Delta Data Storage Using Historical Change Prediction
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Solution Overview
Problem
The increasing demand for data storage in emerging applications like AI, big data, and IoT leads to high purchase and management costs, as well as significant power consumption and space occupation, necessitating an effective data storage solution.
Innovation Solution
A method that generates deltas between current and historical data using AI neural algorithms, compresses these deltas, and stores them instead of the current data, along with mechanisms for efficient data restoration and compression/decompression to reduce storage overheads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data storage capacity is increased to meet growing data storage demands, then storage capacity is improved, but purchase costs and management costs increase
Solution Approach 1:
The patent extracts only the essential information from data by generating deltas that represent differences between current and historical data. Instead of storing complete data sets, only the critical changes (deltas) are stored, which significantly reduces storage capacity requirements while maintaining data integrity and enabling data restoration when needed.
Solution Approach 2:
The patent inverts the traditional storage approach by not storing the data itself but storing the differences (deltas) from historical data. This inversion allows the system to store minimal information that can be used to reconstruct current data from historical data, thereby reducing storage costs while maintaining data availability.
2Quantity of substance
If data storage capacity is increased to meet growing data storage demands, then storage capacity is improved, but the storage device occupies more space and consumes more power
Solution Approach 1:
The patent extracts only the essential information from data by generating deltas that represent differences between current and historical data. Instead of storing complete data sets, only the critical changes (deltas) are stored, which significantly reduces storage capacity requirements while maintaining data integrity and enabling data restoration when needed.
Solution Approach 2:
The patent changes the storage parameter from storing complete data to storing delta values (differences). This parameter change reduces the amount of data that needs to be stored and processed, thereby reducing both storage space occupation and power consumption of the storage device.
3Reliability
If complete current data is stored instead of deltas, then data integrity is improved, but storage overheads increase
Solution Approach 1:
The patent creates a virtual copy of current data by combining historical data with stored deltas during the restoration process. Instead of storing complete current data, the system stores deltas and reconstructs current data on-demand by applying these deltas to historical data, thereby maintaining data integrity while reducing storage overhead.
4Quantity of substance
If deltas are compressed to reduce storage size, then storage overheads are reduced, but compression and decompression time increase
Solution Approach 1:
The patent applies partial compression to only the delta portions of data rather than compressing entire data sets. This partial action approach reduces storage overhead for deltas while minimizing the time required for compression and decompression operations, as only the difference portions need to be processed.
Data Source
AI summary
A method for storing data includes: generating data for current data based on historical data and a change rule of the historical data; obtaining a delta between the data and the current data; storing the delta instead of the current data.