Client-Side Predictive Rendering for Gaming Latency Reduction
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Solution Overview
Problem
In online gaming, rapid rotations and translations of the game field of view can lead to lag and poor performance due to the delay in receiving updated imagery from the server, as existing systems do not efficiently manage predictive scene imagery based on gameplay mechanics, player style, and network performance.
Innovation Solution
The system predicts and renders additional imagery around the current field of view, adjusting pixel density and resolution based on likelihood of use, and translates the field of view proactively, using client-side processing to optimize imagery generation and reduce latency by caching and interpolating between server updates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the game server periodically updates and communicates rendered imagery to game clients, then the game state information is kept synchronized across all clients, but rapid rotations and translations of the field of view result in lag and poor performance due to the delay in receiving updated imagery
Solution Approach 1:
The system performs preliminary action by predictively rendering scene imagery around the current field of view before it is actually needed. The server pre-renders images that anticipate where the player's field of view will move, so when rapid rotation occurs, the client already has the necessary imagery displayed without waiting for server updates. This eliminates lag during quick movements while maintaining game state synchronization through the periodic server updates.
2Loss of time
If additional predictive scene imagery is generated and communicated to reduce latency, then the amount of data transmitted increases, but network bandwidth is limited
Solution Approach 1:
The system applies local quality by varying the pixel density and resolution of predictive scene imagery based on its likelihood of use. Images that are more likely to be displayed (closer to the current field of view or in frequently accessed directions) are rendered at higher resolution, while less likely images are rendered at lower resolution. This selective quality adjustment reduces the total data transmission volume while maintaining acceptable visual quality for the most important predictive images, thereby reducing latency without overwhelming network bandwidth.
3Manufacturing precision
If the client crops the rendered image to generate only the present field of view, then the displayed image resolution is optimized, but no predictive scene imagery is available for rapid rotation
Solution Approach 1:
The system uses segmentation by dividing the rendered image into multiple segments: the current field of view (cropped at full resolution for optimal display quality) and additional predictive scene imagery surrounding it (rendered at variable resolutions based on likelihood of use). This segmentation allows the client to display high-resolution cropped images for normal viewing while having pre-rendered predictive segments ready for rapid rotation, thus maintaining both display precision and rotation responsiveness simultaneously.
Data Source
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AI summary
Embodiments of the present invention provide client-side scene movement using imagery generated by a game server. Embodiments of the present invention predictively render additional imagery surrounding the present field of view. The predictive scene imagery may be on all sides of the current field of view. Embodiments of the present invention determine the amount of predictive scene imagery generated according to a likelihood of use. In addition to client-adjusted rotation, embodiments of the present invention may predictively translate the field of view. Translation is moving the point of view forward, backward or side-to-side. Predictive translation imagery may be communicated to the game server for use in local translation functions.