Predictive Delta Data Storage for Lower Storage Overhead
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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 requirements, necessitating an efficient data storage solution.
Innovation Solution
A data storage method that predicts current data based on historical data, calculates a delta between the current and predicted data, and stores only the delta or its compressed form, using AI neural algorithms and dictionary compression techniques to reduce storage overheads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If the capacity of storage device is increased to store sharply increasing data, then the data storage capacity is improved, but the purchase costs and management costs of the storage device are relatively high
Solution Approach 1:
The patent extracts only the essential information needed to restore current data (historical data and delta values) rather than storing all raw data. By separating and storing only the critical components needed for data reconstruction, the system achieves significant space savings while maintaining data accessibility.
Solution Approach 2:
The patent transforms the storage approach by changing from storing absolute data values to storing relative differences (delta values). This parameter transformation allows the system to store data in a more compact form while preserving the ability to reconstruct original data through cumulative addition of delta values.
2Quantity of substance
If the capacity of storage device is increased to store sharply increasing data, then the data storage capacity is improved, but the storage device occupies relatively large space
Solution Approach 1:
The patent extracts and stores only the minimal necessary information (historical data points and delta values) required to reconstruct current data. This selective extraction dramatically reduces the physical space required for storage while maintaining full data accessibility through reconstruction algorithms.
Solution Approach 2:
By changing the storage parameter from absolute data values to relative delta values, the patent achieves compact representation of data. This parameter transformation enables the same amount of information to be stored in significantly less physical space.
3Quantity of substance
If the capacity of storage device is increased to store sharply increasing data, then the data storage capacity is improved, but the storage device consumes relatively high power
Solution Approach 1:
The patent changes the storage parameter from absolute values to relative delta values, which requires less energy to write and store. This parameter transformation reduces the power consumption associated with data storage operations while maintaining the ability to retrieve and reconstruct data when needed.
4Reliability
If the current data is directly stored, then the data integrity is maintained, but the storage overheads are high
Solution Approach 1:
The patent transforms data from absolute values to relative delta values, maintaining data integrity through mathematical relationships. By storing delta values that can be cumulatively added to historical data, the system preserves complete information while achieving significant storage overhead reduction.
Solution Approach 2:
Instead of storing duplicate absolute data values, the patent uses a referencing approach where historical data serves as a base and delta values serve as corrections. This copying strategy with differences maintains data fidelity while eliminating redundant storage.
Data Source
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AI summary
Embodiments of this application disclose a data storage method, a data obtaining method, and an apparatus, to reduce storage overheads. The data storage method includes: obtaining current data and historical data of the current data; predicting the current data by using the historical data, to obtain predicted data of the current data, where the predicted data of the current data is data obtained after the current data is predicted according to a change rule of the historical data; obtaining a delta between the current data and the predicted data of the current data; and when storage space occupied by the delta is smaller than storage space occupied by the current data, storing information used to restore the current data, where the information used to restore the current data includes the delta or a value obtained by compressing the delta.