High-speed train with passengers streaming videos.

Fast Track Internet: Optimizing Video Streaming on High-Speed Trains

Reese Marlowe in Tech & Innovation June 2025 • 3 min read.

"Discover how innovative tech is making your next train binge-watch smoother than ever."

High-speed rail (HSR) has transformed travel. As more people opt for trains, the demand for onboard entertainment, especially video streaming, is skyrocketing. However, providing stable, high-quality internet on a speeding train presents unique technical challenges.

Imagine trying to binge-watch your favorite show, only for the video to constantly buffer or drop out. This is a common frustration for many train travelers due to the high variability and unpredictability of wireless communications in HSR environments. Researchers are working hard to solve this problem and ensure your entertainment isn't derailed.

One team of researchers has taken a comprehensive approach to this challenge, focusing on improving video streaming using a technique called Dynamic Adaptive Streaming over HTTP (DASH). Their work involves analyzing the specific conditions of HSR networks and developing a system that adapts to these challenges in real-time.

The Challenge of High-Speed Internet

High-speed train with passengers streaming videos.

The primary issue is packet loss. During field experiments on real HSR lines, researchers found that packet loss rates can be incredibly high, averaging around 75.9%. This means that a huge portion of the data sent never arrives, leading to interruptions and poor video quality. The fluctuation of packet loss is also significant, making it hard to predict and compensate for.

To combat these issues, the team developed a system model that considers several factors: packet loss, energy consumption, video service quality, and overall service delivery. They then used a method called Lyapunov optimization to transform the problem into one of queue stability. This approach allows for a scalable and general solution that can adapt to changing network conditions.

Here are some key challenges addressed by the researchers:

High Packet Loss: HSR networks experience significant data loss, disrupting streaming quality.
Unpredictability: The rate of packet loss varies, making it difficult to optimize video streaming in real-time.
Scalability: Solutions need to handle a growing number of users without sacrificing performance.

The researchers broke down the complex problem into smaller, manageable subproblems. They then created a Joint Stochastic DASH Optimization (JSDO) mechanism, which includes algorithms designed to address each subproblem. This system dynamically adjusts video quality based on real-time network conditions, aiming to provide the best possible viewing experience.

The Future of On-the-Go Entertainment

This research offers a promising step toward improving the video streaming experience on high-speed trains. By addressing the unique challenges of HSR networks and using adaptive optimization techniques, it paves the way for smoother, more enjoyable journeys. So, next time you’re on a train, you can thank these researchers for helping ensure your binge-watching session stays on track.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1109/tmm.2018.2881095, Alternate LINK

Title: Stochastic Analysis Of Dash-Based Video Service In High-Speed Railway Networks

Subject: Electrical and Electronic Engineering

Journal: IEEE Transactions on Multimedia

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Authors: Zhongbai Jiang, Changqiao Xu, Jianfeng Guan, Yang Liu, Gabriel-Miro Muntean

Published: 2019-06-01

Everything You Need To Know

What is the biggest hurdle to overcome when streaming videos on high-speed trains?

The primary challenge for video streaming on high-speed trains is high packet loss. During field experiments, packet loss rates averaged around 75.9%, meaning a significant portion of data doesn't arrive, causing interruptions and poor video quality. The unpredictable fluctuation of packet loss further complicates the problem, making it difficult to compensate for in real-time. Addressing this is crucial for a seamless viewing experience.

How are researchers using Dynamic Adaptive Streaming over HTTP (DASH) to improve video quality on trains?

Researchers are using Dynamic Adaptive Streaming over HTTP (DASH) to improve video streaming on high-speed trains. They've developed a system model that considers packet loss, energy consumption, video service quality, and overall service delivery. By using Lyapunov optimization, they transform the problem into one of queue stability, enabling a scalable solution that adapts to changing network conditions. This approach dynamically adjusts video quality based on real-time network conditions.

How does Joint Stochastic DASH Optimization (JSDO) help in optimizing video streaming on high-speed trains?

Joint Stochastic DASH Optimization (JSDO) addresses the challenges of video streaming on high-speed trains by breaking down the complex problem into manageable subproblems. It includes algorithms designed to address each subproblem, dynamically adjusting video quality based on real-time network conditions. This optimization aims to deliver the best possible viewing experience by addressing issues like high and variable packet loss, while also considering factors like energy consumption and service quality.

What role does Lyapunov optimization play in stabilizing video streams on high-speed trains?

Lyapunov optimization transforms the problem of video streaming on high-speed trains into one of queue stability. This approach allows for a scalable and general solution that can adapt to changing network conditions, making it a vital component in addressing the challenges of high packet loss and unpredictable network behavior. It optimizes the streaming process by maintaining stable queues for data transmission, ensuring a smoother video playback experience.

Beyond trains, what are the broader implications of improving video streaming technology in high-speed rail environments?

The work on Dynamic Adaptive Streaming over HTTP (DASH) and Joint Stochastic DASH Optimization (JSDO) has broad implications for on-the-go entertainment. By addressing the unique challenges of High-Speed Rail (HSR) networks, these advancements pave the way for smoother and more enjoyable video streaming experiences. This research is a promising step toward improving the overall quality of onboard entertainment, potentially extending to other mobile environments facing similar network constraints.