Time-Dependent Data Compression With Progressive Bit Removal
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Solution Overview
Problem
There is a need for an efficient and effective method to compress electronic data, particularly for datasets that are infrequently accessed, to minimize storage resources without compromising data integrity.
Innovation Solution
A system utilizing an automated time-dependent compression algorithm that progressively removes least significant bits from datasets over time, with a countdown timer triggering compression processes and intelligent reconstruction algorithms to restore data when accessed, ensuring data remains usable and preventing further compression when unrecoverable.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is compressed by removing least significant bits over time, then storage space is reduced, but data quality and recoverability deteriorate
Solution Approach 1:
The patent implements dynamic compression where the compression level adjusts over time based on data access patterns. Data that is frequently accessed is decompressed to full quality, while inactive data progressively loses bits. This dynamic approach allows the system to optimize storage space for cold data while maintaining full quality for hot data, resolving the contradiction between storage efficiency and data recoverability
Solution Approach 2:
The system changes the data representation parameters by progressively removing least significant bits based on time and access frequency. This parameter transformation allows flexible control over the trade-off between storage size and data quality, enabling the system to achieve high compression ratios for inactive data while preserving full fidelity for actively used data
2Quantity of substance
If compression is applied to all datasets, then storage resources are minimized, but data access speed and reconstruction time increase
Solution Approach 1:
The patent applies different compression qualities to different data based on their access patterns and importance. Frequently accessed data maintains full quality and is stored in uncompressed or lightly compressed form for fast access, while rarely accessed data undergoes aggressive compression. This localized quality approach ensures that data access speed is maintained for critical data while achieving storage savings for non-critical data
3Quantity of substance
If progressive bit removal is used for compression, then compression ratio improves over time, but complexity of managing compression states increases
Solution Approach 1:
The system implements self-service automation where compression and decompression operations are triggered automatically based on data access events without manual intervention. The countdown timers and event-driven architecture enable the system to autonomously manage compression states, tracking which data has been accessed and applying appropriate decompression, thereby reducing the perceived complexity for users while maintaining sophisticated compression management
Data Source
AI summary
A system is provided for electronic data compression by automated time-dependent compression algorithm. In particular, the system may track instances in which a particular dataset is used, copied, or accessed over time. For certain datasets (e.g., datasets that have not been accessed for a threshold amount of time), the system may use a time-based compression algorithm that progressively removes the least significant bits of such datasets as time passes. The compression of the datasets may continue until the system detects that further compression would cause the dataset to be unreadable or unrecoverable. In this way, the system may minimize the computing resources allocated to storing datasets that are not frequently accessed.