Heterogeneous Indicia Engine for Transactional 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 malicious modifications or malware infections, which can lead to data integrity issues and system failures, especially in transaction processing systems.
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 ensuring data integrity without the need for a Logical Synchronization Unit (LSU).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a Logical Synchronization Unit (LSU) is used to compare outputs of redundant subsystems, then transactional integrity is ensured, but the system has a single point of failure and reduced reliability
Solution Approach 1:
The patent removes the Logical Synchronization Unit (LSU) from the system architecture. Instead of using a centralized LSU to compare outputs, each subsystem independently compares its own output with received outputs from other subsystems. This extraction of the LSU eliminates the single point of failure while maintaining transactional integrity through distributed comparison mechanisms.
Solution Approach 2:
The patent divides the centralized output comparison function into distributed segments across multiple subsystems. Each subsystem performs its own output comparison independently rather than relying on a single centralized unit. This segmentation distributes the reliability burden across multiple independent components, eliminating the single point of failure.
2Reliability
If multiple redundant subsystems are used to detect computational errors, then reliability is improved, but system complexity and processing overhead increase
Solution Approach 1:
Each subsystem performs its own output comparison independently using received outputs from other subsystems, rather than relying on a centralized comparison unit. This self-service approach allows each subsystem to autonomously detect errors in its own processing, reducing the need for complex centralized control mechanisms while maintaining high reliability through distributed verification.
3Reliability
If output comparison is performed before transaction commit, then data integrity is ensured, but processing speed is reduced
Solution Approach 1:
The patent performs output comparison before the transaction commit point, ensuring that integrity verification is completed in advance. By using heterogeneous subsystems with different manufacturing origins, the system achieves reliable error detection without significantly impacting processing speed, as the comparison operates in parallel with transaction processing rather than sequentially blocking it.
Data Source
AI summary
A system is configured to ensure transactional integrity thereof. The system includes a first subsystem and a second subsystem. Each of the subsystems receive the same request to process a transaction. An indicia engine at each subsystem computes indicia of the outcome of the processing of the same request. The computed indicia from each of the subsystems is compared. An action is completed at one of the subsystems when the computed indicia does not match. The action completed at one of the subsystems is one or more of issuing a database rollback on one of the subsystems, executing self-diagnostics on one of the subsystems, shutting down one of the subsystems, taking one of the subsystems offline, aborting the transaction executing on one of the subsystems, and generating an error indication for one of the subsystems.