Bitrate Selection Algorithm Parameter Tuning
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Solution Overview
Problem
Existing adaptive bitrate selection algorithms for media streaming face challenges in optimizing parameter settings for diverse client devices and varying network conditions, leading to negative user experiences due to manual configuration that fails to account for specific device and location variations.
Innovation Solution
Segmenting streaming sessions based on characteristics like device type and geographic location, and dynamically adjusting parameter settings through control and test subsets to refine settings over time, with performance data comparison to determine optimal settings for improved playback performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual parameter settings are used to optimize algorithms for typical network conditions, then algorithm performance is improved for average cases, but user experience deteriorates for diverse client devices and varying network conditions
Solution Approach 1:
The patent segments the user base into different groups based on device characteristics, network conditions, and session attributes. By dividing the homogeneous manual configuration approach into heterogeneous segments, the system can apply tailored parameter settings to each segment, thereby maintaining reliable algorithm performance while adapting to diverse user experiences across different devices and network conditions.
Solution Approach 2:
The patent implements local quality by providing different parameter settings to different segments of users based on their specific characteristics. Instead of applying a uniform manual configuration to all users, the system customizes parameter settings locally for each segment, ensuring that each user group receives optimized settings suited to their specific device and network conditions, thus improving both reliability and adaptability.
2Device complexity
If single set of parameter settings is provided for all clients, then system complexity is reduced, but playback performance deteriorates for specific device and network condition combinations
Solution Approach 1:
The patent segments clients into distinct groups based on their characteristics and provides customized parameter settings to each segment. This segmentation approach maintains relatively simple system complexity by using predefined segments rather than fully custom configurations for each client, while simultaneously improving playback performance by tailoring settings to specific device and network condition combinations.
Solution Approach 2:
The patent applies parameter changes by adjusting algorithm parameters differently for different client segments. By changing parameter values based on segment characteristics rather than using a single fixed set of parameters for all clients, the system improves playback performance for specific device and network condition combinations while keeping the overall system complexity manageable through systematic parameter management.
3Ease of operation
If administrator-configured parameter settings are used, then ease of operation is improved through centralized control, but adaptability to specific network conditions and device variations deteriorates
Solution Approach 1:
The patent segments users into different groups and applies different parameter settings to each segment while maintaining centralized administrator control. This approach preserves ease of operation by allowing administrators to manage configurations centrally, while simultaneously improving adaptability by tailoring settings to specific network conditions and device variations through segment-based differentiation.
Solution Approach 2:
The patent implements universality by creating a parameter configuration system that serves multiple functions: centralized administrator control for ease of operation, and automated segment-based adaptation for specific network conditions and device variations. The system universally applies different parameter sets to different segments, achieving both centralized management and condition-specific optimization.
Data Source
AI summary
Techniques are described for adjusting parameter settings for bitrate selection algorithms for different segments of a population of devices streaming content. Streaming sessions are identified according to session characteristics. Within each segment of sessions, control parameter settings are sent to devices corresponding to a subset of each segment. Test parameter settings are sent to devices corresponding to another subset of each segment. If the test parameter settings result in better playback performance relative to the control parameter settings, the test parameter settings become the new control parameter settings, and new test parameter settings are generated.


