Protocol-Adaptive Data Compression Using Learned Codebooks

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Solution Overview

Problem

The rapid growth of data storage demand, exceeding the capacity of physical storage devices, and the limitations imposed by data compression methods, particularly with the increasing presence of multimedia data, lead to a need for efficient data encoding solutions that can adapt to various protocols.

Innovation Solution

A system and method for data compression with protocol adaptation, utilizing a codebook generator that leverages machine/deep learning algorithms to generate a protocol appendix and codebook, enabling efficient encoding and decoding with protocol formatting during the decoding process.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If data compression is applied to increase storage capacity, then storage efficiency improves, but the compression ratio decreases substantially for multimedia data

Engineering Contradiction:

Improvestorage capacityVSAvoidcompression ratio

Core Design Contradiction:

Quantity of substanceVSProductivity

Solution Approach 1:

The patent transforms the data representation parameters by converting raw multimedia data into encoded form using learned codebooks, changing the fundamental parameters of data storage from raw bytes to compressed symbolic representations that achieve higher compression ratios

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces traditional mechanical compression algorithms with machine learning-based encoding systems that automatically learn optimal compression strategies from training data, enabling adaptive compression that maintains high ratios for multimedia content

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Adaptability or versatility

If protocol conversion is added to the decoding process, then interoperability improves, but system complexity increases

Engineering Contradiction:

ImproveinteroperabilityVSAvoidsystem complexity

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent merges the protocol conversion function with the decoding process by integrating protocol-specific manipulation rules directly into the decoding pipeline, allowing a single system to perform both decoding and protocol adaptation without requiring separate conversion components

Inventive Principle:

Principle #5Merging (Combining)

Solution Approach 2:

The patent creates a universal decoding framework that can handle multiple protocols by incorporating protocol-specific manipulation rules, enabling the same decoder to adapt to different communication protocols without requiring protocol-specific decoder instances

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS12218696B2Data compression with protocol adaptation

Publication Date: 2025.02.04 ATOMBEAM TECH INC

AI summary

A system and method for data compression with protocol adaptation, that utilizes a codebook generator which leverages one or more machine/deep learning algorithms trained on at least a plurality of protocol policies in order to generate a protocol appendix and codebook, wherein original data is encoded by an encoder according to the codebook and sent to a decoder, but instead of just decoding the data according to the codebook to reconstruct the original data, data manipulation rules such as mapping and transformation are applied at the decoding stage to transform the decoded data into protocol formatted data.