Live Video Upload Quality Adaptation via Aggregated Network Statistics
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Solution Overview
Problem
Conventional adaptive quality schemes for live video streaming from mobile devices are inefficient in determining optimal upload quality, leading to suboptimal video quality and increased processing time due to iterative processes in response to changing network conditions.
Innovation Solution
The use of aggregated network statistics to estimate network conditions and apply a heuristic estimation model for initial quality setting and continuous adaptation of upload quality parameters, such as bitrate, resolution, and frame rate, to quickly achieve optimal upload quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional adaptive quality schemes are used to determine upload quality in response to changing network conditions, then the system can adapt to network changes, but the iterative process causes increased processing time and delays in achieving optimal upload quality
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing quality parameters for different network conditions before they are needed. The server pre-computes quality settings based on historical network statistics and makes them available for immediate selection, eliminating the need for iterative adjustments when network conditions change. This allows the client to quickly switch to pre-determined optimal settings based on current network state.
Solution Approach 2:
The system implements feedback mechanisms where the client reports network conditions and quality metrics to the server, which then provides updated quality recommendations. This closed-loop feedback enables the system to adapt to changing conditions while using pre-computed parameters to minimize processing delays, balancing adaptability with rapid response.
2Manufacturing precision
If conventional iterative processes are used to adjust upload quality, then the system can optimize video quality, but it consumes excessive processing resources and time
Solution Approach 1:
The server performs preliminary computation of quality parameters based on historical network statistics and stores these pre-optimized settings. When the client needs quality adjustments, it directly applies these pre-computed parameters without performing iterative optimization locally, significantly reducing processing resource consumption while maintaining video quality optimization.
Solution Approach 2:
The server acts as an intermediary that centralizes the computationally intensive quality optimization work. Instead of each client device performing iterative optimization independently (consuming local processing resources), the server pre-computes optimal parameters and distributes them to clients, improving overall system productivity while maintaining optimization quality.
3Adaptability or versatility
If real-time adaptive bitrate streaming is implemented, then the system can respond to bandwidth changes, but the iterative quality determination process delays the response time
Solution Approach 1:
The system pre-computes quality parameters for various bandwidth conditions and stores them for rapid retrieval. When bandwidth changes occur, the client can immediately switch to appropriate pre-determined settings based on current network state, eliminating the delay caused by iterative quality determination and achieving both adaptability and fast response.
Data Source
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AI summary
Implementations disclose leveraging aggregated network statistics for enhancing quality and user experience for live video streaming from mobile devices. A method includes receiving, by a processing device of a client device, a bandwidth parameter corresponding to aggregated network statistics for at least one of a current geographic location of the client device or a current network of the client device, initializing an upload quality parameter of an upload session based on the received bandwidth parameter, the upload session comprising upload of content from the client device, and modifying, by the processing device, the upload quality parameter during the upload session based on updated bandwidth parameters corresponding to aggregated network conditions for at least one of new geographic locations of the client device or new networks of the client device, the upload quality parameter being used to control a format of the upload session.