Cellular Automata File Pre-Processing for Hard-to-Compress Data
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Solution Overview
Problem
Existing file compression methods are inefficient when dealing with random strings of characters, such as SSH keys, as they require an exact match between the original and compressed files, leading to high computing power usage and limited compressibility.
Innovation Solution
A method using cellular automata pre-processing to create an intermediary file that is more easily compressible, involving the identification of an optimal binary mask and its encoding to facilitate compression and decompression with standard algorithms.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If standard compression algorithms are used on random strings of characters, then the compression process is simple to implement, but the compression efficiency is poor and computing power is wasted
Solution Approach 1:
The patent applies preliminary action by performing cellular automata pre-processing on the original file before compression. This transforms the file into an intermediary format that is more compressible, allowing standard compression algorithms to achieve better results without requiring complex custom compression logic.
Solution Approach 2:
The patent introduces an intermediary file as a mediator between the original file and the compressed output. The cellular automata process creates this intermediary representation that preserves all information while being more amenable to compression, effectively bridging the gap between arbitrary input data and efficient compression formats.
2Productivity
If cellular automata methods are used to achieve better compression ratios, then compression efficiency improves, but the device complexity and computing power requirements increase significantly
Solution Approach 1:
The cellular automata pre-processing is performed once as a preliminary step before standard compression. This preliminary transformation creates a more compressible representation that subsequent standard algorithms can efficiently handle, avoiding the need for complex iterative optimization during the main compression phase.
Solution Approach 2:
The patent uses cellular automata to create a copied representation of the original data in an intermediary format. This copy contains all the information needed to reconstruct the original file but is structured in a way that is more suitable for compression, allowing standard algorithms to work more effectively.
3Productivity
If cellular automata pre-processing is applied to create an intermediary file, then compressibility of random data improves, but the overall processing time increases due to additional steps
Solution Approach 1:
The cellular automata transformation is performed as a preliminary step that quickly converts the original data into a more compressible format. Once this transformation is done, standard compression algorithms can proceed efficiently, and the decompression process is also accelerated because standard algorithms can work directly on the intermediary representation.
Data Source
AI summary
A method for pre-processing files that can improve file compression rates of existing general-purpose lossless file compression algorithms, particularly for files on which traditional algorithms perform poorly. The elementary cellular automata (CA) pre-processing technique involves finding an optimal CA state that can be used to transform an original file into a format (i.e., an intermediary file) that is more amenable to compression than the original file format. This technique is applicable to multiple file types and may be used to enhance multiple compression algorithms. Evaluation on generated files, as well as samples selected from online text repositories, finds that the CA pre-processing technique improves compression rates by up to 4% and shows promising results for assisting in compressing data that typically induce worst-case behavior in standard compression algorithms.