Adaptive LUN Storage Allocation via Access Frequency Query
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Solution Overview
Problem
Existing storage systems require manual configuration of performance levels by administrators, which is inefficient and does not adapt dynamically to changing data access patterns, leading to suboptimal storage of data across different performance levels.
Innovation Solution
A method and device that query and obtain performance levels of Logical Unit Numbers (LUNs) in a storage device, allowing data to be written into LUNs based on accessing frequency, enabling adaptive and dynamic hierarchical storage without manual administrator intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual configuration of performance levels by administrators is used, then the storage system can be managed with simple device structure, but the storage system cannot adapt dynamically to changing data access patterns
Solution Approach 1:
The storage device automatically queries its own performance levels and allocates data without requiring external administrator intervention. The storage device performs self-assessment of performance capabilities and autonomously makes allocation decisions based on data access patterns, eliminating the need for manual configuration while maintaining simple device structure.
Solution Approach 2:
The system implements automatic feedback mechanisms where the storage device continuously monitors data access patterns and adjusts performance level allocations dynamically. This feedback loop enables the storage system to adapt to changing access patterns automatically, improving versatility without requiring complex manual management mechanisms.
2Productivity
If automatic performance level querying and data allocation is implemented, then storage efficiency is improved through adaptive allocation, but the operation process becomes more complex
Solution Approach 1:
The storage device performs automatic performance level querying and data allocation without requiring administrator operations. The system serves itself by autonomously monitoring performance, querying appropriate levels, and allocating data based on access patterns, thereby improving storage efficiency while maintaining operational simplicity through automation.
Solution Approach 2:
The storage device proactively queries performance levels and pre-allocates data to appropriate storage tiers before access patterns change. This preliminary action enables the system to be prepared for upcoming access demands, improving storage efficiency by having data ready at optimal performance levels while keeping the operation process simple through advance automation.
3Adaptability or versatility
If hierarchical storage management is implemented with multiple storage media types, then storage performance requirements are met, but manual specification of performance levels is required
Solution Approach 1:
The storage device automatically determines appropriate performance levels for different data types and access patterns without requiring administrator specification. The system self-manages the hierarchical allocation across multiple storage media types (SSD, SAS/FC HDD, SATA/NL SAS HDD) by autonomously assessing performance requirements and assigning data to appropriate tiers.
Solution Approach 2:
The hierarchical storage management becomes dynamic and adaptive, automatically adjusting performance level assignments based on real-time access patterns rather than static manual configuration. The system dynamically migrates data between different storage media types based on changing performance requirements, enhancing versatility while increasing automation.
Data Source
AI summary
The embodiments of the present invention provide a data storage method, including: sending a performance level request to a storage device, which is used to query information about performance level of one or more logical unit number LUNs in the storage device; receiving a response sent by the storage device in response to the performance level request, wherein the response comprises the information about performance levels of the LUNs; and obtaining performance levels of the LUNs according to the information about performance levels of the LUNs so that data to be stored is written into a LUN of a corresponding performance level according to a accessing frequency level of the data to be stored comprised in a write-data instruction when the write-data instruction is received.