Tiered Storage Migration Using Multi-Granularity Heat Maps
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Solution Overview
Problem
In tiered storage architectures, there is a need for an effective means to determine which portion of the storage environment performs caching and migration operations on data segments for optimal performance, as existing systems lack a mechanism to differentiate between uniformly hot and sparsely hot data segments for efficient migration and caching.
Innovation Solution
The implementation of a system that uses heat maps of differing granularities to determine whether data segments are uniformly or sparsely hot, allowing for tailored caching and migration mechanisms, where uniformly hot segments are migrated to Solid State Drives and sparsely hot segments are migrated to lower-speed caches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single heat map granularity is used for data migration decisions, then the system is simpler to implement, but it cannot effectively differentiate between uniformly hot and sparsely hot data segments
Solution Approach 1:
The patent divides the heat map into multiple granularities (e.g., block level and sector level) to segment the data storage structure. This allows the system to analyze data hotness at different levels of detail, enabling differentiation between uniformly hot data segments and sparsely hot data segments without requiring a single overly complex measurement approach.
Solution Approach 2:
The patent introduces a new dimension of analysis by implementing heat maps at multiple granularities simultaneously. Instead of using a single heat map, the system creates a multi-level heat map structure that adds depth to the hotness detection capability, allowing for more precise classification of data segments based on their access patterns.
2Speed
If all data segments are migrated to high-speed SSDs, then read performance is maximized, but storage cost and migration overhead increase
Solution Approach 1:
The patent applies different quality levels of storage to different data segments based on their hotness characteristics. Uniformly hot data segments are migrated to high-speed SSDs for optimal read performance, while sparsely hot data segments remain on lower-speed storage. This local differentiation ensures that high-performance storage resources are allocated only where most needed, balancing performance and cost.
3Reliability
If heat maps are updated frequently to capture data access patterns, then migration decisions are more accurate, but system overhead and latency increase
Solution Approach 1:
The patent performs preliminary analysis of data access patterns by maintaining heat maps that are updated periodically rather than continuously. The system pre-calculates and stores hotness metrics in the heat maps, allowing for accurate migration decisions without requiring real-time updates during data access operations. This preliminary action approach balances accuracy with performance.
Data Source
AI summary
For data processing in a computing storage environment by a processor device, the computing storage environment incorporating at least high-speed and lower-speed caches, and tiered levels of storage, groups of data segments are migrated between the tiered levels of storage such that uniformly hot ones of the groups of data segments are migrated to utilize a Solid State Drive (SSD) portion of the tiered levels of storage, while sparsely hot ones of the groups of data segments are migrated to utilize the lower-speed cache.