Frame Memory Checksum Validation for Corruption Detection
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Solution Overview
Problem
Existing methods for managing data corruption in frame memory, such as in portable electronic devices, often result in unnecessary power and data consumption by periodically updating the memory even when no new data is present, leading to inefficient data management and prolonged display of corrupted data.
Innovation Solution
A method involving the calculation and comparison of validation parameters, such as checksums, at different times to determine data corruption, allowing for targeted updates only when discrepancies are detected, thereby minimizing unnecessary updates and power usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the frame memory is updated periodically to minimize corrupted data display time, then the reliability of data display is improved, but the power consumption and data processing load increase significantly
Solution Approach 1:
The patent implements a feedback mechanism where the checksum of the current frame memory content is calculated and compared with a previously stored checksum. This feedback loop enables the system to detect data corruption and trigger updates only when necessary, rather than following a fixed periodic schedule. The feedback principle resolves the contradiction by making the update frequency adaptive to actual data integrity conditions.
Solution Approach 2:
The patent transforms the static periodic update approach into a dynamic adaptive update approach. The update timing is no longer fixed but varies based on the detected data integrity status. When corruption is detected through checksum comparison, an immediate update is triggered; when no corruption is detected, updates are deferred. This dynamic adjustment resolves the contradiction by optimizing power consumption while maintaining reliability.
2Reliability
If the frame memory is updated frequently to ensure data accuracy, then the reliability is improved, but the loss of time for other data processing increases
Solution Approach 1:
The checksum comparison feedback mechanism enables the system to identify when updates are actually needed versus when they are unnecessary. By feeding back the integrity status to the update controller, the system avoids wasting processing time on redundant updates, thus resolving the time loss contradiction while maintaining data integrity through targeted updates.
Solution Approach 2:
The patent changes the parameter of update frequency from a fixed value to a variable parameter that adapts based on data integrity conditions. This parameter change allows the system to optimize the balance between reliability and processing efficiency by adjusting update timing according to actual needs rather than following a rigid schedule.
3Measurement precision
If validation parameters are calculated and compared at every refresh cycle, then the detection precision of corruption is improved, but the processing complexity increases
Solution Approach 1:
The patent uses checksums, which are computationally inexpensive validation parameters, rather than more complex validation methods. The checksum calculation is a simple arithmetic operation that can be performed quickly with minimal processing resources. This choice of a 'cheap' validation method achieves sufficient detection precision without significantly increasing processing complexity.
4Reliability
If the frame memory contents are completely refreshed periodically, then the reliability of displayed data is improved, but the quantity of data transferred increases unnecessarily
Solution Approach 1:
The checksum comparison provides feedback on whether the current data is corrupted or intact. When the feedback indicates no corruption (matching checksums), the system skips the complete data transfer, thereby reducing data transfer volume. When corruption is detected (mismatching checksums), a complete refresh is triggered to ensure reliability. This feedback-driven approach resolves the contradiction between reliability and data transfer quantity.
Solution Approach 2:
Instead of always performing the complete action of refreshing the entire frame memory, the patent applies partial action by conditionally refreshing only when necessary. This selective approach reduces unnecessary data transfer while maintaining reliability through targeted refreshes based on corruption detection.
Data Source
AI summary
Image or other data is stored in a memory. A first validation parameter (e.g., a checksum) is determined for the data stored in the memory at a first time, and stored. A second validation parameter is determined for the data stored in the memory at a second time, and also stored. The stored first and second validation parameters are then compared. In this manner, corruption of data in the memory may be determined by the comparison. In the case where the compared first and second validation parameters are not identical (within a threshold in certain embodiments), the data stored in the memory is updated. As applied to graphical image data, this is seen as advantageous over the prior art approach of periodically updating a frame memory even when no new image data set is present. Apparatus and computer program products are also detailed.