Cloud 3D Rendering Frame-Rate Synchronization with Priority Processing
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Solution Overview
Problem
Cloud-based 3D rendering systems face inefficiencies in resource allocation and latency, leading to suboptimal user experiences during peak demand periods, with high frame rates and motion-to-photon latency impacting interactive applications like VR.
Innovation Solution
A frame rate control system using double buffers in a proxy server to synchronize frame rendering, encoding, and transmission, prioritizing user-input-generated frames, and adjusting frame rates to meet quality of service targets while optimizing energy consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cloud-based 3D rendering systems operate at high frame rates during peak demand, then user experience quality is improved, but resource allocation efficiency deteriorates and energy consumption increases
Solution Approach 1:
The system dynamically changes the frame rate parameter based on demand conditions. During peak demand, it adjusts frame rates to match actual user needs rather than maintaining constant high frame rates, thereby improving resource allocation efficiency while preserving user experience quality through adaptive parameter adjustment.
Solution Approach 2:
The rendering system transitions from static fixed frame rate operation to dynamic adaptive frame rate control. The system continuously adjusts frame rates in response to changing demand conditions, enabling it to optimize the balance between user experience quality and resource allocation efficiency during peak demand periods.
2Speed
If cloud-based 3D rendering systems process all frames at high priority, then frame processing speed is improved, but latency for user-input-generated frames increases
Solution Approach 1:
The system applies different quality levels of processing to different frames based on their priority. User-input-generated frames receive high-priority processing with minimal delay, while other frames are processed at standard priority. This local differentiation in processing quality reduces motion-to-photon latency for critical frames without sacrificing overall frame processing speed.
Solution Approach 2:
The system introduces a priority classification mechanism that acts as an intermediary between frame generation and frame processing. This mediator categorizes frames into different priority levels, enabling the processing system to allocate resources dynamically and reduce latency for user-input-generated frames while maintaining efficient processing for other frames.
3Reliability
If cloud-based 3D rendering systems maintain constant high frame rates, then visual quality is improved, but energy consumption increases
Solution Approach 1:
The system dynamically adjusts the frame rate parameter based on actual user needs and demand conditions rather than maintaining constant high frame rates. This adaptive parameter change preserves visual quality by maintaining high frame rates only when necessary, thereby reducing energy consumption during periods when lower frame rates would suffice.
Solution Approach 2:
The system implements periodic assessment of frame rate requirements and adjusts frame rates accordingly. Instead of continuous high frame rate operation, the system periodically evaluates whether high frame rates are necessary and adjusts accordingly, reducing energy consumption while maintaining visual quality through periodic optimization.
Data Source
AI summary
Embodiments are directed to a computer-implemented method for regulating graphics frame rendering and encoding rates. The method including synchronizing a frame rate of rendering graphics frames by a 3D application executing in a cloud server with a frame rate of encoding rendered graphics frames at a proxy server; and synchronizing the frame rate of encoding the rendered graphics frames at the proxy server with a frame rate of transmitting the encoded graphics frames to a client device over a network.