AI Storage Optimization Using Media File References
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Solution Overview
Problem
The increasing demand for media storage due to higher quality media files leads to rapid depletion of local storage space on devices, resulting in increased costs for additional cloud storage services and the need to delete valuable files, as existing technologies fail to efficiently manage storage without deleting user content.
Innovation Solution
A computer-implemented method using artificial intelligence to identify media files, extract metadata, search for matching files across storage locations, and predict whether local storage should be optimized by storing a link to the media file instead of the file itself, thereby reducing local storage utilization and costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If media files are stored locally on devices, then media accessibility and quality are improved, but local storage space is depleted rapidly
Solution Approach 1:
The patent creates a local copy (link/reference) of the media file metadata instead of storing the entire media file locally. This allows the device to maintain accessibility to media content while significantly reducing local storage consumption. The system stores a reference that points to the actual media file location, enabling quick access without occupying substantial local space.
Solution Approach 2:
The patent transitions from storing media files in a single local dimension to a distributed storage model across multiple dimensions (local device, cloud storage, network locations). By creating references that span multiple storage dimensions, the system maintains media accessibility while optimizing local storage utilization.
2Quantity of substance
If cloud storage services are used to compensate for limited local storage, then storage capacity is increased, but storage costs increase
Solution Approach 1:
The system performs self-service by automatically analyzing local storage capacity, identifying media files for optimization, and creating references to alternative storage locations. This automated process eliminates the need for manual user intervention and reduces reliance on paid cloud storage services by intelligently managing storage resources based on device capabilities and usage patterns.
Solution Approach 2:
The patent changes the storage parameter from storing complete media files to storing references/links to media files. This parameter change allows the system to maintain media accessibility while dramatically reducing the actual storage capacity required, thereby reducing or eliminating the need for expensive cloud storage subscriptions.
3Quantity of substance
If users delete media files to free up storage space, then local storage is optimized, but valuable files are lost
Solution Approach 1:
The patent introduces an intermediary reference mechanism that mediates between the need for local storage optimization and the desire to retain media files. Instead of directly deleting files, the system creates references that act as intermediaries, allowing users to maintain access to their media collections while freeing up local storage space. The reference serves as a placeholder that preserves the connection to the original media file.
4Measurement precision
If AI analysis is performed on media files, then storage optimization accuracy is improved, but processing time increases
Solution Approach 1:
The system performs preliminary AI analysis on media files to extract metadata and characteristics before making storage optimization decisions. By conducting this analysis in advance, the system can make accurate predictions about which files are good candidates for reference-based optimization, reducing processing time during actual storage operations while maintaining high accuracy in file selection.
Data Source
AI summary
An approach for optimizing storage on a local storage device. The approach identifies a stored or being stored on a user's local storage device. The approach extracts metadata from the media file. The approach searches the user-associated storage locations for a matching media file based on the metadata. If the approach locates the matching media file, then the approach, using artificial intelligence (AI), predicts if the local device storage should be optimized for the media file, then the approach, using AI, stores a link to the matching media file on the local device storage and removes the media file from the local device storage.