Preloaded Data Prefix Compression for Small-Packet Bandwidth Overhead
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data compression methods face inefficiencies in compressing smaller data sizes, particularly due to overhead costs associated with fetching prefixes and Huffman tables, which can erode compression gains and increase bandwidth utilization.
Innovation Solution
A system and method that preloads predefined prefixes and Huffman tables within a compression engine, allowing selection based on data analysis to minimize overhead, using neural networks for prefix selection and generating Huffman tables based on actual frequencies for optimal compression ratios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If external prefix fetching is used for data compression, then compression flexibility is improved, but bandwidth utilization deteriorates due to overhead costs
Solution Approach 1:
The patent preloads prefixes and Huffman tables into the compression engine before compression operations begin. This preliminary action stores frequently used compression resources in local memory, eliminating the need for repeated external fetching during compression operations and reducing bandwidth overhead
Solution Approach 2:
The patent introduces an intermediary layer (local memory/cache within the compression engine) between the external storage and the compression algorithm. This intermediary stores prefixes and Huffman tables locally, allowing fast access without repeatedly accessing external storage, thus reducing bandwidth utilization while maintaining compression flexibility
2Device complexity
If traditional compression methods are used for smaller data sizes, then processing simplicity is improved, but compression ratio deteriorates due to overhead costs
Solution Approach 1:
The patent applies different compression strategies based on data characteristics. For smaller data sizes, it uses preloaded prefixes and optimized Huffman tables that are specifically tailored for small data compression, achieving better compression ratios without significantly increasing processing complexity
Solution Approach 2:
The patent dynamically adjusts compression parameters based on data size. When processing smaller data, it selects appropriate prefixes and Huffman tables from the preloaded sets that are optimized for small data, thereby improving compression ratios while maintaining reasonable processing complexity
Data Source
AI summary
A data compression system includes a memory to store a plurality of predetermined prefixes corresponding to a plurality of classes of data. A classifying module is configured to receive data, receive a class of the data, and select a prefix to compress the data from the plurality of predetermined prefixes based on the data and the class of the data. A compressing module is configured to compress the data using the prefix. A header generating module is configured to generate a header including an indication of the prefix used to compress the data, and to output the header and the compressed data for storage or transmission. Using the prefix from the predetermined prefixes to compress the data eliminates an overhead of fetching the prefix from outside the data compression system.