Terminal QoE Estimation via Application-Specific Color-Coded Icons
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Users lack effective methods to estimate and output Quality of Experience (QoE) for various applications on terminals, such as smartphones and laptops, which affects user experience due to varying network and cloud conditions.
Innovation Solution
A method is implemented on terminals to perform QoE estimation on an application basis, using criteria set based on user data and preferences, and outputting estimated QoE information through color-coded icons or links, allowing users to anticipate the quality of experience before application execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If QoE estimation is performed on an application basis with detailed criteria, then measurement precision is improved, but device complexity increases
Solution Approach 1:
The QoE estimation process is segmented into distinct components: network condition acquisition, application-specific criterion application, and separate output generation. Each component handles a specific aspect of the estimation, reducing overall system complexity while maintaining precision through specialized processing for each segment.
Solution Approach 2:
QoE estimation criteria are pre-configured for different application types before actual QoE measurement. The terminal stores multiple sets of criteria corresponding to different application categories, allowing rapid selection and application during runtime without complex real-time decision-making, thus reducing device complexity while maintaining measurement precision.
2Loss of information
If QoE information is output for multiple applications, then information completeness is improved, but loss of information increases due to output limitations
Solution Approach 1:
The terminal uses color-coded icons or links to represent QoE levels for different applications. Each color corresponds to a specific QoE range, allowing multiple applications to be displayed simultaneously with their QoE status visible at a glance. This visual encoding method overcomes text output limitations while maintaining information completeness and reducing the complexity of the output mechanism.
Data Source
AI summary
Implementations and techniques for outputting information about estimated QoEs on a terminal on which plural applications can be executed are generally disclosed. The estimated QoEs may be obtained by performing QoE estimation on an application basis.