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Related Experiment Video

Updated: May 10, 2025

Automated Deployment of an Internet Protocol Telephony Service on Unmanned Aerial Vehicles Using Network Functions Virtualization
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Study of In-Vehicle Ethernet Message Scheduling Based on the Adaptive Frame Segmentation Algorithm.

Jiaoyue Chen1, Yujing Wu1, Yihu Xu1

  • 1College of Engineering, Yanbian University, Yanji 133002, China.

Sensors (Basel, Switzerland)
|April 26, 2025
PubMed
Summary

A new Adaptive Frame Segmentation (AFS) algorithm boosts In-Vehicle Ethernet bandwidth utilization to 94.16% by optimizing Time-Sensitive Networking (TSN) scheduling. This enhances real-time performance for intelligent driving systems.

Keywords:
adaptive frame segmentationbandwidth utilizationin-vehicle ethernetmessage schedulingtime-sensitive networking

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Area of Science:

  • Automotive Engineering
  • Computer Networks
  • Real-time Systems

Background:

  • Traditional in-vehicle networks (LIN, CAN, FlexRay) lack the bandwidth and speed for intelligent driving.
  • In-Vehicle Ethernet is crucial for next-gen automotive communication due to high bandwidth and low latency.
  • Existing In-Vehicle Ethernet scheduling methods face limitations in bandwidth utilization.

Purpose of the Study:

  • To optimize Time-Sensitive Networking (TSN) scheduling for In-Vehicle Ethernet.
  • To enhance bandwidth utilization and reduce waste caused by guard bands and frame pre-emption.
  • To improve the real-time performance and responsiveness of in-vehicle communication networks.

Main Methods:

  • Development of an innovative Adaptive Frame Segmentation (AFS) algorithm based on the TSN protocol.
  • Flexible frame segmentation and efficient message scheduling to optimize In-Vehicle Ethernet performance.
  • Experimental evaluation of the AFS algorithm against existing scheduling methods.

Main Results:

  • The AFS algorithm achieved an average local bandwidth utilization of 94.16%.
  • AFS demonstrated significant improvements over Frame Pre-emption (4.35%), PAS (5.65%), and Improved Qbv (30.48%).
  • The algorithm proved stable and efficient under complex network traffic conditions.

Conclusions:

  • The AFS algorithm effectively reduces bandwidth waste and enhances In-Vehicle Ethernet's real-time capabilities.
  • This research provides crucial technical support for efficient communication in intelligent connected vehicles.
  • The study advances the development and application of In-Vehicle Ethernet technology for intelligent driving.