Middleware Integration Logic Programming Canonical Data Model
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Solution Overview
Problem
Existing middleware systems face challenges in efficiently integrating business applications due to differences in operating systems, database solutions, and data formats, leading to complex data format conversions and inefficient processing.
Innovation Solution
The implementation of integration logic programming using logic programming languages like DATALOG or PROLOG within middleware systems, which enables declarative description of integration semantics and relational logic data processing closer to its storage representation, leveraging parallelizable query execution through data partitioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional middleware systems perform data format conversions between different application formats and relational database formats, then integration between applications is achieved, but processing complexity and time increase significantly
Solution Approach 1:
The patent introduces a canonical data model as an intermediary representation layer between diverse application data formats and relational database formats. This canonical model serves as a standardized intermediate format that simplifies conversion operations by providing a common reference structure, thereby reducing processing time while maintaining integration capability.
Solution Approach 2:
The patent segments the data conversion process into distinct transformation stages: application format to canonical data model, and canonical data model to relational database format. This segmentation allows each transformation step to be optimized independently and enables parallel processing of multiple conversions, reducing overall processing time.
2Reliability
If middleware systems use Java Messaging Service-based solutions with relational databases for asynchronous messaging, then reliable messaging is achieved, but data format conversion complexity increases
Solution Approach 1:
The canonical data model acts as an intermediary representation that standardizes data structures before storage in the relational database. This intermediary layer simplifies the conversion complexity by providing a consistent target format for all incoming messages, while maintaining the reliability of JMS-based asynchronous messaging.
Solution Approach 2:
The patent changes the parameter representation of data by transforming diverse application-specific data formats into a standardized canonical data model with consistent parameters and structure. This parameter standardization reduces conversion complexity while preserving the reliability of the underlying messaging system.
3Productivity
If integration logic programming patterns are applied to process information in canonical data model format, then processing efficiency improves, but implementation complexity increases
Solution Approach 1:
The patent performs preliminary action by converting all incoming data to the canonical data model format before applying integration logic programming patterns. This preliminary standardization enables subsequent processing to operate on a consistent data structure, improving efficiency while containing implementation complexity in the initial conversion layer.
Solution Approach 2:
The canonical data model serves as a universal intermediate representation that can handle multiple application formats and support various integration logic programming patterns. This universality improves processing efficiency across different scenarios while reducing overall implementation complexity by reusing the same canonical structure.
Data Source
AI summary
The present disclosure describes methods, systems, and computer program products for performing integration logic programming. One computer-implemented method includes receiving, by operation of a middleware system, first information in a first format corresponding to a first application, applying, by operation of the middleware system, one or more integration logic programming (ILP) patterns to the first information, the one or more ILP patterns representing application integration semantics using a logic programming language, generating, by operation of the middleware system, a second information in response to applying the one or more ILP patterns to the first information, and outputting, by operation of the middleware system, the second information in a second format corresponding to a second application.