Storage Device Grouping for SSD Allocation
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Solution Overview
Problem
In distributed storage systems, the performance efficiency of Solid-State Drives (SSDs) is low due to their limited deployment and inefficient allocation, as they are not adequately utilized in scenarios requiring frequent data read/write operations, leading to wasted storage space and idle SSD resources.
Innovation Solution
Divide storage devices into groups based on the frequency of data read/write operations by service subsystems, allocating a larger quantity of SSDs to subsystems that perform more frequent operations and HDDs to less frequent ones, ensuring that SSDs are optimally utilized in high-demand scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If SSDs are deployed in limited quantities due to cost constraints, then cost is reduced, but storage performance efficiency deteriorates because SSDs are not adequately allocated to high-demand service subsystems
Solution Approach 1:
The patent applies local quality by differentiating storage device allocation based on service subsystem characteristics. High-demand service subsystems receive SSDs for fast read/write operations, while low-demand subsystems use HDDs. This non-uniform allocation optimizes overall system performance by matching storage medium properties to specific operational requirements, resolving the contradiction between limited SSD quantity and storage performance efficiency.
Solution Approach 2:
The patent implements dynamic allocation of storage devices by continuously monitoring service subsystem read/write frequencies and adjusting SSD distribution accordingly. When service subsystems' data access patterns change, the system reconfigures storage device assignments to maintain optimal performance. This dynamic approach ensures that limited SSD resources are always directed to the most demanding workloads, maximizing storage performance efficiency despite quantity constraints.
2Ease of operation
If SSDs are allocated uniformly across all service subsystems, then allocation simplicity is maintained, but storage speed deteriorates because high-demand subsystems do not receive sufficient SSD capacity
Solution Approach 1:
The patent replaces static uniform allocation with dynamic allocation based on monitored service subsystem behavior. By tracking read/write frequencies and automatically adjusting SSD distribution, the system achieves both simplicity (automated decision-making) and high storage speed (optimized resource placement). The dynamic nature allows the system to adapt to changing demands without complex manual configuration.
Solution Approach 2:
The patent implements feedback mechanisms that monitor service subsystem data access patterns and use this information to guide SSD allocation decisions. The system continuously collects performance data, analyzes read/write frequencies, and adjusts storage device assignments accordingly. This closed-loop feedback ensures that storage speed requirements are met while maintaining allocation simplicity through automated, data-driven decision-making.
3Speed
If more SSDs are deployed to improve storage speed, then storage performance is enhanced, but cost increases due to the high price of SSDs compared to HDDs
Solution Approach 1:
The patent applies local quality by concentrating SSD resources in high-demand service subsystems where fast storage is critical, while using cheaper HDDs in low-demand subsystems. This targeted approach maximizes storage speed where it matters most while minimizing overall cost by avoiding unnecessary SSD deployment throughout the entire system. The non-uniform distribution resolves the contradiction between storage speed enhancement and cost control.
Solution Approach 2:
The patent implements partial action by deploying SSDs only to the extent necessary for high-demand service subsystems, rather than uniformly across all subsystems. By identifying and serving only the most critical workloads with premium storage media, the system achieves sufficient storage speed performance at lower cost compared to comprehensive SSD deployment, resolving the contradiction between speed enhancement and cost increase.
4Device complexity
If storage devices are not divided into device groups, then system complexity is reduced, but SSD idleness increases because SSDs cannot be efficiently matched to specific service subsystems
Solution Approach 1:
The patent applies segmentation by dividing storage devices into distinct device groups and establishing one-to-one correspondences with service subsystems. This segmentation enables precise matching of SSDs to high-demand subsystems, eliminating idle SSD resources that would occur with undifferentiated storage pools. The segmented structure resolves the contradiction by organizing complexity into manageable, purpose-specific units that optimize resource utilization.
Solution Approach 2:
The patent implements dynamic device group formation that adapts to changing service subsystem demands. By continuously monitoring read/write frequencies and reconfiguring storage device groupings accordingly, the system minimizes SSD idleness while maintaining manageable complexity through automated management. The dynamic reconfiguration ensures that SSDs are always actively utilized by appropriate service subsystems, resolving the contradiction between system complexity and resource utilization efficiency.
Data Source
AI summary
Storage devices are divided into subgroups and assigned to subsystems based on data input and data output frequencies of the subsystems. Each subgroup of storage devices is associated with a corresponding subsystem. A subsystem with higher data input and data output frequencies is assigned a higher number of solid state drives than a subsystem with lower data input and data output frequencies.