Adaptive Data Compression for Memory and Bandwidth Constraints
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Solution Overview
Problem
Organizations face challenges in managing memory storage and communication bandwidth due to increasing computing resources demands, particularly in financial institutions handling large volumes of electronic transactions, which can lead to memory depletion and communication slowdowns.
Innovation Solution
Implementing a system that compresses data based on stored information by monitoring data structure sizes and applying compression parameters to reduce memory usage and communication bandwidth requirements, thereby minimizing the need for additional storage devices and reducing communication delays.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is stored in uncompressed format, then data retrieval and processing speed is improved, but memory storage capacity is depleted faster
Solution Approach 1:
The patent applies parameter changes by transitioning data between compressed and uncompressed states based on operational needs. Data is stored in compressed format to conserve memory capacity, then selectively decompressed to uncompressed format when retrieval and processing speed is required, optimizing the balance between storage efficiency and access performance
Solution Approach 2:
The system dynamically adjusts data compression levels based on current operational requirements. The patent implements adaptive compression where data structures are compressed when storage capacity is constrained and decompressed when processing speed becomes the priority, creating a dynamic response to changing system conditions
2Quantity of substance
If more memory storage resources are allocated, then data storage capacity is improved, but computing processing power is depleted
Solution Approach 1:
The patent changes the compression parameter of stored data to reduce storage capacity requirements. By maintaining data in compressed format longer and only decompressing when absolutely necessary, the system reduces the amount of memory allocation needed, thereby conserving computing processing power that would otherwise be consumed by managing larger storage resources
3Reliability
If data is transmitted in uncompressed format, then communication accuracy is improved, but communication bandwidth is depleted
Solution Approach 1:
The patent applies compression parameters to transmitted data, changing its state from uncompressed to compressed format. This reduces the bandwidth required for communication while maintaining data integrity through lossless compression algorithms that preserve all original information, ensuring communication accuracy is not compromised
4Quantity of substance
If data compression is applied, then memory storage requirements are reduced, but device complexity increases
Solution Approach 1:
The patent segments the compression system into distinct modular components: compression algorithms, decompression algorithms, and data structure management layers. This segmentation allows the complex compression functionality to be implemented in a structured, maintainable way that minimizes overall system complexity while achieving significant storage reduction
Solution Approach 2:
The compression system is designed to operate automatically without requiring complex external management. The patent implements self-managing compression where the system automatically compresses, decompresses, and manages data formats based on predefined criteria and operational needs, reducing the complexity of external control mechanisms
Data Source
AI summary
Systems, devices and methods for adaptive compression of stored information includes a memory management computing device programmed to monitor a size of a plurality of data structures stored in a data repository. The computing device compares the size of each of a plurality of data structures to a predetermined threshold. When a size of an uncompressed data structure meets the threshold, the memory management computing device calculates a value of a first compression parameter based on a value of a first parameter and a value of a second parameter of each data element of the uncompressed data structure, calculates a value of a second compression parameter based the value of the first parameter of each data element of the uncompressed data structure, generates a compressed data structure based on the value of the first compression parameter and the second compression parameter; and replaces, in the data repository, the uncompressed data structure with the compressed data structure.