A Joint Scheduling Scheme for WiFi Access TSN.

Area of Science:

• Industrial Internet of Things (IIoT)
• Wireless Communication Networks
• Network Engineering

Background:

• Industry 4.0 necessitates intelligent industrial production through enhanced communication.
• Current networks require large-scale access, protocol interoperability, and low-latency transmission.
• Time-Sensitive Networking (TSN) and Wi-Fi are key technologies for industrial environments.

Purpose of the Study:

• To address the scheduling challenges in converged TSN and Wi-Fi networks.
• To develop an efficient algorithm for optimizing network performance in industrial settings.
• To improve the integration of wireless access within deterministic industrial communication systems.

Main Methods:

• Modeling the scheduling problem for TSN and Wi-Fi converged networks.
• Proposing a greedy strategy distributed estimation algorithm (GE).
• Comparing the GE algorithm against Integer Linear Programming (ILP) and Tabu algorithms.

Main Results:

• The GE algorithm demonstrates superior adaptability across diverse scenarios.
• Significant improvements in scheduling optimization efficiency were observed, particularly with large traffic volumes.
• The proposed algorithm outperforms ILP and Tabu algorithms in key performance metrics.

Conclusions:

• The GE algorithm provides an effective solution for scheduling in converged TSN and Wi-Fi industrial networks.
• This approach enhances the intelligence and efficiency of industrial production under Industry 4.0.
• The findings support the integration of Wi-Fi within TSN for future industrial internet applications.