Cloud Storage Pool Migration by Data Heat and Bandwidth
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Solution Overview
Problem
Existing cloud storage systems face inefficiencies in data migration due to the lack of a strategic approach that accounts for data heat levels and bandwidth requirements, leading to suboptimal utilization of storage resources and increased costs.
Innovation Solution
A method and system for data processing that migrates data blocks based on their heat levels and bandwidth needs, determining a second storage pool that meets the requirements for accurate data migration, thereby optimizing storage utilization and reducing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data migration is performed without considering data heat levels and bandwidth requirements, then storage pool replacement and construction can proceed, but data access efficiency deteriorates and storage costs increase
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting data migration decisions based on heat level parameters and bandwidth parameters. The system evaluates multiple parameters (heat level, bandwidth requirements, storage pool performance) and changes migration parameters accordingly to optimize both access efficiency and cost effectiveness
Solution Approach 2:
The patent implements local quality by treating different data blocks with different migration strategies based on their individual heat levels and bandwidth requirements. Each data block is evaluated independently and migrated to storage pools that specifically match its characteristics, rather than applying a uniform migration policy
2Productivity
If data blocks are migrated to storage pools without matching performance characteristics, then storage resource utilization may improve, but data access speed deteriorates
Solution Approach 1:
The patent applies segmentation by dividing data into data blocks and evaluating each block's heat level and bandwidth requirements separately. Storage pools are also segmented by performance characteristics, allowing precise matching between data block requirements and storage pool capabilities
Solution Approach 2:
The patent implements feedback mechanisms by continuously monitoring data access patterns, heat levels, and bandwidth usage. This feedback information is used to dynamically adjust migration decisions and ensure data blocks remain in storage pools that match their current performance requirements
3Ease of operation
If all data blocks are migrated uniformly regardless of their access patterns, then migration process simplicity is maintained, but bandwidth utilization efficiency deteriorates
Solution Approach 1:
The patent applies dynamics by making the migration process adaptive rather than static. The system dynamically evaluates heat levels and bandwidth requirements in real-time, adjusting migration decisions based on current conditions. This creates a flexible, responsive migration process that optimizes bandwidth utilization
Data Source
AI summary
Examples of the present application relate to a method and system for data processing, and relate to the field of storage technology. The method includes: receiving an access request for a data block, the data corresponding to the data block being stored in the first storage pool; in response to the access request, determining a second storage pool in accordance with the data heat level of the data block and the bandwidth required for the data block; writing the data corresponding to the data block into the second storage pool. Thus, the overall access efficiency of the storage pool in the cloud computing platform may be improved.