Dynamic Rendering Distribution for XR Latency and Power
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Solution Overview
Problem
Modern computing devices face challenges in efficiently managing computational loads and power consumption during extended reality (XR), augmented reality (AR), and virtual reality (VR) applications, particularly due to high power usage and latency issues when rendering graphical content.
Innovation Solution
The proposed solution involves distributing the rendering architecture between a client device and a server based on communication network conditions, quality of service (QoS) levels, computational capacity, and thermal thresholds, allowing for dynamic adjustment of computational workload to reduce power consumption and maintain high rendering quality and low latency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If computational tasks are performed locally on the client device, then rendering quality can be maintained, but power consumption increases and thermal thresholds may be exceeded
Solution Approach 1:
The rendering system is segmented into multiple components distributed across client and server devices. The client device performs local rendering for immediate visual feedback, while the server device handles computationally intensive tasks. This segmentation allows the system to maintain rendering quality through local processing while offloading power-consuming tasks to the server, thereby resolving the contradiction between maintaining rendering quality and reducing power consumption.
2Use of energy by moving object
If computational tasks are offloaded to a server, then power consumption is reduced, but communication latency increases
Solution Approach 1:
The system performs preliminary actions by pre-processing and preparing rendering data on the server before it is needed by the client. The server anticipates rendering requirements and prepares computational results in advance, so that when the client requests rendered content, the data is already available or nearly ready. This preliminary action on the server reduces the actual communication latency experienced by the client, allowing power consumption to be reduced through server offloading without significantly increasing perceived latency.
3Loss of time
If more computational tasks are performed locally, then latency is reduced, but thermal thresholds may be exceeded
Solution Approach 1:
The system dynamically adjusts the distribution of computational tasks between client and server based on real-time conditions. When the client device's thermal threshold is approached, the system dynamically shifts more tasks to the server. When thermal conditions are favorable and low latency is critical, the system dynamically increases local processing. This dynamic adjustment allows the system to manage thermal thresholds while minimizing latency impacts through adaptive task distribution.
Data Source
AI summary
The present disclosure relates to methods and apparatus for computer processing. Aspects of the present disclosure can determine at least one of a quality, latency, or capacity of a communication link for communication between a client device and a server. Aspects of the present disclosure can also determine a computational load for an application computation between the client device and the server. Moreover, aspects of the present disclosure can adjust a computational distribution for the application computation between the client device and the server based on at least one of the computational load for the application computation or the at least one of the quality, latency, or capacity of the communication link. Aspects of the present disclosure can also determine a computational capacity of at least one of the client device or the server.