Geo-Aware Cloud Storage Quota Management
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Solution Overview
Problem
Current disk quota management systems in cloud computing lack awareness of geo-specific storage availability and costs, leading to inefficient resource allocation and increased costs due to varying prices across different geographic locations.
Innovation Solution
A cloud quota management system that identifies storage component locations and properties, including available space and costs, to generate user-specific storage quotas, prioritizing cost-effectiveness and geo-aware allocation, using a Storage Cloud Management System Interface (SCMSI) to manage and display storage quotas based on user preferences and properties.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If traditional disk quota management is used without geo-awareness, then implementation simplicity is maintained, but storage cost efficiency deteriorates due to ignoring geographic price variations
Solution Approach 1:
The system implements geo-specific storage quotas that assign different storage allocation limits to different geographic regions based on local pricing and availability characteristics. This allows the organization to optimize storage costs by allocating more capacity to regions with lower costs while maintaining service levels in critical regions, directly addressing the cost efficiency problem without requiring complete system redesign
Solution Approach 2:
The invention changes the quota management approach by introducing geographic location as a variable parameter. Instead of uniform or user-only-based quotas, the system now considers geographic parameters (location, local pricing, local availability) to dynamically determine storage allocation limits, thereby improving cost efficiency while maintaining manageable complexity through structured parameter-based control
2Loss of energy
If geo-aware storage quota management is implemented, then storage cost efficiency is improved, but system complexity increases due to tracking multiple storage component locations and properties
Solution Approach 1:
The system introduces a cloud quota management module as an intermediary layer between the storage components and users. This module abstracts the complex geo-aware quota calculations, location tracking, and cost computations, presenting a simplified interface to users while handling the complexity internally. This resolves the contradiction by improving cost efficiency through sophisticated management while shielding users from the resulting system complexity
Solution Approach 2:
The invention segments the storage system into distinct geographic regions with independently managed quotas. Each region can be configured with its own pricing parameters and availability characteristics, allowing the system to handle complexity in a modular, organized manner rather than as a monolithic system, thereby making the complexity more manageable
3Ease of operation
If uniform storage quotas are applied across all locations, then administrative management is simplified, but resource distribution equity deteriorates due to varying storage costs and availability across regions
Solution Approach 1:
The system implements location-specific storage quotas that recognize and adapt to local conditions such as pricing and availability in different geographic regions. This allows equitable resource distribution by allocating storage capacity according to local characteristics rather than applying uniform standards, directly addressing the fairness problem while maintaining administrative simplicity through automated geo-based rules
Data Source
AI summary
An embodiment of the invention provides a method for storage management in a cloud computing system. More specifically, locations of storage components in the cloud computing system and storage properties of the storage components are identified. The storage properties include the amount of available storage space and/or the cost of storage space. A storage quota for a user of the cloud computing system is generated with a cloud quota management module based on the locations of the storage components and/or the storage properties of the storage components. In at least one embodiment, the storage quota includes the maximum amount of storage allocated to the user in at least one of the storage components.