Dynamic Cloud Gaming Encoder Tuning for Latency and Video Quality
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Solution Overview
Problem
Cloud gaming systems face challenges in achieving optimal tradeoffs between one-way latency and video quality due to limitations in network connections and processing capabilities, leading to inconsistent and high latency in streaming high-quality video frames.
Innovation Solution
Implementing high-performance encoders and decoders with dynamic tuning based on client bandwidth, monitoring skipped frames, scene changes, and target frame size, and adjusting parameters like encoder bit rate, target frame size, and quantization parameter (QP) to reduce latency while maintaining video quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If encoder bit rate is increased to improve video quality, then video quality is improved, but one-way latency increases due to longer encoding time
Solution Approach 1:
The encoder dynamically adjusts the bit rate based on real-time network conditions and latency requirements. The system monitors network bandwidth and latency metrics, then adaptively modifies encoding parameters to balance video quality against encoding time, ensuring optimal performance under varying conditions
Solution Approach 2:
The system changes encoder parameters (bit rate, resolution, compression level) based on monitored network conditions. When latency is high or network bandwidth is limited, the encoder reduces bit rate or adjusts other parameters to decrease encoding time while maintaining acceptable video quality
2Manufacturing precision
If target frame size is increased to improve video quality, then video quality is improved, but encoding time increases leading to higher latency
Solution Approach 1:
The target frame size is dynamically adjusted based on network conditions and latency metrics. The encoder monitors performance and adaptively changes frame size parameters to optimize the balance between video quality and encoding speed under different operating conditions
3Loss of time
If network transmission speed is increased to reduce latency, then one-way latency is reduced, but video quality deteriorates due to compression limitations
Solution Approach 1:
The encoder adjusts transmission parameters including bit rate, frame size, and compression level based on network conditions. When network bandwidth is limited, the system optimizes parameters to reduce latency while maintaining acceptable video quality through adaptive compression
4Loss of time
If processing capabilities at server are increased to reduce latency, then one-way latency is reduced, but system complexity increases
Solution Approach 1:
The system performs preliminary actions by pre-configuring encoder parameters and caching frequently used encoding settings. This preparation work reduces the complexity of real-time encoding decisions and enables faster processing without requiring excessive computational resources during actual encoding
Data Source
Figure 1A~1B
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Figure 2B
AI summary
A method for cloud gaming. The method including generating a plurality of video frames when executing a video game at a cloud gaming server. The method including encoding the plurality of video frames at an encoder bit rate, wherein the plurality of video frames that is compressed is transmitted to a client from a streamer of the cloud gaming server. The method including measuring a maximum receive bandwidth of a client. The method including monitoring the encoding of the plurality of video frames at the streamer. The method including dynamically tuning a parameter of the encoder based on the monitoring of the encoding.