Storage Provisioning via Logical Profiles and Objective Functions
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Solution Overview
Problem
Users of data storage systems, particularly customers configuring and provisioning storage for applications like email servers, lack the sophistication and knowledge to effectively select and allocate appropriate resources, leading to suboptimal storage solutions.
Innovation Solution
A method and apparatus for selecting resources for provisioning, which involves defining usage profiles based on core criteria and evaluating objective functions to determine the best set of resources for provisioning, using a piecewise objective function to optimize performance, cost, and capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual storage configuration and provisioning tasks are performed by customers, then storage can be allocated and configured, but the complexity of selecting appropriate resources increases and requires sophisticated knowledge
Solution Approach 1:
The patent introduces an intermediary system (storage provisioning system) that mediates between the customer's storage needs and the complex resource selection process. The system automatically evaluates multiple resources against defined criteria and selects the optimal configuration, eliminating the need for customers to directly navigate complex resource selection while still achieving appropriate storage allocation.
Solution Approach 2:
The system enables self-service by allowing customers to define their storage needs through simple usage definitions and criteria, while the automated provisioning system handles the complex resource evaluation and selection. The system serves itself by automatically selecting resources based on objective functions and criteria without requiring manual intervention in the complex selection process.
2Reliability
If multiple storage resources and configurations are evaluated, then optimal storage solution can be found, but the time required for evaluation increases
Solution Approach 1:
The patent applies preliminary action by pre-defining usage definitions, criteria, and objective functions before the actual resource selection process. These pre-established frameworks enable rapid evaluation of multiple resources without requiring time-consuming analysis during the selection process, as the evaluation criteria are already in place and can be directly applied to compare resources.
Solution Approach 2:
The system uses parameter changes by transforming the resource evaluation process into a comparison of objective function values derived from specific parameters (performance, cost, capacity). By changing the evaluation approach to parameter-based scoring, the system can rapidly compare multiple resources and configurations without time-consuming manual analysis, while still achieving reliable selection results.
3Manufacturing precision
If detailed storage criteria and configurations are provided, then appropriate resources can be selected, but the difficulty of detecting and measuring appropriate criteria increases
Solution Approach 1:
The patent replaces the mechanical/manual process of criteria measurement and evaluation with an automated computational system. The objective function and criteria evaluation are performed through computer-based calculations and comparisons, eliminating the difficulty of manually detecting and measuring appropriate criteria. The system automatically measures and compares resource attributes against defined criteria to determine the optimal allocation.
Data Source
AI summary
Described are techniques for selecting resources for provisioning. A usage definition, including a piecewise objective function, and first set of logical profiles based on core criteria are selected. Each of the logical profiles in the first set represents a resource set characterized by a core criteria value set that specifies values for the core criteria. A second set of resulting objective function values are determined by evaluating one piece of the objective function for each of the logical profiles in the first set. A highest ranked one of the resulting objective function values in the second set is selected having a corresponding first logical profile of the first set and a corresponding core criteria value set. A third set of resources is selected which is characterized by the corresponding core criteria value set for the first logical profile. The third set of resources is any of recommended or selected for provisioning.