Data Processor Value Index Prioritization

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Solution Overview

Problem

Existing data processing technologies do not effectively maximize data value and efficiently utilize resources, as they lack a systematic approach to prioritizing data samples based on their value and utilization forms, leading to inefficient resource allocation.

Innovation Solution

A data processor and method that utilize a table management unit to define value indexes for data samples based on their type and usage attributes, allowing for flexible prioritization of data transfer and maintenance, thereby optimizing resource usage.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If data processing uses a limited resource without defining data value, then resource utilization rate can be optimized, but valuable data is likely to be excluded as a target to be transferred or saved

Engineering Contradiction:

Improveresource utilization rateVSAvoidvaluable data exclusion

Core Design Contradiction:

ProductivityVSLoss of information

Solution Approach 1:

The patent introduces a value index parameter that dynamically changes based on data type, usage attribute information, and state information. This parameter enables the system to differentiate and prioritize valuable data samples, ensuring they are not excluded during resource-constrained operations while maintaining optimized resource utilization.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent replaces simple resource-based prioritization with a sophisticated evaluation mechanism that uses a value index derived from multiple factors (data type, usage attributes, state information). This substitution allows the system to make intelligent decisions about data prioritization without compromising resource efficiency.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

2Device complexity

If data priorities are not defined appropriately, then resource allocation is simple, but data value is not maximized

Engineering Contradiction:

Improvepriority definition complexityVSAvoiddata value

Core Design Contradiction:

Device complexityVSLoss of information

Solution Approach 1:

The patent employs multiple parameters (data type, usage attribute information, state information) that dynamically change to determine the value index. This multi-parameter approach enables sophisticated data prioritization while maintaining a systematic and manageable complexity through the use of a structured evaluation framework.

Inventive Principle:

Principle #35Parameter changes

Solution Approach 2:

The patent segments the data prioritization process into distinct components: data type identification, usage attribute information extraction, state information assessment, and value index calculation. This segmentation makes the complex priority definition process more manageable and systematic.

Inventive Principle:

Principle #1Segmentation

Data Source

PatentUS11341111B2Data processor and data processing method

Publication Date: 2022.05.24 DENSO CORP

AI summary

A data processor for transferring or maintaining a data sample, includes: a table management unit that manages a data value table that relates a data type of the data sample, usage attribute information defined by a pair of at least one attribute type and a value concerning a utilization form, and information for defining a value index; and a prioritizing unit that defines the value index for the data sample based on the data value table, the value index belonging to a specific data type and associated with the usage attribute information, and sets a priority of the transferring or the maintaining of the data sample using the value index.