Storage Controller Optimizing Virtual Storage Combinations
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Solution Overview
Problem
In data storage systems, the performance of virtual storage resources is often limited by the lowest-speed physical storage resource, leading to underutilization of higher-speed resources and inefficient power consumption, even when a combination of physical resources is chosen for optimal speed.
Innovation Solution
An information handling system with a storage controller that determines unique combinations of physical storage resources based on performance and power metrics to select an optimal combination for building a virtual storage resource, balancing effective performance, performance penalties, total power consumption, and power penalties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If physical storage resources of different speeds are combined in a virtual storage resource, then storage capacity is increased, but performance is limited by the lowest-speed resource
Solution Approach 1:
The patent segments the storage array into multiple zones based on performance characteristics (high-performance, medium-performance, low-performance zones). This allows virtual storage resources to be assigned to specific zones matching their performance requirements, preventing fast resources from being bottlenecked by slow resources while still utilizing all available capacity.
Solution Approach 2:
Different portions of the storage array are assigned different performance characteristics and service levels. High-performance resources receive priority access and are allocated to performance-critical virtual resources, while lower-performance resources serve less demanding workloads. This ensures each resource operates at its optimal performance level.
2Speed
If a combination of physical storage resources is chosen for highest speed, then performance is improved, but power consumption may not be minimized
Solution Approach 1:
The system dynamically adjusts operational parameters including power states of physical storage resources based on workload demands. When performance is not critical, resources can operate in lower-power states. The controller monitors both performance metrics and power consumption, adjusting resource allocation and power states to achieve optimal balance between speed and energy usage.
3Productivity
If higher-speed physical storage resources are used, then performance is improved, but power consumption increases
Solution Approach 1:
The storage system dynamically adjusts resource allocation and operational modes based on real-time workload characteristics. During periods of high demand, higher-performance resources are activated. During low-demand periods, the system transitions to lower-power states or consolidates workloads onto fewer resources, reducing overall power consumption while maintaining required service levels.
Solution Approach 2:
The controller continuously monitors performance metrics and power consumption of physical storage resources, using this feedback to optimize resource allocation. When performance targets are met with lower power consumption, the system adjusts accordingly. When performance demands increase, the system activates additional or higher-performance resources, creating a closed-loop optimization system.
Data Source
AI summary
In accordance with embodiments of the present disclosure, a method may include receiving requirements for building a virtual storage resource from an array of physical storage resources, receiving performance metrics and power metrics of the physical storage resources of the array available for inclusion in the virtual storage resource, determining a plurality of unique combinations of the available physical storage resources that could be used to build the virtual storage resource, determining an effective performance, an effective performance penalty, a total power consumption, and an effective power penalty for each of the plurality of unique combinations, and selecting a single combination of the plurality of unique combinations for the virtual storage resource based on effective performances, effective performance penalties, total power consumptions, and effective power penalties of the plurality of unique combinations.