Computational Storage Data Transformation for Processing Efficiency
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Solution Overview
Problem
The rapid increase in data generation and storage has outpaced the computational abilities of computing systems to process massive data stores, leading to inefficiencies in data management and processing, particularly in bridging the divide between data and computing elements.
Innovation Solution
A system comprising a computing device with a data-side processor integrated into the data store, connected via a bus, that receives inputs from remote devices to configure and apply data transformations, such as sampling, obfuscation, or nullification, before outputting transformed data to downstream processors, allowing for fine-grained control and efficient data management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data is stored in large quantities in computational storage or memory, then data availability increases, but data processing efficiency deteriorates due to the vastness of data stores
Solution Approach 1:
The patent applies preliminary action by performing data transformations (sampling, obfuscation, nullification) at the data store level before data is requested by computational entities. This pre-processing reduces the data volume that needs to be transferred and processed downstream, thereby improving processing efficiency while maintaining data availability.
Solution Approach 2:
The patent introduces an intermediary transformation layer between the data store and computational entities. This intermediary applies configurable transformations to data based on remote inputs, acting as a mediator that reduces data volume and enhances security before data reaches downstream processors.
2Measurement precision
If fine-grained control over data access is implemented at sub-data-record level, then data management precision improves, but system complexity increases
Solution Approach 1:
The patent implements self-service by enabling the data store system to autonomously apply transformations to data based on configurable parameters received from remote devices. The system automatically determines which transformations to apply (sampling, obfuscation, nullification) without requiring complex manual configuration, thereby achieving fine-grained control while managing system complexity.
3Productivity
If data transformations are applied at the data store level, then data processing efficiency improves by reducing data volume, but data security requirements increase
Solution Approach 1:
The patent applies parameter changes by transforming data parameters (applying sampling rates, obfuscation levels, nullification thresholds) at the data store level. These parameter-based transformations reduce data volume for efficient processing while maintaining configurable security levels, allowing the system to balance efficiency and security through adjustable transformation parameters.
Data Source
AI summary
Provided is a system, comprising: a computing device, comprising: computational storage or computational memory, the computational storage or computational memory having a processor; a downstream data processor that is different from the processor of the computational storage or computational memory; and a bus connecting the processor to the computational storage or computational memory, wherein the computing device comprises a tangible, non-transitory, machine readable medium storing instructions that, when executed, effectuate operations comprising: receiving an input from a remote device conveyed to the computing device; determining, based on the input, how to configure a transformation of data stored in the computational storage or computational memory; and applying, with the processor, the configured transformation to the data stored in the computational storage or computational memory; and outputting the transformed data to the downstream data processor.