Event Data Validation During Communication Interruptions
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Solution Overview
Problem
Conventional event processing systems face inefficiencies due to interruptions in communication between systems or applications, leading to delays and increased computing bandwidth, as they either hold events until connectivity is restored or delete and restart processing, which requires excessive computing resources.
Innovation Solution
A computing platform that employs a decision tree to identify mandatory and optional transaction details, tokenizes data upon availability, and uses a machine learning model to format data for continued processing, ensuring data integrity and efficiency during communication disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If events are held at current application or system until connectivity is restored, then data integrity is ensured, but processing time increases and productivity decreases
Solution Approach 1:
The patent segments event data into critical and non-critical components, allowing processing to continue with critical data while connectivity is restored. This segmentation enables partial processing without waiting for complete data availability, thus maintaining productivity while ensuring data integrity through systematic data classification and prioritization.
Solution Approach 2:
The system performs preliminary actions by caching event data locally before connectivity is restored, and begins processing with available data immediately. This preliminary action eliminates the need to wait for connectivity restoration, maintaining processing speed while data integrity is ensured through subsequent validation and completion of processing once data becomes available.
2Reliability
If events are deleted and reprocessed from beginning once connectivity is restored, then data completeness is improved, but computing bandwidth consumption increases
Solution Approach 1:
The patent applies partial action by processing only the portions of events that can be completed with currently available data, rather than requiring complete reprocessing. This approach ensures data completeness for processed portions while consuming significantly less computing bandwidth compared to full reprocessing, achieving an optimal balance between reliability and resource consumption.
Solution Approach 2:
The system discards incomplete event processing states and recovers by retrieving only the specific missing data portions needed to complete processing, rather than reprocessing entire events. This selective recovery mechanism maintains data completeness while minimizing computing bandwidth consumption by focusing only on essential data retrieval and processing.
3Reliability
If conventional arrangements hold events until data is available, then data integrity is maintained, but processing delays occur
Solution Approach 1:
The system performs preliminary actions by pre-caching event data and beginning processing with available data before connectivity is fully restored. This preliminary processing eliminates idle waiting time while maintaining data integrity through subsequent validation steps, directly addressing the contradiction between reliability and time loss.
Solution Approach 2:
The patent enables continuity of useful action by allowing event processing to continue with available data rather than pausing completely. This continuous processing maintains productivity and reduces delays while data integrity is ensured through systematic validation and completion mechanisms that operate throughout the connectivity restoration process.
Data Source
AI summary
Arrangements for providing data integrity validation in event processing are provided. A computing platform may detect a communication interruption between a first and second system. The platform may identify data from the second system that cannot be retrieved. A decision tree may be used to identify transaction details for processing by a third system and the transaction may be passed to the third system for processing. When the interruption is resolved, the first system may retrieve the data from the second system, generate a token including the data and publish the token to the platform, where the third system may retrieve the token and evaluate the data for formatting. If formatting is required, a second decision tree may be used to identify a transformation to perform. Machine learning may be used to transform the data and the third system may process the transaction using the formatted data.


