# A Dynamic QoS Mapping Algorithm for 5G-TSN Converged Networks Based on Weighted Fuzzy C-Means and Three-Way Decision Theory

## TL;DR

This paper introduces a new algorithm for managing quality of service in 5G-TSN networks using fuzzy clustering and decision theory to improve performance and balance loads.

## Contribution

A novel dynamic QoS mapping method combining Weighted Fuzzy C-Means and Three-Way Decisions for 5G-TSN networks.

## Key findings

- WFCM-TDwQM ensures end-to-end QoS consistency in 5G-TSN networks.
- The method achieves better load balancing under varying network conditions.
- It outperforms three other mapping algorithms in experimental evaluations.

## Abstract

To ensure end-to-end Quality of Service (QoS) management in 5G-TSN converged networks, this paper proposes a dynamic weighted QoS mapping method based on Weighted Fuzzy C-Means and Three-Way Decisions (WFCM-TDwQM). The WFCM algorithm is employed to cluster Time-Sensitive Networking (TSN) flows based on their QoS attributes, reducing computational complexity. A three-way decision-based method is used to assign a reasonable and approximate set of 5G QoS Identifier (5QI) values to each cluster. Finally, dynamic weights are adjusted by considering QoS similarity and the residual load rate, enabling the system to adapt to network load changes. The experimental results show that, compared with three other mapping algorithm combinations, WFCM-TDwQM not only ensures end-to-end QoS consistency but also achieves better load balancing under varying network loads. Moreover, its mapping performance is evaluated under different network scenarios.