Endpoint Agent Schema Mapping for Heterogeneous Data Integration
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Solution Overview
Problem
Heterogeneous computing systems with non-compatible schemas face difficulties in data sharing and integration due to the need for manual correlation between disparate schemas, which is resource-intensive and often lacks interfaces like APIs, hindering efficient communication.
Innovation Solution
The system identifies client systems, extracts data, parses and converts it to conform to a receiving system's schema using mapping rules, and transmits the converted data, facilitating automatic integration and communication between disparate systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual correlation between disparate schemas is performed, then data integration between heterogeneous systems is achieved, but resource consumption and time cost increase significantly
Solution Approach 1:
The patent applies preliminary action by pre-defining schema mapping rules and data transformation templates before actual data integration occurs. The system establishes mapping relationships between source schemas and target schemas in advance, storing them as reusable rules that automatically guide data transformation during runtime, eliminating the need for manual correlation each time integration is needed.
Solution Approach 2:
The patent introduces an intermediary component - a schema mapping service or translation layer - that sits between heterogeneous computing systems. This intermediary automatically transforms data from source schemas to target schemas using pre-defined mapping rules, acting as a mediator that enables integration without requiring manual intervention or direct compatibility between source and target systems.
2Adaptability or versatility
If heterogeneous computing systems with non-compatible schemas are integrated, then system versatility increases, but system complexity increases
Solution Approach 1:
The patent uses an intermediary schema mapping service that abstracts the complexity of heterogeneous system integration. This intermediary handles all schema translation and data transformation automatically, allowing the system to support multiple diverse schemas without increasing the complexity of individual computing systems. The intermediary layer isolates complexity from the core systems while enabling broad adaptability.
Solution Approach 2:
The patent implements a universal schema mapping framework that can handle multiple different schemas through a single standardized interface. The system defines a target schema that serves as a common denominator, and mapping rules are created from various source schemas to this universal target schema, enabling one system to integrate with multiple heterogeneous systems without requiring custom integration logic for each.
3Manufacturing precision
If data is extracted and converted according to client system identity, then data accuracy and compatibility improve, but processing time and computational resources increase
Solution Approach 1:
The patent applies preliminary action by pre-compiling and caching schema mapping rules and transformation logic before data conversion is needed. The system analyzes source schemas and generates optimized transformation rules in advance, storing them for rapid retrieval during data extraction. This preliminary preparation ensures accurate conversion while reducing runtime processing overhead, balancing precision with productivity.
4Adaptability or versatility
If mapping rules are executed to modify data syntax, then data compatibility with receiving system improves, but processing overhead increases
Solution Approach 1:
The patent applies local quality by executing schema mapping rules selectively rather than uniformly transforming all data. The system identifies which specific data elements require conversion based on the source schema type and applies only the necessary transformation rules to those elements. This localized approach ensures compatibility where needed while minimizing unnecessary processing and energy consumption for data that already conforms or doesn't require transformation.
Data Source
AI summary
A method for integrating heterogeneous computing systems including identifying, by an endpoint system agent operating on a client device, a read/write operation associated with the client device based on monitoring an operation of a program executed on the client device, extracting, by the endpoint system agent from at least one of the client device or a client system in communication with the client device, data having a first syntax associated with the client system, receiving, by the endpoint system agent from an endpoint system, one or more rules describing a mapping between the first syntax and a second syntax associated with the endpoint system, executing, by the endpoint system agent, the one or more rules to modify the data to conform to the second syntax to produce mapped data, and transmitting, by the endpoint system agent, the mapped data to the endpoint system.