Predicted Frame Buffering for Game Streaming Connection Drops
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Connection drops and latency during video game streaming lead to gaps in game and audio content, affecting user experience and game play performance.
Innovation Solution
Implementing prediction engines at both client devices and servers to generate predicted frames and inputs based on current game state, storing them in buffers, and using these to fill gaps in streaming content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If frames of streaming content are transmitted over network, then user can access video game from anywhere, but connection drops cause gaps in game content
Solution Approach 1:
The system performs preliminary action by generating and storing predicted frames in advance at both server and client devices. When connection drops occur, these pre-generated predicted frames are used to fill gaps without requiring real-time retransmission, thus maintaining content delivery continuity while preserving remote access capability.
2Speed
If connection is maintained for real-time streaming, then game inputs are transmitted promptly, but latency occurs due to poor connection
Solution Approach 1:
The system creates copies of game inputs and predicted frames at both server and client devices. When connection latency occurs, the client device uses its local copy of predicted frames to maintain gameplay continuity, effectively bypassing the latency issue while preserving real-time input transmission capability.
3Productivity
If predicted frames are generated at client device, then gaps can be filled quickly, but device complexity increases
Solution Approach 1:
The system merges the predicted frame generation capability between server and client devices. The server generates predicted frames based on game state, and the client device stores and uses these predicted frames. This distribution of functionality allows efficient gap filling while avoiding the need for complex prediction algorithms at the client device.
4Reliability
If buffering is implemented to store predicted frames, then seamless rendering is achieved, but loss of time occurs during buffer management
Solution Approach 1:
The system maintains continuity of useful action by continuously generating and updating predicted frames in buffers at both server and client devices during normal operation. When connection drops occur, the pre-buffered predicted frames are immediately available for gap filling without requiring buffer management operations during the critical gap-filling period, thus achieving seamless rendering while minimizing buffer management time.
Data Source
AI summary
Methods and system for providing streaming content of a video game at a client device includes receiving frames of streaming content from a game server. The frames represent a current game state. The frames are analyzed to generate predicted frames that are likely to occur following the current frames. The predicted frames are stored in a prediction frame buffer and used to fill any gaps in subsequent frames representing subsequent game state received from the game server.