioritization depending on their configuration, both mechanisms should be seen as additional optimization options beyond prioritization.

Tab. 1: Traffic types, classes and priorities [In19]

In automation, Industrial Ethernet protocols, such as PROFINET, play a significant role. For instance, in PROFINET, TSN can replace the two proprietary real-time extensions on Layer 2, PROFINET IRT (isochronous real-time, cf. traffic class 6) and PROFINET RT (real-time, cf. class 5) [SJ21],

OPC UA (Open Platform Communications United Architecture) is gradually finding its way into automation and can be used for controller-to-controller (C2C) and controller-to-device (C2D) communication. In pure C2C communication, classes 0-4 are covered. If C2D, i.e. field level communication, is also considered via OPC UA TSN, all traffic classes can be affected [Br19],

In the following, traffic prioritization in 5G will be discussed. First, the 5G QoS framework will be briefly explained, including the relevant parameters for traffic prioritization.

3GPP TS 23.501 specifies the 5G QoS model. The 5G system establishes a Protocol Data Unit (PDU) session between the User Plane Function (UPF) and the User Equipment (UE). A PDU session can contain one or more QoS flows including the respective QoS Flow ID (QFI). Each QoS flow in turn has a specific QoS profile with several QoS parameters [5G21 b], such as 5G QoS Identifiers (5QI), Resource Type, Priority Level, Packet Delay Budget (PDB), Packet Error Rate (PER), Maximum Data Burst Volume (MDBV) and Averaging window. The parameters are explained below and listed with concrete values in Table 2 below [3G21a], • Resource Type: This parameter indicates how the Packet Delay Budget, Packet Error Rate, and Maximum Data Burst Volume should be handled. The resource can be of type Guaranteed Bit Rate (GBR), Non-GBR, or Delay-Critical GBR. The required bit rates are permanently allocated.

• Priority Level: indicates a flow’s priority in relation to other flows for scheduling resources. Unlike TSN, the lowest priority level value corresponds to the highest priority.

• Packet Delay Budget (PDB): sets an upper time limit for the delay between the UE and the UPF, before the packet is counted as lost. Packet fragmentation can affect the PDB and limit the packet size.

• Packet Error Rate (PER): defines the level of reliability by providing an upper bound on the number of incorrectly received and lost packets divided by the total number of received packets. The larger the packet and the lower the PDB, the higher the PER.

• Maximum Data Burst Volume (MDBV): indicates the amount of data that can be sent without exceeding the PDB.

• Averaging Window: This parameter deals with GBR resources and indicates the calculation time of Guaranteed Flow Bit Rate (GFBR) and Maximum Flow Bit Rate (MFBR) for a given traffic flow. While GFBR can be expected for a QoS flow over the averaging window, MFBR defines the maximum value of an actual bitrate.

• Allocation and retention priority (ARP): indicates a QoS flow’s relative priority and can have a value between one (highest priority) and 15 in combination with 5QI. Based on ARP, the 5G system decides how a QoS flow should be served or preempted when resources are limited [5G21 b].

The standardized 5QI were specified for public networks. Since TSN is expected to be used in combination with non-public networks, the operator can freely define the 5QI values.

Tab. 2: 5QI from 3GPP TS 23.501 5.7.4-1 [3G21a]

In the following, embodiments enabling the general translation process for the TSN translator functions within the 5G-TSN bridge will be described and systematically explicit mapping solutions for standardized and non-standardized 5G QoS parameters will be derived and discussed.

A 5G system 500 can receive QoS information for the TSN traffic from the centralized network configuration (TSN-CNC) via TSN AF 308, cf. Fig. 3. The QoS mapping table preconfigured by the TSN AF 308 is used to identify a suitable 5G QoS profile. Based on the information received, the 5G system 500 selects an appropriate QoS profile for each TSN stream in order to establish a corresponding 5G QoS flow for delivering TSN traffic between the ingress and egress ports of the 5G bridge. In addition, it is possible to use packet filters on the UE 502, 504 and UPF side, 508, which can be used to map different TSN streams to corresponding 5G QoS flows [5G21b].

