Flat-Top Multi-Level Tree System for Entity Distribution
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional multi-level tree systems experience exponential broadening of bases, leading to instability, unfair distribution of entities, and practical challenges in assigning child entities, resulting in slow tree formation and disproportionate representation.
Innovation Solution
A structured relational multi-level tree system is developed, using a database to sort entities by age and assign them based on an age range tabulation data structure and level strength analysis chart, ensuring fair distribution and preventing exponential growth by constructing flat-top multi-level trees with optimal sizes and numbers, and periodically reassigning entities as they advance in age.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional multi-level tree systems use exponential broadening base logic, then the system can accommodate more entities at lower levels, but the base size becomes unmanageably large and determines maximum base limits become nearly impossible
Solution Approach 1:
The patent changes the growth parameter from exponential to linear by implementing a structured assignment system where each level has a defined maximum base limit. Instead of allowing unlimited exponential broadening, the system uses a progression ratio that limits base growth, transforming the mathematical relationship from exponential to controlled linear growth while still accommodating increasing numbers of entities across levels.
Solution Approach 2:
The patent segments the multi-level tree system into structured levels with defined base limits and progression ratios. By dividing the system into discrete levels with controlled growth parameters, it prevents the uncontrolled exponential broadening that would otherwise occur, making the base size manageable while still allowing the system to scale to accommodate more entities.
2Adaptability or versatility
If conventional multi-level tree systems allow free growth patterns, then the system is flexible in accommodating entities, but the system becomes unstable and lopsided
Solution Approach 1:
The patent implements dynamic control of tree growth through structured assignment rules that adjust based on level strength analysis. The system dynamically determines optimal base limits and progression ratios for each level, allowing flexibility in accommodating entities while maintaining stability through controlled, rule-based growth patterns rather than free-form expansion.
Solution Approach 2:
The patent uses level strength analysis as a feedback mechanism to monitor and control system growth. By continuously assessing the strength and balance of each level, the system can adjust assignment parameters to maintain stability, preventing lopsided growth patterns while still allowing adaptive expansion to accommodate new entities.
3Ease of manufacture
If conventional multi-level tree systems assign entities to fixed positions, then the assignment process is simple, but top levels are filled with minority entities that indefinitely hold their positions causing disproportionate distribution
Solution Approach 1:
The patent implements periodic reassignment of entities based on age advancement and interval indications. Instead of fixed permanent assignments, the system periodically reviews and reassigns entities to appropriate levels, ensuring that minority entities at top levels eventually progress downward and that distribution remains fair and proportional across all levels over time.
Solution Approach 2:
The patent transforms static fixed-position assignments into dynamic assignments that evolve with entity characteristics such as age. Entities can progress from top to bottom levels as they advance, creating a dynamic distribution system that maintains fairness while still providing clear assignment rules for simplicity.
4Productivity
If conventional multi-level tree systems experience exponential incremental effects, then the system can grow rapidly, but the slowing down effects occur when encountering obstacles of the next exponentially incremental effects
Solution Approach 1:
The patent changes the growth parameter from exponential to controlled linear progression by implementing structured base limits and progression ratios. This prevents the rapid exponential growth that eventually encounters obstacles and slows down, instead providing steady, predictable growth rates that maintain assignment speed without encountering the bottlenecks of exponential expansion.
Data Source
AI summary
Embodiments generally relate to structured methods and systems for effecting fair distributions to the entities in a relational multi-level tree system. An optimal number of age range interval tabulations (ARIT) may be defined corresponding to levels of an age ranges tabulation data structure of the relational multi-level tree system including a plurality of structured adjacent flat-top multi-level trees. The contributing entities are pre-sorted to form an ordered age priority sequence and assigned into a single flat-top multi-level tree or multiple adjacent flat-top multi-level trees by applying top/down or adjacent-top/down assignment in a respective age ARIT based on optimal size and measurement considerations made according to a level strength analysis chart (LSAC). The contributing entities' positions are periodically released and reassigned into a next successive higher position based on the contributing entities' age advancement. Fair distributions are accorded to the contributing entities based on their age-ordered assigned positions in the relational multi-level tree system.