Selective Data Compression in Storage Media for Write-Time Efficiency
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Solution Overview
Problem
Current data storage systems, particularly in solid state drives, face inefficiencies in data storage due to the high cost of semiconductor memories and the latency of magnetic disk systems, which can be exacerbated by the need for data compression and the energy consumption associated with volatile memory-based SSDs.
Innovation Solution
A method and system for selectively compressing data in non-volatile memory storage media based on a reference condition, where data is compressed if the size of the data satisfies specific criteria, such as a non-zero remainder when divided by a physical storage unit, and the compression time is within a predetermined ratio of write and read operations, using a controller with a compression/decompression block to manage data storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is compressed before storage, then storage capacity utilization is improved, but processing time and energy consumption increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting compression settings based on data characteristics. The controller evaluates data patterns and selects appropriate compression algorithms and levels, changing compression parameters adaptively to balance storage efficiency gains against processing time costs for different data types
Solution Approach 2:
The patent implements partial compression action by selectively compressing only certain data blocks or regions that meet specific criteria, rather than compressing all data uniformly. This allows the system to achieve storage capacity improvements on suitable data while avoiding unnecessary processing time expenditure on data that would not benefit from compression
2Quantity of substance
If selective compression is applied based on data size, then storage efficiency is improved, but device complexity increases
Solution Approach 1:
The patent applies segmentation by dividing incoming data into discrete blocks and evaluating each block independently against compression criteria. The controller segments the data stream, assesses each segment's compressibility, and applies compression selectively to qualifying segments, thereby achieving storage efficiency improvements through manageable, modular processing that limits controller complexity
Solution Approach 2:
The patent implements local quality by applying different compression strategies to different data regions based on their specific characteristics. Rather than using a uniform compression approach throughout, the system tailors compression application to local data properties, allowing storage efficiency optimization in compressible regions while avoiding unnecessary complexity in regions where compression would not be beneficial
Data Source
AI summary
A method of storing data in a storage media can include determining whether a size of data to be stored in the storage media satisfies a reference condition and compressing the data to provide compressed data for storage in the storage media upon determining that the size satisfies a reference condition.