Compression Algorithm Selection Based on Storage Resources
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Traditional data storage systems often employ a single compression algorithm, leading to suboptimal results in terms of compute time and compression ratio, as different algorithms are better suited for various applications and data types, and they fail to dynamically adjust to changing system resources and data activity levels.
Innovation Solution
A method and system that evaluates system resources and data activity levels to select an optimal compression algorithm for data storage, allowing for dynamic adjustment of compression algorithms based on available resources and data characteristics, enabling efficient storage and retrieval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a single compression algorithm is used in traditional data storage systems, then the system structure is simple and ease of operation is maintained, but storage efficiency is suboptimal and resource utilization is poor
Solution Approach 1:
The system dynamically selects compression algorithms based on real-time evaluation of system resources and data characteristics. The compression algorithm is not fixed but adapts to changing conditions, allowing the system to optimize storage efficiency while managing complexity through automated resource-based selection
Solution Approach 2:
The system changes the parameter of compression algorithm selection based on system resources and data activity levels. By evaluating resources such as CPU availability, memory, and storage capacity, the system selects appropriate compression algorithms to optimize storage efficiency without excessive complexity
2Productivity
If multiple compression algorithms are selected based on system resources, then storage efficiency and resource utilization are optimized, but compute time and system complexity increase
Solution Approach 1:
The system performs preliminary evaluation of system resources and data characteristics before selecting a compression algorithm. This advance assessment allows the system to choose the most appropriate algorithm without excessive compute time during actual compression operations
Solution Approach 2:
The system autonomously evaluates its own resources and selects compression algorithms without external intervention. This self-service approach optimizes storage efficiency while minimizing the time lost to manual configuration or complex decision-making processes
Data Source
AI summary
Example embodiments of the present invention relate to methods, systems, and a computer program product for storing data compressed according to available system resources. The method includes evaluating system resources of a data storage system and selecting a compression algorithm according to the system resources. The data set then may be compressed according to the selected compression algorithm and the compressed data stored in the data storage system.