Adaptive Data Compression for Memory and Bandwidth Limits
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Solution Overview
Problem
Organizations face challenges in managing memory storage and communication bandwidth due to increasing computing demands, often constrained by aging hardware and software resources, leading to depleted resources and communication delays, especially in high-traffic scenarios like financial trading systems.
Innovation Solution
Implementing a memory management system that actively monitors and compresses data structures by calculating compression parameters based on the size of data elements, reducing 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
1Reliability
If data is stored in uncompressed format to maintain data integrity and accessibility, then data quality and retrieval speed are improved, but memory storage capacity is depleted faster
Solution Approach 1:
The patent applies parameter changes by transitioning data from an uncompressed state to a compressed state, altering the storage density parameter. The system dynamically adjusts compression levels based on data access patterns, allowing the same physical storage medium to hold more data while maintaining necessary accessibility characteristics.
Solution Approach 2:
The patent implements dynamics by making the compression state adaptive rather than static. The system continuously monitors data access patterns and dynamically adjusts the compression level, transforming the storage system from a fixed-state to a variable-state system that optimizes between storage capacity and retrieval speed based on actual usage.
2Quantity of substance
If data structures are compressed to reduce memory usage and communication bandwidth, then storage capacity and communication efficiency are improved, but data processing complexity increases
Solution Approach 1:
The patent applies self-service by implementing automated compression and decompression systems that operate without manual intervention. The system automatically monitors data structures, determines optimal compression levels, performs compression when beneficial, and handles decompression during retrieval, thereby managing the increased processing complexity through automation rather than manual processes.
Solution Approach 2:
The patent implements feedback mechanisms that monitor data access patterns, storage usage, and retrieval performance. This feedback information is used to dynamically adjust compression strategies, allowing the system to learn from actual usage and optimize the balance between memory usage and processing complexity over time.
3Quantity of substance
If compression algorithms are applied to reduce communication bandwidth requirements, then network bandwidth efficiency is improved, but communication processing time increases
Solution Approach 1:
The patent applies partial action by implementing selective compression rather than universal compression. The system identifies and compresses only those data structures that are candidates for storage or transmission, leaving frequently accessed or time-sensitive data in uncompressed form. This partial application of compression reduces overall bandwidth requirements while minimizing the processing time penalty for critical data.
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.