Referential Data Structures for Real-Time Asset Attribute Updates
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Solution Overview
Problem
Existing systems fail to efficiently and automatically update asset attributes in real-time based on streaming data, leading to inefficiencies in market value determination and trading processes, particularly in fungible assets across multiple baskets.
Innovation Solution
A server-connected database system with referential data structures that automatically update fungible asset attributes in real-time by modifying fields based on streaming data, allowing for cycling, liquidating, and replenishing of assets while maintaining relative value equivalence, and incorporating features like Sharia compliance and secure transaction validation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual updating of asset attributes is used, then system complexity is reduced, but real-time update capability is lost
Solution Approach 1:
The system enables self-service through referential data structures that automatically update asset attributes when underlying fields change. The referential relationship between the first data structure (storing asset attributes) and second data structure (storing source fields) creates an automatic update mechanism that eliminates manual intervention while maintaining system reliability.
Solution Approach 2:
The referential data structure acts as an intermediary between the source data fields and the asset attributes. This intermediary layer establishes a referential relationship that automatically propagates changes from the second data structure to the first data structure, enabling real-time updates without direct manual intervention.
2Productivity
If real-time automatic updating is implemented, then trading efficiency is improved, but data structure complexity increases
Solution Approach 1:
The system segments data storage into two distinct data structures: the first data structure stores asset attributes that determine market values, while the second data structure stores the source fields. This segmentation allows independent management of each structure while maintaining referential relationships, improving trading efficiency through automated updates.
Solution Approach 2:
The invention adds a referential dimension to the data structure design. By establishing referential relationships between fields in the second data structure and attributes in the first data structure, the system creates a multi-dimensional data organization that enables automatic propagation of changes across different data layers.
3Speed
If referential data structures are used for automatic updates, then update speed is improved, but system complexity increases
Solution Approach 1:
The referential data structures enable self-service updating where changes in the second data structure automatically propagate to the first data structure through established referential relationships. This self-service mechanism accelerates update speed by eliminating manual intervention while the modular referential design keeps system complexity manageable.
Data Source
AI summary
A server connected to a network generates a database including a first data structure configured to store attributes of fungible assets, where the attributes determine market values of the fungible assets, and a second data structure having fields referentially related to the attributes stored in the first data structure such that a change in any one of the fields induces a change in real time in a corresponding attribute in the first data structure. The server receives a stream of data regarding one or more of the attributes of the fungible assets from the network, which modifies one or more of the fields of the second data structure, and which allows at least one of cycling, liquidating, and replenishing of one or more of the fungible assets while maintaining a relative value equivalence of the fungible assets. The server securely validate, verify, record, trace, and track transactions for cryptocurrency specimens.