Multi-Resolution Image Management for Faster Cloud Viewing
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Solution Overview
Problem
Users face challenges in accessing high-resolution images from cloud storage systems due to network constraints, leading to delayed viewing and interaction, especially when internet connectivity is low, which affects the user experience.
Innovation Solution
Implementing a system that categorizes and downloads content items based on expected use, allowing a first version of the content items to be viewed while a higher resolution version downloads in the background, optimizing the use of network resources and storage space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high resolution images are stored and downloaded from cloud storage, then image quality is improved, but download time and network resource consumption increase
Solution Approach 1:
The patent segments images into multiple resolution versions (e.g., thumbnail, medium, high resolution). The system automatically selects and downloads only the appropriate resolution version based on the user's device capabilities, network conditions, and intended use, rather than always downloading the full high-resolution version. This segmentation allows users to access images faster while maintaining quality when needed.
Solution Approach 2:
The system changes the resolution parameter of images dynamically based on contextual factors such as device screen resolution, network bandwidth, storage space, and predicted user interaction. By adjusting this parameter, the system optimizes the balance between image quality and download time, delivering appropriate quality without unnecessary delays.
2Manufacturing precision
If high resolution images are downloaded, then viewing quality is improved, but network resource consumption increases
Solution Approach 1:
The system dynamically adjusts the image resolution parameter based on network conditions, device capabilities, and predicted usage patterns. By changing this parameter, the system reduces network resource consumption for images that don't require high resolution, while still delivering optimal quality when the user's device and context support it.
Solution Approach 2:
The system employs machine learning models that automatically analyze user behavior patterns, device characteristics, and network conditions to make intelligent decisions about image resolution selection. This self-service approach eliminates the need for manual user input while optimizing resource usage based on contextual understanding.
3Adaptability or versatility
If multiple resolution versions of images are stored, then access flexibility is improved, but storage space requirements increase
Solution Approach 1:
The patent segments images into multiple resolution versions and stores them efficiently in the cloud. The system then selectively downloads only the necessary resolution version based on real-time conditions, providing access flexibility without requiring all resolution versions to be permanently stored on the user's device. This reduces local storage requirements while maintaining versatility.
Solution Approach 2:
The system implements a nested structure where lower resolution versions are embedded within or alongside higher resolution versions in the cloud storage hierarchy. This allows the system to efficiently manage multiple resolutions by nesting them in a way that minimizes redundant data storage while maintaining access to various resolution levels when needed.
Data Source
AI summary
Systems, methods, and non-transitory computer readable media for managing content items having multiple resolutions may be provided. In some embodiments, a user device may send a request to access one or more images from a content management system. The one or more images may be categorized on the user device by an expected use that determines that the one or more images be in a first version. A second version of the one or more images may be received while a background download of the first version of the one or more images may be performed. In some embodiments, the first version may correspond to a high-resolution image whereas the second version may correspond to a lower resolution image.