Storage Device Selection via Scoring Function
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Solution Overview
Problem
In data storage systems providing 'storage as a service,' efficiently selecting the most suitable storage device for virtual disks based on user requests is challenging due to the need for balancing cost, capacity, quality-of-service parameters, and location considerations.
Innovation Solution
A method and apparatus that compare attributes of storage devices with request parameters to generate device scores, identifying the best-suited storage device for mapping virtual disks by applying a device selection function that considers cost, capacity, quality-of-service, and location attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple storage devices are evaluated based on multiple attributes (cost, capacity, QoS, location), then the suitability of selecting the optimal storage device improves, but the complexity of the selection process increases
Solution Approach 1:
The patent transforms multiple storage device attributes (cost, capacity, QoS parameters, location) and request parameters into a unified scoring system. Each attribute is normalized and weighted to produce a single suitability score, converting a multi-dimensional selection problem into a single-parameter comparison that resolves the contradiction between selection reliability and process complexity.
2Measurement precision
If a comprehensive device selection function is applied to evaluate all storage devices against request parameters, then the accuracy of matching storage devices to virtual disk requirements improves, but the computational time and resources increase
Solution Approach 1:
The system pre-calculates and maintains attributes for each storage device (cost, capacity, QoS metrics, location) before requests arrive. When a request is received, the selection function immediately compares request parameters against these pre-prepared device attributes, avoiding redundant calculations and reducing the time penalty of comprehensive evaluation while maintaining matching accuracy.
3Reliability
If storage devices with higher quality-of-service attributes are selected, then the service level provided to users improves, but the operating cost increases
Solution Approach 1:
The scoring function incorporates both QoS attributes and cost attributes with configurable weights. By adjusting the weight parameters in the selection function, the system can optimize the balance between service quality and operating cost, transforming the trade-off into a controllable parameter relationship rather than a fixed contradiction.
Data Source
AI summary
Selecting a storage device to be mapped to a requested virtual disk includes maintaining attributes for a set of storage devices including a cost attribute, a capacity attribute and quality-of-service attributes. A request for a virtual disk includes request parameters including a price parameter, a capacity parameter and quality-of-service parameters. A device selection function generates a score for each storage device based on the request parameters and the storage device attributes, and identifies a best suited storage device by comparing the respective scores of the storage devices. The virtual disk is then created in satisfaction of the request with a mapping to the identified storage device to provide underlying physical data storage for the virtual disk.