Selective Backup Based on File History Data
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Solution Overview
Problem
Current backup systems indiscriminately include unimportant digital content, leading to resource wastage and increased costs due to the growing volume of digital media, which is often of temporary or freely available nature.
Innovation Solution
A method and system for performing selective backup operations based on file history data, where a business rule engine determines whether files should be included in backups by analyzing data from a file history database, considering factors like file creation, modification, ownership, and content, to approximate the importance of files to the user.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If backup systems include all digital content to ensure complete data protection, then data security is improved, but resource consumption and costs increase due to backing up incidental material
Solution Approach 1:
The patent applies local quality by differentiating between important and incidental files at the individual file level rather than treating all files uniformly. The system analyzes specific file attributes (extension, size, creation date, access patterns) to determine which files warrant backup, allowing selective application of backup resources to only those files that meet importance criteria.
Solution Approach 2:
The patent segments the backup process into distinct phases: file identification, attribute analysis, importance determination, and selective backup execution. This segmentation allows the system to process files individually based on their characteristics rather than backing up everything at once, optimizing resource allocation across the backup operation.
2Reliability
If backup systems include all digital content to ensure complete data protection, then data security is improved, but backup operation costs increase due to unnecessary data retention
Solution Approach 1:
The system evaluates each file's individual characteristics (extension, size, creation date, access patterns) to determine its importance, applying backup resources only to files that meet specific criteria. This local quality approach prevents unnecessary backup of incidental material while ensuring important files are protected.
Solution Approach 2:
The patent implements partial action by backing up only a subset of files that are determined to be important based on analyzed attributes, rather than performing complete backup of all digital content. This selective approach reduces data volume consumed in backup operations while maintaining adequate protection for valuable files.
3Reliability
If backup systems perform comprehensive backups of all files, then complete data recovery capability is improved, but backup operation time increases
Solution Approach 1:
The backup operation is segmented into phases: file scanning, attribute analysis, importance determination, and selective backup. This segmentation reduces total backup time by identifying and backing up only important files rather than processing every file in the system, while still maintaining recovery capability for critical data.
Solution Approach 2:
The system performs partial backup action by selecting only files that meet importance criteria for inclusion in the backup set. This reduces backup operation time significantly compared to comprehensive backups, while the selective nature ensures that backed-up files represent the most valuable data requiring protection.
Data Source
AI summary
A method involves generating a business rule; the business rule indicates whether a file should be included in a backup operation. Data is accumulated in a file history database, and the data represents one or more associations of the file. A result is determined, indicating whether the business rule indicates the file should be included in the backup operation. The result is based, at least in part, on the data in the file history database. The result is reported.