Metadata Adjustment for Error Detection in Data Processing Blocks
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Solution Overview
Problem
Safety-critical applications on non-safety-critical hardware require effective monitoring of data processing to ensure correct program flow, especially in dynamic distributed systems where error detection and communication overhead must be managed efficiently.
Innovation Solution
A method involving data processing blocks that adjust metadata versions using adjustment values and rules, allowing for error detection through cyclic redundancy checks, ensuring correct processing by comparing final metadata versions with reference values, and enabling scalable error detection across complex data paths.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by stationary object
If safety-critical applications are executed on non-safety-critical hardware with software-emulated safety features, then hardware cost and power consumption are reduced, but system reliability and error detection capability deteriorate
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing adjustment values for each data processing block before runtime. These adjustment values are computed based on expected payload data characteristics and stored in a lookup table. During runtime, the metadata is adjusted using these pre-computed values, enabling fast error detection without complex real-time calculations, thus maintaining reliability while reducing power consumption.
Solution Approach 2:
The patent introduces metadata as an intermediary element that travels with payload data through the processing pipeline. This metadata contains checksum values that are adjusted using pre-computed adjustment values. The metadata acts as a mediator between the payload data and the error detection mechanism, enabling reliable error detection on non-safety-critical hardware without requiring complex safety-critical processing for every data item.
2Reliability
If complex program flow control is implemented to ensure correct data processing paths, then error detection capability is improved, but device complexity and communication overhead increase
Solution Approach 1:
The patent extracts the error detection logic from the main data processing flow by using separate metadata that travels parallel to the payload data. Instead of embedding complex check logic within each processing block, the error detection is performed by comparing adjusted metadata values at the end of the processing pipeline. This separation reduces device complexity while maintaining error detection capability.
Solution Approach 2:
The patent changes the parameter being monitored from complex program flow states to simple metadata values that can be adjusted using pre-computed adjustment values. By transforming the error detection problem into a parameter comparison problem (comparing final metadata values against expected values), the system achieves effective error detection with minimal complexity in the data processing path.
3Reliability
If comprehensive metadata tracking is performed through all data processing blocks, then program flow monitoring is improved, but communication overhead and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-computing adjustment values for each data processing block based on expected payload characteristics. These adjustment values are stored in advance, eliminating the need for complex real-time calculations during data processing. The metadata adjustment operation becomes a simple table lookup and arithmetic operation, significantly reducing processing time while maintaining comprehensive program flow monitoring.
4Productivity
If adjustment values are pre-calculated and stored for each data processing block, then error detection efficiency is improved, but initial setup complexity and memory requirements increase
Solution Approach 1:
The patent applies preliminary action by pre-calculating adjustment values during system initialization or offline preparation. These values are stored in compact lookup tables associated with each data processing block. The pre-computation phase, while requiring initial setup effort, enables extremely fast error detection during runtime through simple metadata adjustment operations, significantly improving error detection efficiency.
Data Source
AI summary
A method for checking a processing of payload data. The method includes processing the payload data and metadata by a sequence of data processing blocks. An adjustment value is ascertained for each data processing block as a function of a thereto-supplied payload data version so that, if the thereto-supplied metadata version is correctly processed by the data processing block to form a respective processing result, the processing result, after having been adjusted according to the adjustment value according to a specified adjustment rule, is equal to a value assigned to the data processing block. Each data processing block processes the metadata version supplied to it, and the next metadata version is derived from the supplied metadata version as a function of the processing result adjusted according to the adjustment value according to the specified adjustment rule, and checking whether the payload data have been processed correctly.