Hierarchical Data Snapshot Transmission for Network Synchronization
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Solution Overview
Problem
Current network data management systems face synchronization issues due to time-consuming batch data transmissions and format changes, which compromise data integrity and require frequent updates across interconnected entities in a value chain.
Innovation Solution
A data management system and method that automatically detects updates in a primary database, determines affected clients, and generates messages by modifying the hierarchical structure of data formats, enabling efficient and synchronized data transmission to affected clients.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If batch mode data transmission is used, then data can be transmitted between entities, but the transmission process is time-consuming and compromises data integrity
Solution Approach 1:
The system implements event-driven periodic action where data transmission is triggered by specific events (data changes) rather than continuous periodic transmission. The database manager monitors for changes and automatically transmits data snapshots only when changes occur, eliminating unnecessary transmission time while maintaining data integrity through event-based synchronization.
Solution Approach 2:
The data transmission is segmented into targeted data snapshots containing only changed records rather than transmitting entire datasets. The system identifies specific affected clients and sends only their relevant data portions, reducing transmission time while maintaining完整性 through selective data segmentation based on client-specific impact analysis.
2Adaptability or versatility
If data format changes occur, then data can be adapted to different client requirements, but all other entities must change their extraction processes accordingly
Solution Approach 1:
The system introduces an intermediary data snapshot format that acts as a mediator between the database and various clients. The data snapshot contains standardized metadata and structured data that can be automatically extracted by all clients without requiring changes to their extraction processes. This intermediary layer provides adaptability to different client formats while shielding clients from extraction complexity.
Solution Approach 2:
The data snapshot structure is designed with universal compatibility, containing standardized fields and metadata that serve multiple client types simultaneously. A single snapshot format can be processed by different clients with varying requirements, providing multi-functionality that maintains adaptability while reducing the need for client-specific extraction process modifications.
3Reliability
If data snapshots are transmitted frequently, then data synchronization is improved, but the time consumption and processing overhead increase
Solution Approach 1:
The system applies partial action by transmitting only the necessary portion of data (affected records) to affected clients rather than transmitting complete datasets to all clients. The workflow engine determines the minimal set of affected clients and sends targeted snapshots, achieving sufficient synchronization while minimizing processing overhead through selective partial transmission.
Data Source
AI summary
A data management method for a network. Whether a first record in a database is updated is automatically determined. Content of the first record is organized in a hierarchical structure. Which of a group of clients is affected by update of the first record is automatically determined. A data format corresponding to an affected client is automatically determined. A message is automatically generated by modifying the hierarchical structure according to the data format. The message comprising the result of modifying the hierarchical structure is automatically transmitted to the affected client.