Distributed Ledger Tolerance Range Rule for Data Linkage
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Solution Overview
Problem
Current distributed ledger systems face challenges in efficiently linking with non-distributed ledger systems without relying on a single organization, particularly in handling non-deterministic processes and ensuring data consistency across nodes, which leads to deviations and fraud risks due to variations in data acquisition timing and authority.
Innovation Solution
A data linkage management method where each node in a distributed ledger system holds a tolerance range rule for discrepancies in data from external systems, forming a consensus by tolerating these discrepancies through a pass-fail judgment, allowing for efficient data linking between distributed and non-distributed ledger systems without relying on a single organization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If distributed ledger systems link with non-distributed ledger systems without relying on a single organization, then data exchange efficiency and system independence are improved, but data consistency and reliability deteriorate due to variations in data acquisition timing and authority across nodes
Solution Approach 1:
The patent introduces a tolerance range parameter (α) that defines the acceptable deviation threshold for data acquired from external systems. Each node compares its acquired data with others, and if the difference falls within the tolerance range, consensus is achieved. This parameter-based approach allows the system to maintain reliability while enabling efficient multi-organization data exchange without requiring single-point control.
2Reliability
If strict data consistency rules are enforced across all nodes, then data reliability is improved, but system complexity and difficulty of operation worsen due to the need for centralized coordination
Solution Approach 1:
Each node in the distributed ledger system independently performs data acquisition, comparison, and consensus determination using the tolerance range rule. Nodes autonomously evaluate whether their acquired external data matches others within the acceptable range and自行 form consensus without requiring centralized coordination. This self-service mechanism reduces system complexity while maintaining data reliability through decentralized autonomous operation.
3Measurement precision
If tolerance ranges are set narrowly to ensure data precision, then measurement precision is improved, but adaptability worsens as the system becomes less flexible in handling variations from different external systems
Solution Approach 1:
The tolerance range (α) is not fixed but can be dynamically adjusted based on the type of external system, data category, and organizational agreements. This dynamic parameter allows the system to maintain high precision when needed while becoming more flexible when integrating diverse external systems. The adaptability enables the distributed ledger to accommodate variations in data acquisition timing and methods across different organizations without compromising overall data quality.
Data Source
AI summary
In a data linkage management system, at least each node of a specified plurality of organizations among a plurality of nodes holds a tolerance range rule that defines a specified tolerance range relating to discrepancies among data acquired from a specified external system, and forms a consensus that tolerates discrepancies among the data by passing a tolerance pass-fail judgment relating to discrepancies among the data according to the tolerance range rule in regards to a transaction issued by each node for the data.