XR Experience Adaptation and Handover Between Edge Nodes During Movement
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Solution Overview
Problem
Current wireless mobile networks are inadequate for providing sufficient bandwidth, processing, and low latency required for extended reality (XR) applications, leading to challenges in adapting XR content to environmental conditions and user movements, particularly in server-side rendering and client-side adaptation.
Innovation Solution
A system and method for adapting XR content to environmental conditions and user movements by utilizing edge nodes for seamless handover, incorporating environmental detection, content adaptation, and dynamic responsiveness, ensuring optimal system performance and user experience through edge processing and communication between edge nodes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If server-side rendering is used for XR experiences, then processing capability is improved, but adaptation to environmental conditions requires complex server-side processing
Solution Approach 1:
The patent segments the XR rendering process into server-side rendering (for high-quality image generation) and client-side environmental detection (for capturing real-world conditions). This division allows the server to focus on rendering while the client handles environmental sensing, reducing server-side processing complexity for adaptation.
Solution Approach 2:
The patent introduces an intermediary mechanism where environmental parameters detected by the client are transmitted to the server as adaptation instructions. This intermediary approach allows environmental adaptation without requiring the server to directly process complex environmental data, maintaining processing efficiency while achieving adaptation.
2Adaptability or versatility
If client-side adaptation is used for XR content, then responsiveness to environmental conditions is improved, but users in motion experience problems
Solution Approach 1:
The patent implements preliminary action by pre-establishing a connection between the client's environmental sensors and the server before motion occurs. The system continuously monitors environmental conditions and prepares adaptation data in advance, ensuring that when the user moves, the server already has the necessary information to maintain seamless adaptation without interruption.
3Device complexity
If centralized rendering service is used, then resource management is simplified, but mobile operation with multiple clients becomes challenging
Solution Approach 1:
The patent applies universality by designing a centralized rendering service that simultaneously handles multiple client connections with individualized environmental adaptations. The server maintains a universal rendering pipeline while accepting client-specific environmental parameters, allowing it to serve multiple mobile users with different environmental conditions through a single unified system.
4Adaptability or versatility
If XR content is adapted to environmental conditions, then integration with physical environment is improved, but processing requirements increase
Solution Approach 1:
The patent applies local quality by having each client device independently detect and report its specific environmental conditions (lighting, geometry, weather) to the server. This allows the server to adapt the XR content locally for each user's environment without requiring universal complex processing for all possible conditions, reducing overall processing requirements while maintaining high environmental integration quality.
Data Source
AI summary
Methods and systems are described for extended and mixed reality experience adaptation, processing, and handover from one computing or processing entity to another. In response to a change in a condition impacting resource usage, delivery of content is transferred from one edge node to another. One or more changes in a viewing client, a first edge node, a second edge node, a communication network, and content signal a handover. Artificial intelligence systems, including neural networks, and models are trained and developed for improving the adaptation, processing, and handover. Related apparatuses, devices, techniques, and articles are also described.