Automated Storage Medium Assignment for Backup Data
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Solution Overview
Problem
Current backup software lacks the intelligence to automatically classify files and assign the correct storage medium based on file characteristics, requiring human intervention that is impractical due to the volume and speed of data processing.
Innovation Solution
Implementing a data classifier that automates the classification and assignment of storage media types for each file during the backup process, using dedupe and non-dedupe storage efficiently based on file types, compressibility, and service level agreements, thereby reducing costs and meeting data protection requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual classification and sorting of data is performed by a user, then storage medium assignment can be controlled, but the process becomes impractical due to the volume and speed of data beyond human capability
Solution Approach 1:
The backup software automatically classifies files and assigns storage media without requiring user intervention. The system analyzes file characteristics, determines data types, and autonomously selects appropriate storage mediums, making the process self-serving and eliminating the bottleneck of manual classification.
Solution Approach 2:
The patent replaces the mechanical human classification process with an automated computational system. The backup software uses algorithms to analyze file metadata, content characteristics, and storage requirements, substituting human cognitive processes with machine-based automated decision-making to achieve high-speed data classification.
2Device complexity
If backup software assigns storage medium on an entire asset basis, then the process is simple, but it limits flexibility and prevents optimal storage selection on a per file basis
Solution Approach 1:
The patent segments the storage assignment process from the asset level to the individual file level. Instead of assigning a single storage medium to all files in a backup set, the system evaluates each file independently and assigns appropriate storage media based on individual file characteristics, enabling granular and optimized storage allocation.
Solution Approach 2:
The system applies different storage medium assignments to different files based on their specific characteristics. Files are classified into categories such as highly compressible, moderately compressible, and non-compressible, and each category is assigned to the most appropriate storage medium locally, optimizing storage efficiency for each file type rather than applying a uniform approach.
3Reliability
If deep technical understanding of each storage medium is required, then optimal storage can be selected, but the user burden increases significantly
Solution Approach 1:
The backup software embeds the technical expertise required for storage medium selection within the system itself. The software automatically analyzes file characteristics, evaluates storage medium properties, and makes optimal assignment decisions without requiring the user to possess deep technical knowledge of storage technologies, thereby maintaining reliability while improving ease of operation.
Data Source
AI summary
One example method includes defining object groups by classifying each object in a backup saveset based on respective object types of the objects such that all objects in an object group are the same object type, assigning a different respective storage media type to each of the object groups, storing each object group at a respective storage target, representing each object group with a respective Merkle tree that includes a base hash, and mapping each base hash to the storage target where the object group associated with the Merkle tree that includes the base hash is stored.