Intermediary Server for Heterogeneous Data Translation
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Solution Overview
Problem
Current systems fail to efficiently manage and process federated data from heterogeneous services and systems in real time due to the complexity and diversity of systems hosting business applications, such as RDBMS, OODBMS, and Web-based services, leading to impractical manual operations and inability to create consistent datasets.
Innovation Solution
An implementation system featuring a server with an intermediation module and a mapper module that acts as an intermediary between application and service servers, transforming and processing service-related data in real time, using APIs and rule engines to handle queries and data translation across different systems without requiring native data conversion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual data retrieval and translation operations are used to query services across heterogeneous systems, then data can be accessed from multiple sources, but the processing cannot be performed in real time and the system becomes impractical
Solution Approach 1:
The patent introduces an intermediary system that sits between the application and heterogeneous data sources (RDBMS, OODBMS, Web services). This intermediary automatically retrieves data from multiple sources, translates different data formats into a unified structure, and delivers results in real-time without requiring manual intervention. The intermediary handles the complexity of cross-system communication and data translation transparently, enabling real-time processing while maintaining adaptability to diverse data sources.
2Adaptability or versatility
If standardization approaches like ESB and service-oriented architectures are implemented to enable exchanges between heterogeneous services, then flexibility and adaptability are improved, but the system complexity increases and efficiency decreases when exchange requirements are high
Solution Approach 1:
The patent extracts the complexity of data retrieval and translation operations from the application layer and consolidates it into a dedicated intermediary component. By taking out these complex operations and handling them separately in the intermediary, the main application remains simple while still benefiting from access to heterogeneous data sources. This extraction approach reduces overall system complexity while maintaining the ability to handle high exchange requirements efficiently.
3Adaptability or versatility
If data from heterogeneous systems is retrieved and translated manually to create a consistent dataset, then data integration is achieved, but the operation is time-consuming and cannot be performed in real time
Solution Approach 1:
The patent implements preliminary action by having the intermediary system pre-establish connection protocols and translation rules for various heterogeneous data sources. When data retrieval is needed, the intermediary already has the necessary translation mappings and communication patterns prepared in advance, enabling immediate data extraction and transformation without time-consuming setup or manual configuration. This preliminary preparation allows real-time data integration from diverse sources.
Data Source
AI summary
The system comprises a man-machine interface for controlling the application, a server running the application, a server hosting the service and a server for automatically calling the service, including memory resources containing the data describing the service, receive the data related to the service and transform that data so that it can be processed in the application server, all of which under the control of the man-machine interface and the application server.