Selective File System Object Processing for Image Level Backups
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Solution Overview
Problem
Conventional image level backup methods are inefficient as they process and store unnecessary data, leading to slow backup times and increased storage requirements, especially in scenarios with minimal deleted data or during incremental backups, and fail to optimize backups for file systems that immediately reuse deleted blocks or store unimportant data like swap files and OS files.
Innovation Solution
A system for selective processing of file system objects in image level backups, which includes a backup engine with a receiving module, connection module, file allocation table processing module, and block processing module to selectively read and save only relevant data blocks, excluding unnecessary data such as deleted blocks, swap files, and OS files, thereby optimizing both full and incremental backups.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional image level backup methods are used to backup complete disk images, then backup completeness and reliability are improved, but backup time and storage requirements increase significantly
Solution Approach 1:
The patent segments the disk image into individual blocks and uses the FAT to identify and process only the necessary blocks containing actual data, rather than processing the entire disk image sequentially. This segmentation allows the backup system to skip unnecessary blocks (deleted files, unallocated space) while maintaining complete backup capability for valuable data.
Solution Approach 2:
The patent extracts and removes unnecessary data blocks from the backup process by querying the FAT to identify blocks containing deleted or unimportant data. Only essential data blocks are selected for backup, separating valuable information from useless data that would otherwise be included in complete disk images.
2Reliability
If conventional image level backup methods are used, then all data including deleted blocks is backed up, but storage space requirements increase significantly
Solution Approach 1:
The backup process is divided into individual block-level operations guided by FAT queries. This allows selective inclusion of only blocks containing valuable data while excluding blocks with deleted or unimportant content, reducing overall backup volume while preserving essential information.
Solution Approach 2:
The system extracts and removes unnecessary data blocks from the backup by identifying them through FAT queries. Deleted file blocks, unallocated space, and other non-essential data are excluded from the backup, significantly reducing storage space requirements while maintaining data preservation for valuable files.
3Productivity
If FAT parsing is performed to identify data blocks, then backup efficiency is improved, but processing complexity increases
Solution Approach 1:
The FAT structure itself is utilized to guide the backup process. By querying the FAT, the system automatically receives structured information about which blocks contain data and which are free or deleted, eliminating the need for complex custom parsing algorithms and reducing processing complexity while maintaining high efficiency.
4Reliability
If all data blocks are processed during backup, then backup completeness is ensured, but unnecessary data processing slows down backup performance
Solution Approach 1:
The backup process is segmented into selective block processing based on FAT information. Instead of processing all blocks sequentially, the system processes only the segments (blocks) identified as containing valuable data, significantly improving performance while maintaining completeness through systematic coverage of all necessary blocks.
Solution Approach 2:
The system applies partial action by processing only the necessary subset of data blocks identified through FAT queries, rather than processing all blocks. This selective approach maintains sufficient backup completeness for valuable data while dramatically reducing unnecessary processing time and improving overall backup performance.
Data Source
AI summary
Systems, methods, and computer program products are provided for reducing the size of image level backups. An example method receives backup parameters identifying a physical or Virtual Machine (VM) to backup and at least one file system object to include in the backup. The method connects to production storage corresponding to the selected physical or virtual machine and obtains access to data stored in disk corresponding to the selected file system object(s). The method fetches file allocation table (FAT) blocks from the disk and parses contents of the FAT blocks to determine if the disk blocks correspond to the selected file system object(s). The method creates a backup disk image FAT comprising blocks corresponding to the selected file system object(s). The method creates a reconstructed disk image FAT blocks corresponding to the backup FAT and disk image data blocks belonging to the selected file system object(s) and all other disk image data blocks are saved as zero blocks. A reconstructed disc image is compressed and stored in a backup file on backup storage, or replicated (copied) to another storage intact.