Hierarchical DLT Data Management for Traffic Transparency
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Solution Overview
Problem
Current systems lack a comprehensive solution for transparent, orderly, and uniform data management and storage using distributed ledger technology (DLT), particularly in traffic and industrial production contexts, where traceability and evidence security are critical, especially with increasing autonomy and mobility.
Innovation Solution
A system utilizing interoperable local DLT networks forming chronological data records, integrated into a global infrastructure with hierarchical data aggregation and backup levels, ensuring uniform timestamping and secure data availability, with hash values stored separately for efficient data management and access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If distributed ledger technology is used for data storage and management, then data transparency and traceability are improved, but system complexity increases
Solution Approach 1:
The system segments the DLT network into multiple hierarchical levels (local, regional, national, international) with different data aggregation functions. Each level processes and stores data independently, reducing the complexity burden on any single node while maintaining overall system transparency through the hierarchical structure.
Solution Approach 2:
The patent introduces intermediary components such as data aggregation layers and consensus mechanism orchestrators that mediate between individual nodes and the global ledger. These intermediaries simplify node operations by handling complex coordination tasks centrally at each hierarchical level, reducing overall system complexity while preserving DLT transparency benefits.
2Reliability
If complete data is stored in DLT networks, then data availability and traceability are improved, but storage efficiency decreases
Solution Approach 1:
The system extracts and stores only essential data elements (such as hash values, timestamps, and critical metadata) in the DLT ledger, while complete data records are stored in external databases or off-chain storage systems. This extraction approach ensures data availability and traceability through the ledger while dramatically improving storage efficiency by avoiding redundancy of complete data copies across all nodes.
Solution Approach 2:
Instead of storing complete data copies in the DLT, the system stores cryptographic hashes and references that act as verified copies. These hash values serve as immutable proof of data existence and integrity in the ledger, while the actual complete data resides in more efficient storage systems, achieving both availability and storage efficiency.
3Speed
If multiple local DLT networks are created for different regions, then data localization and access speed are improved, but interoperability complexity increases
Solution Approach 1:
The patent merges multiple local DLT networks into a unified hierarchical structure where regional, national, and international layers are combined into a single coherent system. Standardized protocols and interfaces at each hierarchical level enable seamless interoperability between local networks, allowing fast local data access while maintaining smooth cross-regional data flow without requiring complex point-to-point integration between networks.
Solution Approach 2:
The system implements universal communication protocols and data formats that enable each local DLT network to function independently for rapid local access while simultaneously participating in the broader hierarchical network. The standardized multi-functional interface allows the same protocol to handle both local transactions and cross-regional data exchange, reducing interoperability complexity.
4Productivity
If hierarchical data aggregation levels are implemented, then data management efficiency is improved, but system architecture complexity increases
Solution Approach 1:
The system segments data management operations across hierarchical levels (local, regional, national, international), with each level handling specific aggregation and processing tasks. This segmentation improves efficiency by distributing computational load and enabling parallel processing at different levels, while the modular hierarchical architecture makes the complexity manageable through clear separation of concerns and standardized inter-level interfaces.
Data Source
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AI summary
The invention relates to a method for network-based data processing of data from at least two data sources using a data aggregation domain, DAD, and a data backup domain, DSD, wherein the data sources are configured to participate in at least one distributed ledger, DL.