Dynamic Resource Competition Threshold Adjustment
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Solution Overview
Problem
Existing resource competition systems face challenges in setting an optimal threshold, leading to either excessive filtering or inadequate filtering of competitors, resulting in inefficient use of resources.
Innovation Solution
A method and apparatus for dynamically adjusting the resource competition threshold by processing circuitry, which obtains competition data over multiple time periods, calculates optimal thresholds, and updates the threshold based on differences, ensuring adaptive and real-time optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the threshold is set to an excessively high value, then the filtering of competitors is improved, but the number of admitted competitors becomes less than the number of available resources, leading to inefficient resource use
Solution Approach 1:
The patent implements dynamic threshold adjustment by continuously monitoring competition data and adapting the threshold value in real-time. Instead of using a fixed high threshold, the system dynamically modifies the threshold based on current competition intensity and resource availability, ensuring both precise filtering and efficient resource utilization.
Solution Approach 2:
The system changes the threshold parameter based on observed competition patterns and resource utilization metrics. By adjusting the threshold parameter dynamically rather than keeping it fixed, the system resolves the contradiction between maintaining high filtering precision and ensuring adequate resource utilization.
2Quantity of substance
If the threshold is set to an excessively low value, then more competitors are admitted to participate in resource competition, but the filtering of competitors becomes ineffective
Solution Approach 1:
The system dynamically adjusts the threshold based on real-time competition data, allowing the threshold to be low when needed to admit more competitors while maintaining high filtering precision through continuous adaptation. The dynamic nature enables the system to respond to changing conditions rather than being constrained by a fixed low threshold.
Solution Approach 2:
The system incorporates feedback mechanisms that monitor competition outcomes and resource utilization, using this information to continuously refine the threshold value. This feedback loop ensures that the threshold remains optimized to balance competitor admission with effective filtering, preventing both excessive exclusion and inadequate filtering.
3Ease of operation
If a fixed threshold is used for resource competition, then the system operation is simple, but the system cannot adapt to changing competition conditions, leading to suboptimal resource allocation
Solution Approach 1:
The system performs self-adjustment of the threshold by automatically analyzing competition data and modifying the threshold value without external intervention. This self-service capability maintains operational simplicity while achieving high adaptability, as the system autonomously responds to changing conditions.
Solution Approach 2:
The patent transforms the static fixed threshold into a dynamic adaptive threshold that automatically adjusts to competition conditions. This dynamic approach preserves ease of operation while dramatically improving adaptability, as the system automatically responds to changing environments without requiring complex manual configuration.
Data Source
AI summary
A method of adjusting a resource competition threshold for qualifying resource competition participants in resource competition is described. Processing circuitry of an apparatus obtains first competition data associated with a first time period, obtains a first optimal threshold according to the first competition data, and set the resource competition threshold according to the first optimal threshold. The processing circuitry obtains second competition data associated with a second time period, and obtains a second optimal threshold according to the second competition data. When a difference between the second optimal threshold and the resource competition threshold is greater than a difference threshold, the processing circuitry obtains third competition data and updates the resource competition threshold according to the third competition data.