Incremental Inversion for Cloud File Version Restoration
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Solution Overview
Problem
Cloud-based data restoration methods are inefficient as they require transmitting and restoring the entire baseline backup of large files, which is time-consuming and bandwidth-intensive, especially when only incremental changes need to be applied to restore a previous file version.
Innovation Solution
The incremental inversion process identifies and applies byte ranges of tracked changes in incremental backups to locally restore a file version without needing the entire baseline backup, creating an effective patch that transforms the local file version from recent to earlier states by reversing incremental changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If incremental backups are used to reduce storage requirements, then storage efficiency is improved, but restoration time increases significantly
Solution Approach 1:
The patent inverts the traditional restoration approach by applying incremental changes in reverse chronological order. Instead of restoring the baseline first and then applying all increments sequentially, the system starts with the most recent incremental backup and applies previous increments backwards, enabling faster restoration by leveraging already-restored recent data.
Solution Approach 2:
The system performs preliminary actions by maintaining and utilizing the most recent incremental backup locally. When restoration is needed, this recently restored incremental serves as the starting point, eliminating the need to restore the entire baseline and all intermediate increments, thus preliminary preparation significantly reduces restoration time.
2Reliability
If the entire baseline backup is transmitted for restoration, then complete file recovery is achieved, but bandwidth consumption increases
Solution Approach 1:
The patent extracts only the necessary data portions from the backup set for restoration. By identifying which incremental backups contain the required file versions and extracting only those specific data segments, the system avoids transmitting the entire baseline backup, significantly reducing bandwidth consumption while maintaining complete file recovery capability.
Solution Approach 2:
The backup data is segmented into discrete incremental units, each representing a specific time period's changes. The restoration process selectively retrieves and applies only the necessary segments (incrementals) needed to reconstruct the desired file version, rather than transmitting the complete baseline, thus reducing bandwidth usage while ensuring complete recovery.
3Measurement precision
If all incremental backups are applied sequentially to the baseline, then accurate file version restoration is achieved, but restoration complexity increases
Solution Approach 1:
The patent simplifies restoration complexity by inverting the application order of incremental backups. Instead of sequentially applying increments from oldest to newest on top of the baseline, the system applies them in reverse chronological order, leveraging the fact that recent increments are already restored locally. This inversion maintains version accuracy while dramatically simplifying the restoration process.
Data Source
AI summary
In one example, a method includes receiving, at a client where a version of a file is locally stored, an inversion patch concerning the local file version, the inversion patch including original content of one or more byte ranges that embrace changes reflected in the locally stored version of the file version that were made subsequent to creation of a target version of the file with which the locally stored file version is associated, unlocking the local file version, and applying the inversion patch to the unlocked local file version to create a restored file version that matches the target version of the file. The restored file version is then saved.