Dynamic Error Threshold Adjustment in Data Storage Systems
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Solution Overview
Problem
Current data system error recovery methods do not allow for dynamic adjustment of error thresholds based on system status changes, leading to inefficient error detection and potential loss of access to data in computing environments.
Innovation Solution
The method dynamically adjusts error thresholds in a data storage system by changing them based on system status changes, such as availability of redundant resources, I/O loads, and application updates, using a structure with multiple threshold values (high, medium, and low) to handle errors effectively without increasing code-processing overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a fixed default error threshold is used in data systems, then the system operation is simple and consistent, but the error detection accuracy deteriorates when system status changes (such as during application updates or when redundant resources become unavailable)
Solution Approach 1:
The patent implements dynamic error threshold adjustment by transitioning from a fixed default threshold to multiple threshold levels (high, medium, low) that are selected based on real-time system status. The system monitors conditions such as application update states and redundant resource availability to dynamically switch between different error thresholds, thereby adapting error detection sensitivity to current operational conditions without requiring complex reconfiguration.
Solution Approach 2:
The system changes the error threshold parameter based on system status conditions. When specific conditions are detected (such as being in an application update phase or lacking redundant resources), the system adjusts the error threshold parameter from the default value to appropriate high, medium, or low threshold values. This parameter adaptation allows the system to maintain optimal error detection accuracy across varying operational states while managing complexity through condition-based decision logic.
2Reliability
If error thresholds are dynamically adjusted based on system status, then error detection accuracy improves for high error rates, but the code-processing overhead increases
Solution Approach 1:
The patent applies different error threshold qualities to different system states rather than using a uniform threshold throughout. By identifying specific local conditions (application update phase, redundant resource status) and applying appropriate threshold levels (high, medium, low) to each state, the system optimizes error detection for high error rates when needed while avoiding unnecessary processing overhead in normal operational states. This localized adaptation of threshold quality maintains reliability without proportionally increasing overall processing complexity.
3Adaptability or versatility
If multiple error threshold values are implemented, then the adaptability to different system states improves, but the device complexity increases
Solution Approach 1:
The patent segments the error threshold into discrete levels (high, medium, low) that correspond to different system status conditions. Instead of implementing a continuous or complex adaptive threshold system, the invention divides the threshold parameter into distinct segments that can be selectively applied based on monitored conditions such as application update states and redundant resource availability. This segmentation approach provides adaptability to different system states while managing complexity through a structured, discrete threshold framework.
Data Source
AI summary
For efficient data system error recovery, an error threshold is dynamically adjusted from a default error threshold to one of a plurality of error threshold values comprising at least high threshold values, medium threshold values, and low threshold values, for a particular error associated with an event object indicating a responsive action for handling the particular error in a data system. The responsive action to the event object comprises determining whether the error threshold needs to be adjusted for the particular error, and if it is determined the error threshold for the particular error does not need adjustment, the default error threshold is used.