Backup Data Object Prioritization via Nearest-Critical Ordering
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Solution Overview
Problem
Existing data backup solutions lack a mechanism to determine the storing priority of data during backup operations, leading to potential data loss in case of a disaster occurring during or before the backup is complete.
Innovation Solution
The system reorders data objects in a 'nearest-critical based sequential order' using modified weight-based Euclidean distances calculated between adjacent data object pairs, ensuring critical data is written first by incorporating data criticality factors, thereby prioritizing storage during backup operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data objects are stored in the order they arrive in the queue, then the backup operation is simple and fast, but critical data may be lost if a disaster occurs during backup
Solution Approach 1:
The system performs preliminary classification of data objects into critical and non-critical categories before the backup operation begins. Critical data objects are identified and marked in advance, allowing them to be prioritized during the backup process without adding complexity to the actual write operation.
Solution Approach 2:
The system changes the priority parameter of data objects based on their criticality classification. By assigning different priority levels (critical vs. non-critical) to data objects, the system enables differentiated handling during backup operations, ensuring critical data is written first while maintaining a relatively simple overall process.
2Reliability
If critical data is prioritized for storage, then data protection reliability is improved, but the backup operation requires complex priority determination mechanisms
Solution Approach 1:
The system performs preliminary classification of data objects into critical and non-critical categories before the backup operation begins. Critical data objects are identified and marked in advance, allowing them to be prioritized during the backup process without adding complexity to the actual write operation.
Solution Approach 2:
The system changes the priority parameter of data objects based on their criticality classification. By assigning different priority levels (critical vs. non-critical) to data objects, the system enables differentiated handling during backup operations, ensuring critical data is written first while maintaining a relatively simple overall process.
3Loss of time
If all data objects are backed up with equal priority, then the backup process is straightforward, but time is lost and critical data may be compromised
Solution Approach 1:
The system performs preliminary classification of data objects into critical and non-critical categories before the backup operation begins. Critical data objects are identified and marked in advance, allowing them to be prioritized during the backup process without adding complexity to the actual write operation.
Solution Approach 2:
The system changes the priority parameter of data objects based on their criticality classification. By assigning different priority levels (critical vs. non-critical) to data objects, the system enables differentiated handling during backup operations, ensuring critical data is written first while maintaining a relatively simple overall process.
Data Source
AI summary
A method and system for prioritizing critical data object storage during backup operations. Specifically, the method and system disclosed herein entail reordering data objects, awaiting being written to storage and thus queued in one or more data object queues, in accordance with a nearest-critical based sequential order. The nearest-critical based sequential order may be derived through modified weight-based Euclidean distances calculated between adjacent data object pairs queued in any given data object queue. Further, the calculated modified weight-based Euclidean distances incorporate data criticality factors associated with the adjacent data object pairs. By reordering data objects in a nearest-critical based sequential order, critical data objects may be written into storage first, thereby avoiding possible critical data loss should a disaster occur during backup operations.


