Asymmetric Data Encoding for Secure Compaction and Fast Search
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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 transmission bandwidth are causing a bottleneck in data management, particularly with the increasing use of multimedia data.
Innovation Solution
A system and method for highly efficient data encoding that incorporates asymmetric encoding/decoding and distributed computing policy enforcement, allowing for double security through data manipulation rules and enabling efficient data transmission and storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data compression is used to increase storage capacity, then storage efficiency is improved, but data retrieval speed and search capability deteriorate
Solution Approach 1:
The patent segments data into fixed-size blocks and creates multiple indexes for different retrieval needs. This allows the system to maintain compressed storage while enabling fast retrieval by directing searches to specific blocks through indexes, avoiding the need to decompress entire datasets for search operations.
Solution Approach 2:
The patent performs preliminary organization of data into standardized blocks and pre-computes multiple indexes during data ingestion. This preliminary action enables rapid retrieval operations later without requiring real-time compression/decompression, resolving the contradiction between storage efficiency and retrieval speed.
2Quantity of substance
If physical storage capacity is increased to meet demand, then storage availability is improved, but cost and resource utilization worsen
Solution Approach 1:
The patent merges multiple data blocks that share common characteristics into compacted datasets. By combining redundant or similar data representations, the system achieves higher storage density and reduces the total physical storage capacity needed, thereby improving resource utilization without sacrificing storage availability.
Solution Approach 2:
The patent changes the representation parameters of data by applying various compaction algorithms that transform data into more space-efficient formats. This parameter transformation allows the same logical storage capacity to be achieved with fewer physical resources, reducing energy consumption and improving resource utilization.
3Speed
If transmission bandwidth is increased to handle large datasets, then data transmission speed is improved, but infrastructure cost and complexity worsen
Solution Approach 1:
The patent extracts only the essential data blocks needed for specific operations and transmits them separately, rather than transmitting entire large datasets. This extraction approach reduces transmission bandwidth requirements and infrastructure complexity while maintaining data transmission speed for critical operations.
Solution Approach 2:
The patent performs preliminary compaction and organization of data into optimized blocks before transmission. This preliminary processing reduces the overall data volume that needs to be transmitted, thereby lowering bandwidth requirements and infrastructure complexity while preserving transmission speed for the compressed data.
4Quantity of substance
If data is stored in compacted form to save space, then storage efficiency is improved, but data security and access control worsen
Solution Approach 1:
The patent applies different security and access control mechanisms to different data blocks based on their sensitivity and access requirements. This local differentiation allows the system to maintain high storage efficiency through compaction while implementing appropriate security measures only where needed, rather than applying uniform security protocols to all compacted data.
Solution Approach 2:
The patent segments data into blocks with different security classifications and applies targeted access controls to each segment. This segmentation enables the system to maintain storage efficiency through compaction while preserving data security by enforcing access policies at the block level, allowing authorized users to access specific compacted blocks without compromising overall security.
Data Source
AI summary
A system and method for highly efficient encoding of data that includes extended functionality for asymmetric encoding/decoding and network policy enforcement. In the case of asymmetric encoding/decoding the original data is encoded by an encoder according to a codebook and sent to a decoder, but the output of the decoder depends on data manipulation rules applied at the decoding stage to transform the decoded data into a different data set from the original data. In the case of network policy enforcement, a behavior appendix into the codebook, such that the encoder and/or decoder at each node of the network comply with network behavioral rules, limits, and policies during encoding and decoding.