Heterogeneous Indicia Engine for Transaction Integrity
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Solution Overview
Problem
Current computing systems face challenges in detecting and preventing computational errors caused by hardware, firmware, or software faults, as well as malware infections, which can lead to data integrity issues and application faults, especially in transaction processing systems, where errors may go undetected for an extended period.
Innovation Solution
The implementation of a Heterogeneous Indicia Engine (HIE) system, where multiple computing subsystems of different manufacture process transactions and compare indicia to detect mismatches, allowing only valid transactions to be committed and enabling self-diagnostic tests to identify faulty systems, thereby ensuring data integrity and detecting malicious or erroneous operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple computing subsystems process transactions and compare indicia to detect errors, then transaction integrity and error detection capability are improved, but system complexity increases due to the need for coordination and comparison mechanisms
Solution Approach 1:
The system divides transaction processing into multiple independent computing subsystems, each capable of autonomously processing transactions and generating indicia. This segmentation allows parallel processing while maintaining individual accountability for error detection through indicia comparison.
Solution Approach 2:
The system implements a feedback mechanism where indicia generated by each subsystem are compared against each other, and the results of this comparison feed back into the transaction commit decision. This closed-loop feedback ensures that only transactions verified by all subsystems are committed, enhancing reliability through continuous verification.
2Reliability
If indicia comparison is performed before transaction commit, then data integrity is ensured, but processing time increases due to the verification step
Solution Approach 1:
The system performs indicia generation and comparison as preliminary actions before the actual transaction commit. By preparing verification data in advance and comparing indicia before commitment, the system ensures that integrity checks are completed proactively, preventing faulty transactions from being committed while maintaining a clear separation between verification and execution phases.
3Reliability
If self-diagnostic tests are implemented to identify faulty subsystems, then system reliability is improved through fault detection, but device complexity increases due to additional diagnostic components
Solution Approach 1:
Each computing subsystem is equipped with self-diagnostic capabilities that allow it to autonomously test its own functionality and generate health status information. This self-service approach to fault detection eliminates the need for external diagnostic equipment, reducing overall system complexity while maintaining comprehensive fault detection capability.
Data Source
AI summary
A method is provided to verify the computational results of a transaction processing system that includes a parent node a plurality of child nodes. The parent node sends to at least two child nodes an identical request to process a transaction. The transaction is allowed to modify an application's state only if the validity of the result of the processing of the transaction is verified across participating child nodes. Otherwise, the transaction is aborted.