Microdata Movers Using Quantum Segmentation for Large Data Transfer
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Solution Overview
Problem
The traditional methods of moving large and unstructured data are becoming inefficient due to the increasing size and complexity of data, necessitating a more effective and efficient approach to manage and structure data for seamless movement.
Innovation Solution
Utilizing quantum computing and artificial intelligence to segment and stream data into manageable packets, leveraging quantum entanglement for simultaneous processing and movement across multiple locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional methods are used to move large and unstructured data, then data can be transferred, but the efficiency decreases and processing power requirements increase
Solution Approach 1:
The patent segments large unstructured data into small structured microdata packets using quantum computing processors. Each microdata packet is independently structured and can be processed efficiently, transforming one large difficult-to-move data set into many small easily-movable packets that can be parallelized across multiple locations.
Solution Approach 2:
The patent introduces quantum computing as a new dimensional capability that enables simultaneous processing and movement of data packets across multiple locations. This adds a temporal and spatial dimension to data transfer, allowing parallel operations that traditional sequential methods cannot achieve.
2Reliability
If data is moved in large unstructured volumes, then complete data transfer is achieved, but the complexity of managing and structuring data increases
Solution Approach 1:
The patent divides large unstructured data into structured microdata packets, where each packet contains organized information with defined schemas. This segmentation reduces management complexity while maintaining complete data transfer, as each packet can be independently tracked, routed, and verified.
Solution Approach 2:
The patent changes the structural parameters of data by imposing schemas on microdata packets during the segmentation process. This transformation from unstructured to structured format at the packet level simplifies management and tracking while ensuring data completeness through systematic organization.
3Speed
If quantum computing is used to process and move data in microquantities, then transfer speed and efficiency are maintained, but the system complexity increases
Solution Approach 1:
The patent uses quantum computing processors to segment data into micro packets and leverage quantum entanglement to enable simultaneous processing and movement across multiple locations. This maintains high transfer speeds through parallel quantum operations while managing complexity through structured packet protocols.
Solution Approach 2:
The patent introduces structured microdata packets as intermediary objects between quantum processing operations and traditional data storage systems. These packets serve as a bridge that translates quantum processing capabilities into usable data structures, managing the complexity interface between quantum and classical systems.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables efficient data transfer and processing without additional cost or speed reduction, allowing data to be classified, sorted, and stored efficiently across multiple locations using quantum computing processors and AI.
Implementation Method 1
leveraging quantum entanglement for simultaneous processing and movement across multiple locations
Data Source
AI summary
Methods and apparatus for using quantum computing processors to execute microdata factories and microdata movers. The methods and apparatus may include receiving a dataset at an entity computing system. The methods and apparatus may include segmenting the dataset into a plurality of data segments using an artificial intelligence (“AI”) model. The methods and apparatus may include leveraging, via quantum entanglement, each of the plurality of data segments at one or more jump point stations. The methods and apparatus may include executing a plurality of microdata movers. Each of the plurality of microdata movers may move each of the plurality of data segments. The methods and apparatus may include executing a plurality of microdata factories. Each of the plurality of microdata factories may sort each of the plurality of data segments.