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Research on a Hybrid Scheduling Algorithm Based on Critical-Link Optimization for Large-Scale Time-Triggered Ethernet
Haowen Zhu1,2, Zhen Li2, Jinwei Cheng2
1School of Aeronautics and Astronautics, Zhejiang University, Hangzhou 310058, China.
Sensors (Basel, Switzerland)
|October 29, 2025
Summary
This study introduces a hybrid scheduling algorithm for Time-Triggered Ethernet (TTE) in the Industrial Internet of Things (IIoT). The novel approach optimizes critical network links and uses genetic algorithms to improve message scheduling, reducing computation time and enhancing performance.
Area of Science:
- Computer Science
- Electrical Engineering
- Network Engineering
Background:
- The Industrial Internet of Things (IIoT) increasingly utilizes Time-Triggered Ethernet (TTE) technology.
- Traditional scheduling algorithms face challenges with computation time and scheduling quality in large-scale TTE applications.
Purpose of the Study:
- To propose a hybrid scheduling algorithm for large-scale TTE applications in the IIoT.
- To address issues of increasing computation time and deteriorating scheduling quality in existing algorithms.
Main Methods:
- Developed a large-scale TTE message scheduling model with abstracted TT scheduling constraints.
- Implemented a time slot balancing algorithm for critical network links, optimizing TT message intervals.
- Utilized an improved genetic algorithm, incorporating critical link results for enhanced global optimization.
Main Results:
- The proposed algorithm significantly reduces computation time and increases message scheduling success rates.
- Achieved better Time-Triggered (TT) message interval balancing compared to traditional methods.
- Effectively reduced transmission delay and jitter for Best-Effort (BE) messages under increased load.
Conclusions:
- The hybrid scheduling algorithm meets the demanding requirements of large-scale TTE applications in the IIoT.
- Offers improved efficiency and performance for TTE message scheduling, particularly in complex industrial environments.
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