Resolving User-Experience Issues for VR/XR Content by Customizing Congestion Control Logic to the VR/XR Service and to the Network

Project Status:

(roll over for info)

Working

The project is actively being worked on.

Start:

March 1, 2023

Estimated Completion:

March 31, 2024
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Problem Statement

The goal of this POC is to gain an understanding of the last mile behavior for AR/VR content delivery and identify potential bottlenecks in the video pipeline between the edge cache and the user device. We can then use the understanding gained to define the right congestion control and/or customize its parameter to maximize the VR QoE for the underlined network.

Project Description

Virtual Reality (VR), and other forms of Extended Reality (XR), are beginning to drive deep immersive experiences for premium entertainment and sports content. However, network capacity along the delivery path may not be equally shared across users and each application may have a different tolerance for network congestion and packet loss. This POC will test delivery of AR/VR data across a network including last mile and measure network performance using both network and client-side analytics. Additional phases of this POC will introduce additional congestion control algorithm to examine network behavior including adding congestion along the delivery path. This POC will also assess the ability of customization of the congestion control used, to tackle different congestion and network related challenges.

Project Type

Proof of Concept

Project Leads

Advisors

Goals and Objectives

The deliverables would be comprised of a set of empirical test data, an analysis of that data and a set of best practices and recommendations for Content Owners and Network Operators that are considering enhanced and best end-user experiences for VR (and XR family) of services.

Project Scope

  • Enable delivery teams with enhanced visibility into their service behavior without client-side integration.
  • Provide network-relating insight in the case of existing client-side telemetric.
  • Gain deep understanding of the last mile behavior, enabling unique troubleshooting capabilities.
  • Actively use the data gained to improve the VR Quality of Experience.

Contributors

The following members have contributed to this project. Click on their name to visit their profile. If they have not published their profile, the link will redirect to their LinkedIn profile.

Additional References

There are no additional references or other required readings need to participate in this project.

Presentations

The following presentations delivered during Immersive Video working group sessions may provide additional information about this project.