Statistical Huffman Compression for Low-Overhead Data Collection
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Solution Overview
Problem
Conventional Huffman coding for data compression results in substantial overhead due to the need to store or transmit data indicative of the Huffman table, which limits memory storage and network efficiency in devices with limited resources, such as IoT devices and aircraft systems.
Innovation Solution
Storing and transmitting only the parameters (e.g., mean and standard deviation) associated with a statistical distribution instead of the entire frequency-based code, allowing devices to generate the same frequency-based code for decoding compressed data, thereby reducing storage and network overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If Huffman coding is used to compress data, then data size is reduced, but overhead increases due to transmission of encoding data
Solution Approach 1:
The patent extracts only the essential parameters (e.g., mean and standard deviation) from the complete Huffman table, separating the critical statistical information needed for code regeneration from the redundant full frequency distribution data. This allows the encoder to transmit minimal information while enabling the decoder to reconstruct the necessary coding structure.
Solution Approach 2:
The patent transforms the representation of the Huffman table from a complete frequency distribution mapping into a condensed set of statistical parameters. By changing the data structure from explicit code mappings to implicit parameter definitions, the system achieves significant reduction in encoding data size while maintaining the ability to regenerate the frequency-based code at the decoder.
2Reliability
If complete Huffman table is transmitted, then decoder can accurately decode data, but network overhead increases
Solution Approach 1:
The patent enables the decoder to generate a copy of the frequency-based code locally by providing only the essential statistical parameters. Instead of transmitting the complete code table, the system transmits parameters that allow the decoder to reconstruct an identical coding structure, achieving the same decoding capability with minimal data transmission.
3Manufacturing precision
If more encoding data is stored, then compression accuracy is maintained, but memory capacity is reduced
Solution Approach 1:
The patent extracts only the vital statistical parameters (mean and standard deviation) from the complete Huffman table, storing minimal information that is sufficient to regenerate the frequency-based code. This extraction approach maintains compression accuracy by preserving the essential characteristics of the data distribution while freeing up memory capacity.
Solution Approach 2:
The patent changes the storage representation from complete frequency mappings to compact statistical parameters. This parameter transformation maintains the ability to accurately reconstruct the coding structure while significantly reducing the memory footprint required to store the encoding information.
Data Source
AI summary
A method includes generating data at a first device. The method includes determining one or more parameters corresponding to a statistical distribution of values based on the data. The method includes encoding the data based on a frequency-based code that is based on the statistical distribution to generate compressed data. The method further includes sending the one or more parameters and the compressed data from the first device to the second device.