Different TSN traffic classes need to be prioritized differently within the 5G system. IEEE 802.1Q - Strict Priority takes precedence as IEEE 802.1Qbv can open multiple gates simultaneously and then prioritize again according to the PCP. The 3GPP specifications mention QoS mapping tables without making any specific statement about their content [3G21a, 3G21b], Even 5G-ACIA (Alliance for Connected Industries and Automation), which focuses on industrial automation, does not derive any 3GPP QoS mapping table for TSN in detail [5G21a],

A meaningful mapping requires a common understanding of the parameters from the TSN and 5G domain, which can be translated as follows:

* TSN frame size = GFBR

* TSN frame size = MDBV

* periodicity = averaging window [Ma21],

Three of the eight TSN traffic classes are real-time streams (4-6). These correspond to the 5G delay-critical GBR category [Ma21], Automation is given as an exemplary service for 5QI values 82 and 83, but both have a packet delay budget of 10ms, which may exceed the time requirements of isochronous applications. Ethernet frames can reach a length of up to 1522 Bytes including the VLAN tag (virtual LAN, local area network), which exceeds the MDBV of 1354 Bytes maximum. However, the TSN Industrial Automation Profile limits the real-time streams to a maximum of 1000 Bytes.

In both TSN and 5G, Network Control requires guaranteed bandwidth with the highest priority. On the other hand, Network Control, Configuration & Diagnostics, and Best Effort are not time- critical. Best Effort can even be assigned to a 5QI from the non-GBR category.

Since different deployment scenarios for non-public 5G networks are possible [5G19], two solutions are discussed in the following subsections: public network integrated non-public networks (PNI-NPNs) are expected to rely on using exclusively or primarily standardized 5QI values in coordination with the mobile network operator (MNO), while the operator of a standalone non-public network (SNPN) is free to define the 5G QoS parameters. Assuming that only standardized 5QI values are used, Table 3 maps the respective priorities to each other. Due to the 5G time-division duplex (TDD) pattern, uplink traffic usually has less capacity and is more complex to schedule than downlink traffic. Consequently, isochronous uplink streams should be prioritized higher than the corresponding downlink streams, to ensure bidirectional reliability. The alternative values in parentheses from Table 3 can be used for this purpose.

Another reason for setting 5QI fallback values is to allow the service to adapt to current performance and conditions, as wireless networks are inherently less reliable than wired ones. Moreover, a fallback solution makes sense since QoS-adaptive applications support the flexibility in modern factories [5G21 b]. In some embodiments, the first QoS profile comprises a TSN Traffic class and priority, and the second QoS profile comprises a 5G quality indicator, 5QI, and a 5G priority level. The fitting of the first QoS profile to QoS profiles of the second network comprises one or more mappings as shown in Table 3.

.

Tab. 3: 5G-TSN QoS mapping based on standardized 5QI

As mentioned earlier, the priority values in TSN are opposite to 5G and the overall priority understanding. Thus, the values in Table 3 can be derived as follows:

1. Real-time TSN streams with strict latency requirements (i.e. traffic classes 4, 5 and 6) need to be mapped to a 5QI with Delay-critical GBR (> 82).

2. Bandwidth-demanding TSN traffic classes correspond to GBR 5QI.

3. The TSN frame length needs to match the MDBV [Ma21],

4. The TSN periodicity needs to match the averaging window [Ma21], Since only default values are specified (2000ms), these can be adjusted accordingly. 5. At the same time, the order of the 5G Priority Level must be observed in accordance with the TSN priority.

Hence, the mapping for standardized 5QI values is performed starting from the 5G domain. The user must inevitably accept performance compromises here:

• There are inconsistencies in several PDB values (e.g. 5ms for isochronous traffic although 2ms are required and 300ms for audio/video against 40ms).

* The PER of network control traffic is relatively high (10-2).

• It is not clear whether a lower limit exists for the averaging window.

* It is questionable whether in a PNI-NPN the end user is allowed to utilize all 5Qls for non-public traffic or whether this is already firmly reserved for other traffic types by the MNO. Only exemplary services are specified in the 3GPP table.

A compromise would be to use only 5QI values 82 or 83, which are dedicated to industrial automation, and implement relative prioritization based on ARP. Consequently, all TSN traffic within the 5G system would have the same 5QI value, but with relative prioritization via ARP values 1 (for Network Control) to 8 (Best Effort). Further research may further assess whether this simplified approach is already sufficient. In these embodiments the determining 14 of the second QoS profile comprises fitting the first QoS profile to a predefined or standardized QoS profile of the second network. For example, the second network is a public network integrated non-public network.

In contrast to the restrictions in a public 5G network, the operator of an SNPN can flexibly set priorities for its own purposes. In factories, the most likely scenario is an overarching 5G network for the entire plant site and several separate TSN networks per production cell, group of production cells, or maximum hall. However, this requires a more differentiated prioritization in the 5G network than just eight traffic classes or priority levels or ARPs, since it does not exclusively serve TSN data traffic. Furthermore, depending on the scalability or dimensioning of the network, there must be an upper limit at which the capacity of the 5G network is no longer able to handle the over-demanding QoS parameters. This may reveal another point for research, as there does not seem to be any work on this to date in real-world networks.

