Temporal Data System Parallel Processing Priority
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Solution Overview
Problem
Current computer systems require excessive processing resources and time to access and process data from databases, particularly for real-time image processing, making it costly and less accurate.
Innovation Solution
The method involves transforming data into temporal data using parallel processing techniques, where pieces of temporal data are ordered based on priority, enabling faster access and processing without the need for excessive resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional database processing methods are used, then data can be stored and organized, but processing speed is slow and requires excessive processing resources
Solution Approach 1:
The patent segments data into temporal pieces with priority assignments, allowing parallel processing of multiple data segments simultaneously. This segmentation enables the system to process different priority levels concurrently, improving throughput while reducing overall processing resource requirements through efficient resource allocation across segments.
Solution Approach 2:
The system dynamically adjusts processing based on temporal priority assignments. High-priority temporal pieces are processed immediately while lower-priority pieces are deferred or processed in parallel, creating a dynamic processing system that adapts to varying data importance and system load conditions, thereby improving productivity without proportionally increasing resource consumption.
2Speed
If processing power is increased to achieve desired real-time processing, then processing speed improves, but cost increases
Solution Approach 1:
The patent applies preliminary action by assigning temporal priorities to data pieces before processing begins. This pre-organization of data with priority metadata allows the system to efficiently schedule and process high-priority items first without requiring complex real-time decision-making hardware, achieving fast processing speeds through software-based prioritization rather than hardware complexity.
3Use of energy by moving object
If image processing techniques are used to reduce processing power, then resource requirements decrease, but processing accuracy decreases
Solution Approach 1:
The system incorporates feedback mechanisms where processed temporal pieces are evaluated and used to refine subsequent processing. This feedback loop allows the system to maintain high accuracy by learning from previous processing results while continuing to use efficient parallel processing techniques, preventing the accuracy loss that would normally occur when reducing processing resources.
Data Source
AI summary
A method for processing data is provided. Data is identified by a computer system. The data is processed in parallel by the computer system using temporal transformations to form pieces of temporal data. The pieces of temporal data are placed by the computer system in an order as the pieces of temporal data are generated by the temporal transformations to form a sequence of temporal data. The order of the sequence is based on a priority of when the pieces of temporal data should be processed, enabling performing an action.