Edge Computing Offloading for Extended Reality Latency
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Resource-constrained mobile devices struggle to efficiently run complex extended reality (XR) applications due to limited processing, memory, and battery resources, leading to degraded user experiences.
Innovation Solution
An edge computing system that offloads computationally intensive tasks from user devices to edge devices or cloud servers, utilizing a computing mesh, application mesh, or connectivity mesh to balance resource capacity and latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Power
If computationally intensive tasks are processed locally on mobile devices, then processing capability is improved, but device resources (battery, memory, processing power) are overwhelmed
Solution Approach 1:
The patent extracts computationally intensive tasks from the mobile device and relocates them to edge computing systems. The mobile device offloads image processing, object recognition, and other resource-intensive operations to external edge servers, thereby preserving local device resources while maintaining high processing capability for critical functions.
Solution Approach 2:
The patent introduces an edge computing system as an intermediary between the mobile device and the cloud. This intermediary layer provides sufficient processing power and memory resources to handle computationally intensive tasks without requiring the mobile device to have extensive local resources or to communicate directly with remote cloud servers.
2Power
If tasks are offloaded to remote cloud servers, then processing power is improved, but end-to-end latency increases
Solution Approach 1:
The edge computing system serves as a geographically proximal intermediary between mobile devices and remote cloud servers. It provides sufficient processing power to handle computationally intensive tasks while being located close enough to devices to minimize transmission latency, thus resolving the contradiction between processing power and response time.
3Productivity
If more processing resources are allocated to mobile devices, then application performance is improved, but device complexity and cost increase
Solution Approach 1:
The patent extracts complex processing functions from the mobile device architecture and relocates them to edge computing systems. This allows the mobile device to maintain simple, cost-effective hardware while achieving high application performance through cloud-based processing resources.
4Productivity
If extended reality applications are run on mobile devices, then user experience is enhanced, but device battery life is reduced
Solution Approach 1:
The patent extracts battery-intensive computational tasks from the mobile device and transfers them to edge computing systems. The device maintains full extended reality application functionality by offloading image processing, object recognition, and other resource-intensive operations to external processors, thereby preserving battery life while enhancing user experience.
Data Source
AI summary
A method and edge computing system configured to generate or process extended reality (XR) data. Processors in the edge computing system receive, process, and analyze a sensory feed from an optical device to generate analysis results that include a relative position of the optical device from surrounding objects. The processors generate mapper output results (that include virtual coordinates) based on the analysis results, request and receive information (e.g., salient points of interest, etc.), and compare the generated mapper output results to the received information to identify a correlation between a feature included in the processed sensory feed and a feature included in the received information. The processors generate and send augmented information to a renderer and/or send the processed sensory feed to a cloud object recognizer for further processing.