Dynamic Dump Data Collection Management for Storage Area Networks
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Solution Overview
Problem
Current data dump collection processes are time-consuming and can lead to data loss due to timer expirations, especially when prioritizing dump data collection, as they often suspend input/output operations, causing delays and potential loss of data.
Innovation Solution
A method that selectively focuses on the most relevant data dump components, allowing for dynamic component selection to ensure total collection time does not exceed a predetermined maximum, thereby reducing collection time and resources needed, and utilizing expected collection times to manage dump data transfer within a timed interval.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dump data collection process suspends input/output operations to collect all dump data, then data completeness is improved, but system productivity deteriorates due to operation delays
Solution Approach 1:
The patent divides the complete dump data into multiple priority-based segments or categories. Instead of collecting all dump data uniformly, the system segments data by priority levels and collects only the necessary segments based on the specific error or event type, thereby reducing collection time and minimizing impact on system throughput while maintaining data completeness for relevant segments.
Solution Approach 2:
The patent implements partial action by collecting only the necessary portion of dump data required for diagnosing a specific error or event, rather than collecting the entire dump data set. The system determines the minimum required data scope based on error type analysis, suspends I/O operations only for that limited scope, and resumes operations sooner, thus maintaining productivity while ensuring sufficient data for diagnosis.
2Productivity
If dump data collection timer is set short to maintain productivity, then system throughput is improved, but data loss increases due to premature timer expiration
Solution Approach 1:
The patent performs preliminary actions by pre-identifying and prioritizing the critical dump data components needed for specific error types before the timer expires. The system analyzes the error or event type, determines which data segments are essential, and collects them first within the timer constraint. This preliminary identification ensures that the most valuable data is captured within the limited time window, maintaining both productivity and data integrity.
Solution Approach 2:
The patent implements feedback mechanisms where the system continuously monitors the collection progress against the timer and dynamically adjusts the collection strategy. If the timer is approaching expiration, the system receives feedback about remaining time and prioritizes completing the collection of high-priority data segments, ensuring critical data is captured before time runs out while minimizing the impact on throughput.
3Measurement precision
If all dump data components are collected to ensure complete diagnosis, then diagnostic accuracy is improved, but collection time increases beyond acceptable limits
Solution Approach 1:
The patent applies local quality by assigning different collection priorities and quality requirements to different dump data components based on their relevance to specific error types. Instead of uniformly collecting all data with the same level of detail, the system identifies which data components require high-fidelity collection for accurate diagnosis of the particular error, and collects only those with appropriate priority, thereby reducing overall collection time while maintaining diagnostic accuracy for the relevant components.
4Quantity of substance
If volatile memory is allocated for complete dump data storage, then data capacity is improved, but memory resource consumption increases
Solution Approach 1:
The patent segments the dump data storage requirement into priority-based portions, allocating volatile memory resources accordingly. Instead of reserving memory for the complete dump data set, the system allocates memory for only the high-priority and error-relevant data segments that need to be collected within the timer constraint. This segmented allocation reduces overall memory consumption while maintaining sufficient capacity for the critical data required for effective diagnosis.
Data Source
AI summary
Provided are a computer program product, system, and method for dump data collection in accordance with one embodiment of the present description, in which a variable number of data dump components are selected from a set of data dump components. Each component contains a portion of an available dump data and has associated therewith a component collection time to collect the dump data associated with the component. A determination is made as to whether a total component collection time for the selection of data dump components exceeds a predetermined maximum. The dump data contained in the selection of data dump components is collected if the total component collection time for the selection of data dump components does not exceed the predetermined maximum. Other aspects of dump data collection management in accordance with the present description are described.