Cluster Node Scan Prioritization Using Feedback Heatmaps
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Solution Overview
Problem
Existing scan frameworks in storage systems do not efficiently prioritize work items for processing, leading to prolonged scan times and potential data unavailability or loss due to the non-prioritization of error-prone areas.
Innovation Solution
A statistics and feedback-based scan framework that creates a heatmap of work items based on runtime IO operations and metadata access, adjusting priorities dynamically based on the results of scan operations to prioritize high-risk areas for faster error detection and correction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If work items are processed in non-prioritized order, then all work items are eventually scanned, but scan time is prolonged and error-prone areas are not detected quickly
Solution Approach 1:
The patent applies local quality by creating a heatmap that assigns different priority levels to different work items based on their individual characteristics. Work items are not treated uniformly but are prioritized locally according to their error probability, I/O activity, and metadata access patterns. This allows the system to focus scanning resources on high-risk areas while maintaining comprehensive coverage.
Solution Approach 2:
The patent implements preliminary action by pre-calculating and storing priority scores for all work items before scanning begins. The heatmap is generated in advance based on historical data, I/O operations, and metadata access patterns, allowing the scanning process to immediately proceed with prioritized work items without real-time decision-making delays.
2Productivity
If scan operations are performed on all work items uniformly, then comprehensive coverage is achieved, but processing efficiency is reduced due to lack of prioritization
Solution Approach 1:
The system maintains scan coverage reliability by ensuring that while work items are prioritized, all work items eventually receive scanning attention. The heatmap-based prioritization creates different processing speeds for different regions, but the comprehensive nature of the scan framework ensures complete coverage over time, balancing efficiency with reliability.
Solution Approach 2:
The patent applies dynamics by making the scan processing rate adaptive rather than static. The scanning speed and resource allocation dynamically adjust based on the heatmap priorities, accelerating processing for high-priority work items while maintaining slower processing for low-priority items, yet ensuring all items are eventually scanned.
3Measurement precision
If heatmap priorities are updated frequently based on scan results, then priority accuracy is improved, but system complexity and overhead increase
Solution Approach 1:
The patent implements feedback by using scan results to update the heatmap priorities. When work items are scanned and errors are detected or corrected, this information feeds back into the heatmap calculation, adjusting the priority scores of affected work items and their neighbors. This continuous feedback loop improves priority accuracy over time while maintaining a manageable update frequency.
Solution Approach 2:
The system applies parameter changes by adjusting the heatmap priority values based on scan outcomes. Specific parameters such as error frequency, correction count, and priority score are modified according to scan results, allowing the system to adapt priorities without fundamentally changing the overall heatmap structure or requiring complex reconfiguration.
Data Source
AI summary
A statistics and feedback-based diagnostic scan framework for cluster nodes is provided, that prioritizes work items for processing by cluster nodes according to work item priority. A heatmap of work items is created and used by the diagnostic scan framework to prioritize work items for processing by the cluster nodes. The heatmap may be created from runtime IO operations, metadata access/updates, or other metrics derived from systems executing within the storage system. Additionally, as cluster nodes process allocated work items, the results of the scan operations are used to update the heat map to adjust the heat map based on the results of the previous scan operations. The heat map may prioritize individual work items or may create regions of work items and prioritize processing of work items according work item region.