Cloud Backup Generation Merging for Cost-Aware Deletion
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Solution Overview
Problem
Existing methods for managing backup data in cloud systems are inefficient, leading to increased costs and resource consumption without optimal deletion strategies.
Innovation Solution
A computer system with a cloud storage and local storage system, utilizing a backup generation management program that compares load costs with reduction costs to determine efficient deletion of backup data generations, involving differential data acquisition, merging management files, and selective deletion processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If backup data of multiple generations is retained in cloud storage, then data recovery reliability is improved, but storage costs and resource consumption increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting the retention policy based on data characteristics. It calculates the ratio of unchanged data between generations and uses this parameter to determine whether to delete older generations. When the ratio exceeds a threshold indicating high redundancy, the system deletes older backups, thus changing the retention parameter adaptively to balance reliability and storage cost.
Solution Approach 2:
The patent implements discarding and recovering by selectively deleting redundant backup generations while preserving necessary ones. The system discards older generations that have high data overlap with newer backups (calculated via unchanged data ratio), but recovers or maintains generations that provide unique data value. This selective discarding approach reduces storage costs while maintaining adequate recovery capability.
2Quantity of substance
If all backup generations are deleted, then storage costs are reduced, but data recovery capability deteriorates
Solution Approach 1:
The patent uses parameter changes by introducing a deletion determination threshold based on the ratio of unchanged data. Instead of blanket deletion or retention policies, the system dynamically adjusts the deletion decision parameter (threshold) based on calculated redundancy metrics. This allows flexible control over what to delete, optimizing the balance between cost reduction and recovery capability maintenance.
Solution Approach 2:
The patent applies local quality by making deletion decisions at the individual generation level rather than applying a uniform policy to all backups. Each backup generation is evaluated independently based on its specific data characteristics and redundancy ratio with other generations. This localized evaluation ensures that only truly redundant data is deleted while preserving generations with unique recovery value.
3Quantity of substance
If differential data is acquired and management files are merged for multiple generations, then storage efficiency is improved, but processing complexity increases
Solution Approach 1:
The patent directly applies merging by combining management files from multiple backup generations into a single integrated file. Instead of maintaining separate metadata for each generation, the system merges them to reduce the total number of management files and improve storage efficiency. This merging operation consolidates data structures while the system manages the increased processing complexity through automated algorithms.
Data Source
AI summary
A computer system includes a backup generation management program that executes generation deletion processing of deleting backup data and a management file corresponding to M generations (M is an integer of 1 or more), when a reduction cost to be reduced by a generation deletion processing is larger than a load cost. The generation deletion processing acquires differential data of the backup data corresponding to M generations from (N+1)th generation (N is an integer of 1 or more) to (N+M)th generations. The differential data is stored in a cloud storage and the Nth generation backup data is overwritten with the differential data. The management files are merged from Nth to (N+M)th generations and the management data is associated with the Nth generation backup data. Then, the backup data and the management files from (N+1)th to (N+M)th generations are deleted.