Streaming Video QOE Scoring via Session Persistence
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Solution Overview
Problem
Current methods for scoring the quality of experience (QOE) for streaming video content are ineffective and inaccurate, particularly for types like HLS, due to insufficient data on a per-connection basis and the need for user interaction.
Innovation Solution
A method utilizing application management computing devices to obtain and analyze streaming video segments, generating segment and video QOE scores based on static and dynamic parameters, with persistence across connections through a session database, eliminating the need for user interaction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current QOE scoring methods are used for HLS streaming video, then user experience analysis can be performed, but the scoring is inaccurate and ineffective due to insufficient data on a per-connection basis
Solution Approach 1:
The patent segments the video stream into multiple connections and analyzes QOE metrics for each connection separately. By dividing the overall streaming session into individual connection segments, the system can collect sufficient data for each segment to generate accurate QOE scores, resolving the data insufficiency problem while maintaining measurement precision.
Solution Approach 2:
The patent introduces a new dimension of analysis by examining QOE metrics across multiple connections simultaneously rather than treating the stream as a single entity. This multi-dimensional approach allows aggregation of data from different connection perspectives, providing sufficient information for accurate QOE scoring where single-connection analysis failed.
2Measurement precision
If user interaction methods such as surveys or questionnaires are used for QOE scoring, then QOE can be measured, but the process becomes complex and requires user participation
Solution Approach 1:
The system performs self-service QOE measurement by automatically collecting and analyzing streaming metrics without requiring user interaction. The application management computing device autonomously monitors connection parameters, video segment delivery, and playback performance to generate QOE scores, eliminating the need for surveys or questionnaires while maintaining measurement capability.
Solution Approach 2:
The patent replaces the mechanical system of user interaction (surveys, questionnaires) with an automated electronic measurement system. By substituting human-based feedback mechanisms with algorithmic analysis of streaming data, the system reduces complexity while preserving QOE measurement accuracy through objective metric collection.
3Productivity
If multiple connections are used to obtain video segments for HLS content, then streaming can be achieved, but insufficient data is available on a per-connection basis for effective QOE scoring
Solution Approach 1:
The patent merges data from multiple connections by aggregating QOE metrics across all connections associated with a single video stream. The application management computing device combines information from parallel connections to form a comprehensive QOE assessment, ensuring sufficient data availability while maintaining the productivity benefits of multi-connection streaming.
Solution Approach 2:
The patent introduces an intermediary layer (the application management computing device) that sits between the multiple connections and the QOE analysis process. This intermediary aggregates and processes data from various connections, transforming fragmented per-connection data into sufficient information for effective QOE scoring without interfering with the productivity of multi-connection streaming.
Data Source
AI summary
A method, non-transitory computer readable medium, and application management computing device that obtains a segment of streaming video content from a server device in response to a request for the segment received from a client device. One or more static or dynamic parameter values associated with the streaming video content are determined. A segment quality of experience (QOE) score is generated for the segment based on one or more of the static or dynamic parameter values. A session identifier is extracted from the request or from a response from the server device that includes the segment. A video QOE score is generated for the streaming video content based on the segment QOE score and another segment QOE score for another segment of the streaming video content retrieved from a record of a session database associated with the session identifier. The video QOE score is output.