Message Translator Logic for Disparate System Integration
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Solution Overview
Problem
Integrating disparate processing systems in the telecommunications industry to enable efficient, robust, and fault-tolerant message communication for provisioning, execution, and maintenance of complex services is challenging due to compatibility issues and increased complexity of underlying technologies.
Innovation Solution
A message interface system with message translator logic that processes request and response messages by removing non-essential parameters from source requests, storing them temporarily, and adding them back to response messages to ensure compatibility and reduce data exchange overhead between systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If message parameters are transmitted between disparate processing systems, then message compatibility is improved, but data exchange overhead and system complexity increase
Solution Approach 1:
The patent extracts non-essential message parameters from the message stream using a message parameter map that identifies which parameters should be removed. This extraction process reduces data exchange overhead while maintaining compatibility by only transmitting essential parameters between disparate processing systems.
Solution Approach 2:
The message interface system acts as an intermediary between source and destination systems, using a message parameter map to mediate parameter transmission. This intermediary selectively removes and manages message parameters, reducing complexity while ensuring compatibility through controlled parameter exchange.
2Loss of information
If all message parameters are transmitted between systems, then complete information exchange is achieved, but communication overhead and processing time increase
Solution Approach 1:
The message parameter map identifies and extracts only the essential parameters needed for message processing, removing redundant parameters from transmission. This selective extraction maintains information completeness for essential data while reducing processing time by minimizing the volume of data that must be transmitted and handled.
Solution Approach 2:
Instead of transmitting all possible message parameters, the system applies partial action by transmitting only the subset of parameters identified as essential in the message parameter map. This partial transmission approach prevents information loss for critical parameters while avoiding the time cost of processing and transmitting excessive data.
3Productivity
If message parameters are removed to reduce overhead, then data exchange efficiency is improved, but message compatibility may be compromised
Solution Approach 1:
The message interface system serves as an intermediary that uses the message parameter map to intelligently determine which parameters to remove and which to retain. This mediator ensures that essential parameters for maintaining compatibility are preserved while non-essential parameters are removed to improve data exchange efficiency.
Solution Approach 2:
The system changes the parameter set of transmitted messages by selectively removing parameters based on the message parameter map. This parameter transformation maintains compatibility by preserving critical parameters while improving efficiency through the removal of redundant parameters, effectively adapting the message parameter set to optimal levels.
Data Source
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AI summary
A message translator helps address significant technical challenges in integrating disparate processing systems. The message translator intelligently parks and retrieves specific message parameters and allows multiple processing systems to communicate messages to one another in a way that efficiently supports provisioning, execution; and maintenance of complex products and services. Efficient, robust, and fault tolerant service request orchestration and message handling results for capable message communication between disparate systems running disparate applications.