Table 4 below lists the customized 5G QoS parameters based on the traffic parameters in IEC/IEEE 60802 (as shown in Table 1). The derivation corresponds methodically to that in the above section, but starts from the TSN perspective. All values are self-defined based on the characteristics of the TSN traffic types and are not covered by standardized 5Qls. Hence, in some embodiments the determining 14 of the second QoS profile may comprise fitting the first QoS profile to a QoS profile of the second network by configuring an according QoS profile in the second network. The second network may be a standalone non-public network.

For instance, 5G promises a latency of 1ms in the long term, so a PDB of 2ms for isochronous traffic seems realistic. The PER is based on the assumption of a long-term reliability for URLLC traffic of 99.99999 %. The following values differ from the standardized ones: Isochronous traffic cannot be covered by the existing standardized 5Qls. The low values for the Averaging Window parameter are questionable for classes 7, 5 and 4, and the MDBV value for classes 3-0. These are specified in 3GPP by default as 2000ms and "not applicable" respectively. In some embodiments, the first QoS profile may comprise a TSN priority, and wherein the second QoS profile comprises a 5G quality indicator, 5QI, and a priority level, and wherein the fitting of the first QoS profile to QoS profiles of the second network, comprises one or more mappings of the table of

Tab. 4: 5G-TSN QoS mapping based on non-standardized 5QI

In contrast to the previous section, the 5G QoS parameters are mapped to the TSN parameters. Since one of the goals of TSN is to guarantee sufficient bandwidth to all traffic types, it seems reasonable to define Best Effort as GBR as well. The prerequisite for the mapping presented here is appropriate dimensioning and design of the 5G campus network in order to be able to provide the required performance. Validation of the QoS mapping concept has generally been performed as a simulation in OMNET++, but only with two different traffic classes [MP21, Sa22], The present description is focused on the systematic derivation of holistically matching QoS parameters, so that priorities and thus real-time capability are maintained at the system boundaries. The results of this description are transferable and applicable to their simplified QoS mapping table, which is why no further simulation is performed here.

Based on the analyses of traffic prioritization in TSN and 5G, embodiments may provide the mapping of priorities in TSN and 5G with standardized and non-standardized 5G QoS parameters and discussed the results.

While this description focusses on the aspect of traffic prioritization, the QoS mechanisms in TSN and 5G may be much more multi-layered. A solution for a joint QoS model might not be trivial and might need to be further investigated in a holistic approach, including time synchronization, prioritization, scheduling and other QoS mechanisms.

Examples or embodiments may further be or relate to a (computer) program including a program code to execute one or more of the above methods when the program is executed on a computer, processor or other programmable hardware component. Thus, steps, operations or processes of different ones of the methods described above may also be executed by programmed computers, processors or other programmable hardware components. Embodiments may also cover program storage devices, such as digital data storage media, which are machine-, processor- or computer-readable and encode and/or contain machineexecutable, processor-executable or computer-executable programs and instructions. Program storage devices may include or be digital storage devices, magnetic storage media such as magnetic disks and magnetic tapes, hard disk drives, or optically readable digital data storage media, for example. Other embodiments may also include computers, processors, control units, (field) programmable logic arrays ((F)PLAs), (field) programmable gate arrays ((F)PGAs), graphics processor units (GPU), application-specific integrated circuits (ASICs), integrated circuits (ICs) or system-on-a-chip (SoCs) systems programmed to execute the steps of the methods described above.

It is further understood that the disclosure of several steps, processes, operations or functions disclosed in the description or claims shall not be construed to imply that these operations are necessarily dependent on the order described, unless explicitly stated in the individual case or necessary for technical reasons. Therefore, the previous description does not limit the execution of several steps or functions to a certain order. Furthermore, in further embodiments, a single step, function, process or operation may include and/or be broken up into several sub-steps, - functions, -processes or -operations.

If some aspects have been described in relation to a device or system, these aspects should also be understood as a description of the corresponding method. For example, a block, device or functional aspect of the device or system may correspond to a feature, such as a method step, of the corresponding method. Accordingly, aspects described in relation to a method shall also be understood as a description of a corresponding block, a corresponding element, a property or a functional feature of a corresponding device or a corresponding system.

If some aspects have been described in relation to a device or system, these aspects should also be understood as a description of the corresponding method and vice versa. For example, a block, device or functional aspect of the device or system may correspond to a feature, such as a method step, of the corresponding method. Accordingly, aspects described in relation to a method shall also be understood as a description of a corresponding block, a corresponding element, a property or a functional feature of a corresponding device or a corresponding system.

