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Related Concept Videos

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Related Experiment Video

Updated: Sep 22, 2025

Integration of 5G Experimentation Infrastructures into a Multi-Site NFV Ecosystem
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Multiservice-Based Traffic Scheduling for 5G Access Traffic Steering, Switching and Splitting.

Xinran Ba1, Libiao Jin2, Zengrui Li2

  • 1State Key Laboratory of Media Convergence and Communication, School of Information and Communication Engineering, Communication University of China, Beijing 100024, China.

Sensors (Basel, Switzerland)
|May 20, 2022
PubMed
Summary

A new multiservice-type based transmission (MSTT) strategy optimizes network path selection for multipath transport, enhancing user satisfaction and effective network capacity. This approach improves access traffic steering, switching, and splitting (ATSSS) performance.

Keywords:
ATSSSeffective network capacitymultipath transportmultiservice

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Area of Science:

  • Telecommunications Engineering
  • Network Optimization
  • Wireless Communication Systems

Background:

  • Multipath transport enables simultaneous use of multiple network paths for improved throughput and resilience.
  • Access traffic steering, switching, and splitting (ATSSS) relies on effective multipath transport.
  • Current traffic scheduling strategies may not fully optimize multipath performance.

Purpose of the Study:

  • To develop and validate a novel traffic scheduling optimization strategy for multipath transport.
  • To enhance user satisfaction and effective network capacity within ATSSS frameworks.
  • To address the need for optimal network path selection in multipath communication.

Main Methods:

  • Developed a multiservice-type based transmission (MSTT) traffic scheduling strategy.
  • UE selects data stream transmission paths based on service utility and network availability (3GPP and non-3GPP).
  • Applied convex optimization to maximize effective network capacity under Delay Quality of Service (DQoS) constraints.

Main Results:

  • The MSTT strategy demonstrated superior performance compared to existing algorithms.
  • Achieved higher user satisfaction and effective network capacity realization.
  • Validated through simulation experiments, confirming improved multipath transport efficiency.

Conclusions:

  • The proposed MSTT traffic scheduling strategy effectively optimizes multipath transport for ATSSS.
  • This method offers significant improvements in network performance and user experience.
  • The strategy provides a robust solution for dynamic network path management.