Streaming Media Quality Prediction via Network Correlation
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Solution Overview
Problem
Current tools and methods fail to accurately predict the quality of streaming media over wireless networks, as they do not account for wireless network performance factors and user experience, leading to unsatisfactory video and audio delivery due to network conditions like throughput and latency.
Innovation Solution
A system and method that uses real-time network performance measurements and statistical analysis to correlate network parameters with audio and video quality, generating a video quality score to predict streaming media performance, incorporating these measurements into a database for predictive insights.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current tools and methods are used to measure network performance, then throughput and range can be measured, but they fail to accurately predict streaming media quality and user experience
Solution Approach 1:
The patent introduces a correlation database as an intermediary component that stores pre-established relationships between network performance parameters and streaming media quality metrics. This database acts as a mediator between raw network measurements and quality predictions, enabling accurate predictions without requiring complex real-time analysis algorithms. The correlation database translates throughput and range measurements into meaningful quality predictions by referencing pre-computed correlations.
Solution Approach 2:
The patent performs preliminary actions by pre-establishing correlations between network performance parameters and streaming media quality metrics before actual streaming occurs. The system pre-computes and stores these correlations in a database, so that when streaming takes place, accurate quality predictions can be made immediately by querying the pre-established correlations rather than performing complex real-time analysis.
2Speed
If streaming media is transmitted over wireless networks, then users can access content immediately, but network conditions like throughput and latency cause unsatisfactory video and audio delivery
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors actual streaming media quality and compares it against predicted quality based on network performance measurements. This feedback loop allows the system to adjust and refine correlation values in the database, improving prediction accuracy over time. The feedback ensures that the system adapts to changing network conditions and maintains reliable quality predictions even as streaming occurs.
3Measurement precision
If network performance measurements are taken in real-time, then accurate predictions can be made, but the system requires complex statistical analysis and correlation databases
Solution Approach 1:
The patent performs the complex statistical analysis and correlation establishment in advance, before real-time streaming occurs. By pre-computing correlations between network parameters and quality metrics and storing them in a database, the system eliminates the need for complex real-time statistical analysis during actual streaming. This preliminary action shifts the computational burden to an offline phase, simplifying real-time operations.
Data Source
AI summary
An improved system and method for predicting streaming media performance through the use of real-time wireless network performance measurements and statistical analysis, combined with a generalized methodology for comparing digital media quality before and after transmission. Network performance parameters of a benchmark media stream, such as throughput and signal strength, are measured for predetermined wireless network ranges and correlated to the introduction of various artifacts such as but not limited to, blurring, blockiness, and jerkiness, affecting streaming video quality. In various embodiments of the invention, network throughput and signal strength measurements of a received media stream can be processed by an algorithm and correlated to previously collected benchmark measurements to predict the resulting audio and video quality as experienced by a user.