Streaming Media QoE Metric Reporting via Hierarchical Segmentation
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Solution Overview
Problem
Current technologies for assessing and improving streaming media quality-of-experience (QoE) in dynamic network conditions, such as those encountered in HTTP and adaptive HTTP streaming, face challenges in efficiently reporting and adjusting to variations in bitrate, buffering times, and representation switches, leading to suboptimal user experience.
Innovation Solution
A method and system for generating and reporting quality-of-experience (QoE) metrics, including metrics like re-buffering event, buffering time, representation switch duration, and average segment fetch time, which are collected by client devices and analyzed by a QoE metric collecting server to optimize media streaming by adjusting bitrates, reducing buffering, and improving playback quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multiple quality metrics are reported for each streaming media session, then the quality assessment becomes more comprehensive, but the number of reports increases significantly
Solution Approach 1:
The patent segments quality metrics into different hierarchical levels (media presentation level, representation level, segment level) and applies different reporting strategies to each level. This allows comprehensive quality assessment through multi-level metrics while reducing overall reporting volume by aggregating certain metrics at higher levels and reporting only critical details at lower levels.
Solution Approach 2:
The patent implements selective reporting where not all quality metrics are reported with equal frequency or detail. Instead, it reports only the most critical metrics (such as representation switch duration) with higher granularity while aggregating or selectively reporting other metrics, thereby achieving adequate quality assessment with reduced reporting overhead.
2Reliability
If quality metrics are reported at a high rate, then real-time quality monitoring is improved, but network bandwidth consumption increases
Solution Approach 1:
The patent applies different reporting rates and levels of detail to different quality metrics based on their local importance. Critical metrics like representation switch duration are reported with higher frequency and detail, while less critical metrics are reported at lower rates or aggregated, optimizing the balance between real-time monitoring capability and network bandwidth consumption.
3Manufacturing precision
If detailed quality metrics are collected, then quality optimization becomes more accurate, but data processing complexity increases
Solution Approach 1:
The patent segments quality data collection and processing into multiple hierarchical levels (media presentation, representation, segment). This segmentation allows detailed metrics to be collected where needed while distributing processing complexity across different system components and levels, making the overall system more manageable despite the detailed measurement requirements.
Data Source
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AI summary
Various methods for generating and handling streaming media metrics are provided. One example method includes receiving media presentation data, where the media presentation data is associated with a presentation of streaming media, and determining, based on at least the media presentation data, one or more quality of experience metrics that are to be reported. The example method further comprises generating a metric value corresponding to each of the one or more quality of experience metrics, and causing the metric value corresponding to each of the one or more quality of experience metrics to be reported. Similar and related example methods and example apparatuses are also provided.