Content Data Segmentation for Mobile Device Resource Management
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Solution Overview
Problem
Modern mobile devices experience performance issues due to the accumulation of various data types, which users often fail to identify and address, leading to frustration and inefficient troubleshooting.
Innovation Solution
A system and method that determines the impact of different data types on device resources and presents this information to users, allowing them to understand which data types are causing performance issues and providing suggestions for mitigation, such as deleting or moving certain content to improve device responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If users store more content data on mobile devices, then the device's storage capacity and functionality are improved, but the device's responsiveness and performance deteriorate due to resource constraints
Solution Approach 1:
The patent segments content data into different data types (e.g., images, videos, documents, applications) and analyzes their individual impacts on device resources. This segmentation allows users to identify which specific data types are causing performance issues, enabling targeted management rather than blanket deletion of all content.
Solution Approach 2:
The system changes the parameter representation by displaying effect information that quantifies the impact of each data type on device resources (e.g., storage space occupied, processing power consumed). This transformation of abstract resource usage into visible, comparable parameters helps users make informed decisions about content management.
2Difficulty of detecting and measuring
If the device processes and analyzes content data to identify performance issues, then troubleshooting capability is improved, but the complexity of the system increases
Solution Approach 1:
The system performs self-service by automatically monitoring device resources, analyzing the impact of different content data types, and generating visual representations of performance bottlenecks. This automation reduces the need for complex manual troubleshooting procedures while maintaining system intelligence.
Solution Approach 2:
The patent implements feedback by continuously monitoring device resource usage and providing users with visual information about which content data types are affecting performance. This feedback loop enables users to make real-time adjustments to their content storage without requiring complex diagnostic tools.
3Loss of information
If the system provides detailed information about content data impact, then user understanding and control are improved, but the information processing requirements increase
Solution Approach 1:
The system applies partial action by focusing analysis only on the most impactful data types rather than processing all content uniformly. It identifies and highlights only those content categories that significantly affect device performance, reducing unnecessary processing while still providing comprehensive information where needed.
Data Source
AI summary
An approach is provided for representing content data. The cleanup manager determines one or more data types of content associated with a device. Next, the cleanup manager determines effect information regarding one or more effects on one or more resources of the device with respect to the one or more data types. Then, the cleanup manager presents one or more representations of the one or more data types, wherein the one or more representations are based, at least in part, on the effect information.