The following claims are hereby incorporated in the detailed description, wherein each claim may stand on its own as a separate example/embodiment. It should also be noted that although in the claims a dependent claim refers to a particular combination with one or more other claims, other embodiments may also include a combination of the dependent claim with the subject matter of any other dependent or independent claim. Such combinations are hereby explicitly proposed, unless it is stated in the individual case that a particular combination is not intended. Furthermore, features of a claim should also be included for any other independent claim, even if that claim is not directly defined as dependent on that other independent claim.

The aspects and features described in relation to a particular one of the previous embodiments may also be combined with one or more of the further embodiments to replace an identical or similar feature of that further embodiment or to additionally introduce the features into the further embodiment. List of reference numerals method for assigning quality of service, QoS, flows between a first network and a second network receiving a first QoS profile for a data flow from the first network determining a second QoS profile for the data flow in the second network based on fitting the first QoS profile to QoS profiles of the second network assigning the QoS flows for the data flow in the first and second network to each other based on the first and second QoS profiles apparatus for assigning quality of service, QoS, flows between a first network and a second network one or more interfaces processing circuitry bridge

5G-TSN bridge

Device-Side TSN Translator (DS-TT)

Network-Side TSN Translator (NW-TT)

TSN Application Function (TSN AF)

TSN end device 1

TSN end device 3

TSN bridge

TSN centralized network configuration (TSN CNC)

TSN centralized user configuration (TSN CUC)

TSN end device 2

Claims

Claims .A method (10) for assigning quality of service, QoS, flows between a first network and a second network, wherein the first and second networks form a convergent network, the method (10) comprising receiving (12) a first QoS profile for a data flow from the first network; determining (14) a second QoS profile for the data flow in the second network based on fitting the first QoS profile to QoS profiles of the second network; and assigning (14) the QoS flows for the data flow in the first and second network to each other based on the first and second QoS profiles. . The method (10) of claim 1 , wherein the first network is a wired Time Sensitive Network, TSN, according to IEEE, Institute of Electrical and Electronics Engineers, 802.1 standards. . The method (10) of one of the claims 1 or 2, wherein the second network is a wireless 5^th Generation, 5G, system as specified by the 3^rd Generation Partnership Project. . The method (10) of one of the claims 1 to 3, wherein the determining (14) of the second QoS profile comprises fitting the first QoS profile to a predefined or standardized QoS profile of the second network. . The method (10) of claim 4, wherein the second network is a public network integrated non-public network. . The method (10) of one of the claims 1 to 3, wherein the determining (14) of the second QoS profile comprises fitting the first QoS profile to a QoS profile of the second network by configuring an according QoS profile in the second network. . The method (10) of claim 6, wherein the second network is a standalone non-public network.

8. The method (10) of one of the claims 1 to 7, wherein the first and the second QoS profiles comprise a priority level for the data flow.

9. The method (10) of one of the claims 1 to 8, wherein the first and the second QoS profiles comprise one or more requirements of the group of latency, packet error rate, frame length, periodicity, or data rate for the data flow.

10. The method (10) of claims 1 , 2 and 3, wherein the first QoS profile comprises a TSN Traffic class and priority, and wherein the second QoS profile comprises a 5G quality indicator, 5QI, and a 5G priority level, and wherein the fitting of the first QoS profile to QoS profiles of the second network comprises one or more mappings of the table of

, wherein the values given in parenthesis indicate a fallback option for isochronous uplink time division duplex traffic.

11. The method (10) of claims 1 , 2 and 3, wherein the first QoS profile comprises a TSN priority, and wherein the second QoS profile comprises a 5G quality indicator, 5QI, and a priority level, and wherein the fitting of the first QoS profile to QoS profiles of the second network, comprises one or more mappings of the table of

, wherein

GBR is Guaranteed Bit Rate,

DC-GBR is Delay-Critical GBR,

PDB is Packet Delay Budget,

PER is Packet Error Rate, and

MDBV is Maximum Data Burst Volume, as defined by 3GPP.

12. A computer program having a program code for performing a method (10) according to any one of claims 1 to 11 , when the computer program is executed on a computer, a processor, or a programmable hardware component.

13. An apparatus (20), comprising: one or more interfaces (22) configured to communicate with one or more components of a network; and processing circuitry (24) configured to control the one or more interfaces (22) and to perform a method (10) according to any of claims 1 to 11.

14. A bridge (200) between a first network and a second network comprising the apparatus (20) of claim 13.

15. A 5G-TSN bridge (300) comprising the bridge (200) of claim 14.