Token Apportionment Stack for Multi-Tiered Data Structures
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Solution Overview
Problem
Existing networked resource distribution systems face inefficiencies in managing and tracking resource allocation across multiple tiers, leading to complex computations and potential token mismanagement.
Innovation Solution
A token apportionment stack with a multi-layered architecture that includes a data structure layer, token assignment layer, and interface interaction layer, which uses apportionment tags and certificate messages to efficiently assign and track tokens across multiple tiers, ensuring consistent resource distribution and preventing token loss through recursive assignment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If complex multi-tiered data structures are used for resource distribution, then resource allocation precision is improved, but computational complexity increases
Solution Approach 1:
The patent segments the complex multi-tiered resource distribution problem into discrete token assignment operations across hierarchical layers. Each layer (L0, L1, L2, etc.) handles token apportionment independently through standardized algorithms, breaking down the monolithic computational task into manageable segments that can be processed sequentially or in parallel, thereby reducing overall computational complexity while maintaining allocation precision.
Solution Approach 2:
The patent implements a nested hierarchical structure where token assignments at higher layers (L0) contain and govern token assignments at lower layers (L1, L2, etc.). Each layer's token pool is nested within the parent layer's allocation framework, allowing precise resource distribution through layered containment relationships. This nesting enables complex multi-tiered allocation without requiring a single monolithic computation, as each nested layer processes tokens independently within its scope.
2Stability of the object's composition
If token apportionment is performed across multiple tiers, then resource distribution consistency is improved, but system complexity increases
Solution Approach 1:
The patent performs preliminary token apportionment at each hierarchical layer before distribution to end entities. At layer L0, tokens are preliminarily allocated to L1 groups; at L1, these tokens are preliminarily allocated to L2 groups, and so on. This preliminary action at each tier ensures that consistency constraints are established early in the allocation process, propagating downward through the hierarchy and guaranteeing final distribution consistency without requiring complex post-processing verification.
Solution Approach 2:
The patent implements feedback mechanisms where each layer monitors and adjusts token assignments based on allocations at parent and child layers. The token pool at each layer provides feedback about available resources to parent layers, while allocation decisions from parent layers provide feedback constraints to child layers. This bidirectional feedback ensures consistency across all tiers by continuously coordinating allocation decisions throughout the hierarchical structure.
Data Source
AI summary
A token apportionment stack may include multiple layers. A data structure layer of the token apportionment stack may access configuration memory to determine nodes and node attributes for a multiple-tier data structure. The data structure layer may send a message to a token assignment later of the token apportionment stack that indicates the determined nodes and attributes. Responsive to the message, the token assignment layer may assign tokens to a first node and recursively assign an apportionment of the assigned tokens to a second node. The token assignment layer may send a message with the assignments to the data structure layer. An interface interaction layer of the token apportionment stack may receive and handle query regarding token assignment by accessing token assignment data stored at the data structure layer.