Memory Checking with Count-Encoded Data for Error Detection
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Solution Overview
Problem
Existing methods for ensuring data integrity in safety-relevant computing environments, such as those in railroad applications, face challenges in reliably detecting memory errors without significant hardware expenditure and may fail to identify errors in certain constellations.
Innovation Solution
A method for encoding and decoding data in a memory unit, where each data set is assigned a check data segment with count data that characterizes the checking operation, allowing for error detection and prevention of accidental or deliberate changes, and cyclical checking for sleeping errors, ensuring high safety integrity levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is stored in memory unit without encoding and checking, then storage speed and simplicity are improved, but data integrity and error detection capability deteriorate
Solution Approach 1:
The patent applies preliminary action by encoding data with check data segments before storing them in the memory unit. This proactive measure ensures that error detection capability is built into the stored data structure, allowing future verification without requiring complex real-time checking mechanisms during retrieval.
Solution Approach 2:
The patent introduces check data segments as intermediaries between the original data and the memory storage system. These check data segments serve as mediators that enable error detection and verification without directly modifying the original application data, thus maintaining data integrity while enabling reliability checking.
2Reliability
If redundant computing instances are used for error detection, then error detection capability is improved, but hardware expenditure and system complexity worsen
Solution Approach 1:
The patent uses copying by creating check data segments that are derived from and associated with the original application data sets. Instead of requiring multiple redundant computing instances, the system creates simplified copies (check data segments) that contain verification information, enabling error detection with a single computing instance.
Solution Approach 2:
The patent extracts the error detection function from the main computing instance by separating check data segments from application data sets. This extraction allows the checking operation to be performed independently without requiring multiple full computing instances, thus reducing hardware expenditure while maintaining error detection capability.
3Measurement precision
If check data segments are updated with current checking operation count data, then error detection accuracy is improved, but processing time and operational complexity worsen
Solution Approach 1:
The patent implements periodic action by updating check data segments with count data that characterizes the checking operation being implemented. This periodic updating mechanism ensures that error detection remains accurate by reflecting the current state of checking operations, while the structured approach minimizes processing overhead through systematic updates.
Solution Approach 2:
The system performs self-service by automatically updating check data segments with current checking operation count data during the normal operation flow. This self-updating mechanism ensures error detection accuracy without requiring external intervention or complex manual tracking, thus reducing operational complexity despite the enhanced precision.
Data Source
AI summary
In a method for computer-assisted operation of a memory unit, encoded data is saved in the memory unit. The data is retrieved and decoded after retrieval. The memory unit is monitored for errors in that a temporal sequence of computer-assisted checking operations is carried out for the memory unit. For first-time encoding of the data, each required application data set is generated or selected, containing check data segments. For each application data set, the check data segment is occupied by count data, which characterizes the checking operation being implemented. After retrieving and decoding the application data sets, an error is determined when the count data characterizes neither the checking operation being implemented nor the most recent completely implemented checking operation. The check data segment of the relevant application data set is occupied by count data, which characterizes the checking operation being implemented, if no error was determined.