Document Storage Tiering Using Metadata and Access Metrics
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Solution Overview
Problem
Existing document management systems lack the ability to automatically classify and manage documents for optimized storage costs, requiring manual organization of documents between hot and cold storages based on access frequency, which is inefficient and time-consuming.
Innovation Solution
A computer-implemented method and system that analyzes metadata and attributes of documents to automatically categorize them into hot, warm, or cold storages based on usage metrics, periodically or on-demand, re-routing documents if usage patterns change, and optimizing storage costs by saving frequently accessed documents in higher-cost storages and less-frequently accessed documents in lower-cost storages.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If manual organization of documents into hot, warm, and cold storages is performed, then storage cost can be reduced by placing less frequently accessed documents in cold storage, but the process requires manual intervention and time-consuming reorganization
Solution Approach 1:
The system automatically classifies and organizes documents into hot, warm, and cold storages based on access frequency metrics without requiring manual intervention. The automated classification mechanism continuously monitors document access patterns and routes documents to appropriate storage tiers, eliminating the need for manual reorganization while optimizing storage costs.
Solution Approach 2:
The system implements continuous monitoring of document access frequency and uses this feedback to dynamically classify documents into different storage tiers. By regularly analyzing access metrics and adjusting document placement accordingly, the system optimizes storage costs over time while eliminating manual reorganization requirements.
2Extent of automation
If automated document classification is implemented, then manual intervention is minimized and storage cost is optimized, but the system complexity increases due to metadata analysis and usage pattern monitoring
Solution Approach 1:
The system extracts and analyzes metadata from documents during the initial upload phase, pre-classifying documents into appropriate storage tiers before they are needed. This preliminary action reduces the complexity of ongoing management by establishing document classification rules and usage pattern baselines in advance, enabling automated decision-making without complex real-time analysis.
Solution Approach 2:
The system creates a simplified representation of document characteristics through metadata extraction and usage pattern modeling, rather than analyzing the actual document content in detail. This copying approach allows the system to make classification decisions based on summarized attributes, reducing computational complexity while maintaining effective automated classification.
3Adaptability or versatility
If documents are continuously monitored and re-routed based on changing usage patterns, then storage optimization is maintained over time, but the processing load and system resources increase
Solution Approach 1:
The system performs document classification and reorganization at periodic intervals rather than continuously, analyzing usage patterns and reclassifying documents at scheduled times. This periodic action maintains adaptability to changing usage patterns while significantly reducing processing load compared to continuous monitoring and re-routing of all documents.
Solution Approach 2:
The system monitors and analyzes only the most relevant document attributes and usage metrics necessary for classification decisions, rather than processing all possible document characteristics. This partial action approach maintains effective usage pattern adaptation while minimizing processing resources and energy consumption.
Data Source
AI summary
A document management method for optimizing storage costs of new importing documents and existing documents are disclosed. The method categorizes the uploaded documents and the existing documents based on metadata and attributes embedded therein and saves the uploaded documents and the existing documents in a cold storage or a hot storage based on their usage or access metrics calculated from the attributes. A document management system that managing storages of new uploaded documents and the existing documents using the above method is also disclosed.