Intelligent Data Backup Scoring for Change Detection
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Solution Overview
Problem
Current data backup methods are inefficient as they often backup entire files, even if only metadata has changed, leading to unnecessary processing and resource consumption, and may not accurately determine if data needs to be backed up due to rearrangements or changes in metadata without altering the file content.
Innovation Solution
A system that computes a score for data files to determine if they have changed since the last backup, only backing up files with scores different from the previous backup, thereby reducing unnecessary backups and focusing on content changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the system checks only metadata changes to determine backup necessity, then the backup process becomes faster and less resource-intensive, but it may miss detecting actual content changes when metadata remains unchanged
Solution Approach 1:
The patent segments the change detection process into two independent components: metadata analysis (file attributes, timestamps, permissions) and content analysis (actual file data comparison). This segmentation allows the system to perform rapid metadata checks first, and only proceed to content analysis when metadata indicates a potential change, thus resolving the contradiction between speed and accuracy.
Solution Approach 2:
The patent implements a two-stage verification process where metadata checking serves as a preliminary filter (partial action). Only when metadata suggests a change does the system perform the more resource-intensive content comparison (excessive action). This partial action approach optimizes the balance between quick detection and accurate verification.
2Measurement precision
If the system performs content comparison to accurately detect data changes, then backup accuracy improves, but processing time and computational resources increase significantly
Solution Approach 1:
The patent performs preliminary metadata analysis before conducting content comparison. By checking file attributes, timestamps, and other metadata first, the system can identify and skip files that haven't changed, performing the time-consuming content comparison only on files where metadata indicates a potential change. This preliminary action significantly reduces overall processing time while maintaining accuracy.
Solution Approach 2:
The patent introduces metadata as an intermediary layer between the backup system and content comparison. This intermediary provides a fast, low-cost filtering mechanism that precedes the more resource-intensive content analysis, allowing the system to accurately identify changed files without always performing full content comparisons.
3Reliability
If the system backs up all files regardless of changes, then data protection completeness is ensured, but unnecessary backups consume excessive storage space and processing resources
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors file metadata and compares it against the previous backup state. This feedback loop enables the system to intelligently determine which files have actually changed and require backup, versus files that remain unchanged and can be skipped, thus ensuring data protection completeness while avoiding unnecessary resource consumption.
Solution Approach 2:
The patent monitors changes in file parameters (metadata such as timestamps, attributes, permissions) to determine backup necessity. By tracking parameter changes rather than blindly backing up all files, the system ensures that only files with actual changes are backed up, maintaining reliability while reducing energy and resource consumption.
Data Source
AI summary
A system according to certain aspects improves the process of creating secondary copies of data (e.g., creating backup copies). The system can compute the score of the data (e.g., a computer file storing information) to be backed up, and determine whether the score satisfies one or more threshold criteria before backing up the data. In one example, a change in score indicates a change in the content of the data. The threshold criteria may be that the score be different from the score of the most recently backed up copy of the data.