Video Playing Control Algorithm Adaptation for Quality Trade-offs
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Solution Overview
Problem
Existing video playing control algorithms fail to consider all quality indicators in dynamic network conditions, leading to trade-offs between video quality and start delay, resulting in suboptimal viewing experiences across different devices.
Innovation Solution
A method where terminal devices and servers collaborate to dynamically adjust video playing policies by collecting and analyzing quality indicator data, selecting appropriate control algorithms based on device type, network conditions, and historical usage, and updating algorithms to optimize video quality and smoothness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a video bitstream with a low resolution and bit rate is selected to achieve short playing start delay and zero freeze, then video playing smoothness is improved, but video playing definition deteriorates
Solution Approach 1:
The patent applies dynamics by transitioning from static empirical parameters to dynamic adaptive control. The control algorithm continuously adjusts video bitstream parameters (resolution, bit rate) in real-time based on changing network conditions, terminal device capabilities, and playback state, enabling the system to optimize both smoothness and definition dynamically rather than being constrained by fixed parameter settings
Solution Approach 2:
The patent implements parameter changes by modifying key control parameters including video resolution, bit rate, buffering strategy, and playback speed based on real-time feedback from multiple quality indicators. This allows the system to adapt parameter combinations to simultaneously achieve good smoothness and definition under different network conditions
2Manufacturing precision
If a video bitstream with a high resolution and bit rate is selected to achieve good video playing definition, then video quality is improved, but playing start delay increases and freeze rate increases
Solution Approach 1:
The patent applies preliminary action by pre-buffering video data and pre-selecting appropriate bitstream parameters based on initial network condition assessment and terminal device capabilities. This allows the system to start playback quickly with lower resolution initially, then switch to higher resolution once sufficient buffer is accumulated, reducing perceived start delay while maintaining definition
Solution Approach 2:
The system dynamically adjusts the balance between start delay and definition by continuously monitoring network conditions and playback state, transitioning from low-resolution fast-start mode to high-resolution quality mode as conditions permit
3Device complexity
If static empirical data from laboratory network model testing is used for control algorithm parameters, then algorithm simplicity is maintained, but adaptability to complex and changeable network conditions deteriorates
Solution Approach 1:
The patent implements feedback by collecting real-time quality indicator data from actual video playback including network bandwidth measurements, playback smoothness metrics, definition quality assessments, and freeze events. This feedback loop enables the control algorithm to learn from actual performance and adapt to complex and changing network conditions that cannot be fully replicated in laboratory testing
Solution Approach 2:
The system applies self-service by enabling the control algorithm to automatically adjust its own parameters based on collected quality indicator data without requiring manual reconfiguration or external intervention, allowing continuous adaptation to changing conditions
4Reliability
If different quality indicators are considered in video playing control, then comprehensive video quality is improved, but control algorithm complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the control algorithm into modular functional components: quality indicator collection module, data processing module, parameter selection module, and execution module. Each module handles specific aspects of multi-indicator consideration, making the overall complex system manageable and maintainable while achieving comprehensive video quality optimization
Data Source
AI summary
A video playing control method includes obtaining a video playing policy, where the video playing policy determines information about a control algorithm used for video playing, determining according to the video playing policy, a target control algorithm used for video playing, downloading and playing a video by using the target control algorithm, collecting video playing quality indicator data in a process of downloading and playing the video, and uploading the quality indicator data to a server, to indicate the server to adjust the video playing policy based on the quality indicator data.