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A Novel Traffic Scheduling Algorithm for Multi-CQF Using Mixed Integer Programming and Variable Neighborhood Search

Cheng Wang1, Zhiquan Lin1, Yuhao Zhao2

  • 1School of Computer Science and Artificial Intelligence, Changzhou University, Changzhou 213159, China.

Sensors (Basel, Switzerland)
|July 12, 2025
PubMed
Summary
This summary is machine-generated.

Time-Sensitive Networking (TSN) scheduling is improved using queuing theory and optimization algorithms. Mixed Integer Programming (MIP) and Variable Neighborhood Search Genetic Algorithm (VNS-GA) reduce transmission delays in TSN networks.

Keywords:
Multi-CQFgenetic algorithmmixed integer programmingqueueing theorytime-sensitive networkvariable neighborhood search

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Area of Science:

  • Computer Networking
  • Real-Time Systems
  • Network Optimization

Background:

  • Time-Sensitive Networking (TSN) enhances Ethernet for deterministic communication.
  • Cycling Queuing and Forwarding (CQF) and its extension Multi-CQF manage traffic scheduling.
  • Existing Multi-CQF algorithms lack flow sorting, causing delays in dynamic networks.

Purpose of the Study:

  • To enhance Multi-CQF performance by optimizing traffic scheduling.
  • To reduce transmission delays and improve network efficiency in TSN.

Main Methods:

  • Queuing theory for traffic analysis and foundational solutions.
  • Mixed Integer Programming (MIP) for optimal scheduling in small-traffic networks.
  • Variable Neighborhood Search Genetic Algorithm (VNS-GA) for large-traffic network optimization.

Main Results:

  • MIP achieved an average delay reduction of approximately 13% in small-traffic TSN networks.
  • VNS-GA achieved an average delay reduction of 7% in large-traffic TSN networks.
  • Both methods demonstrated superior performance compared to existing schemes.

Conclusions:

  • Optimized scheduling significantly reduces transmission delays in TSN networks.
  • MIP and VNS-GA offer effective solutions for different scales of TSN traffic.
  • The proposed methods enhance the efficiency and determinism of TSN communication.