Cloud Data Migration via Geographic Service Unit Grouping
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Solution Overview
Problem
Traditional storage arrays face performance limitations due to physical and temporal constraints, and the adoption of Virtual Desktop Infrastructure and mobile applications introduces challenges in dynamically moving data across geographically dispersed storage tiers, requiring efficient data migration and replication to follow users and applications in real-time.
Innovation Solution
A computer-implemented method and system for migrating user assets across a cloud by grouping Service Units into cells and areas, determining the optimal Service Unit location based on geographic proximity, service contracts, and SLAs, and transferring assets seamlessly without disrupting services, using a Service-Oriented Architecture (SOA) approach to automate data migration across different tiers and geographic locations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data is stored in fixed geographic locations, then storage capacity is maintained, but access speed and service quality deteriorate when users move
Solution Approach 1:
The patent implements dynamic data migration by continuously monitoring user location and automatically transferring data between storage devices based on current geographic position. This dynamic approach ensures data is always stored on the nearest available device, optimizing access speed without requiring manual intervention or complex migration planning.
Solution Approach 2:
The system employs self-service mechanisms where the storage network automatically detects user movement and initiates data migration without external control. The distributed storage devices autonomously coordinate to transfer data, eliminating the need for centralized management complexity while maintaining optimal service quality.
2Reliability
If data is replicated across multiple geographic locations, then service availability is improved, but storage costs and system complexity increase
Solution Approach 1:
The patent segments the storage system into distributed geographic zones, with data replicated across multiple locations organized in a hierarchical structure. This segmentation provides service availability through geographic distribution while managing complexity through structured organization and automated zone-based migration protocols.
3Productivity
If data migration is performed manually, then control and security are maintained, but response time and productivity decrease
Solution Approach 1:
The system implements continuous feedback loops that monitor user location, data access patterns, and storage device status. This feedback enables automated real-time migration decisions while incorporating security policies and access controls, achieving both high productivity and maintained security through intelligent automated decision-making.
Data Source
AI summary
A computer implemented method, system, and program product for migration of a user's assets across a cloud comprising Service Units, the method comprising grouping Service Unit devices into cells, wherein the service units comprise storage devices, wherein each cell comprises a group of the Service Unit device comprising a common geographic region, grouping the cells into areas, each cell of the cells grouped into an area comprising a common geographic region, determining the location of the user with respect to the cells, determining the area corresponding to the determined cells, determining which cell of the cells contains the Service Unit device that provides the user with the best services; and transferring the user's assets to the Service Unit within the determined cell.