Scheduled Data Tiering for Storage Access Optimization
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Solution Overview
Problem
Data often resides in slower performance tiers when it should be in faster tiers, leading to inefficient storage and access in modern data storage systems.
Innovation Solution
A method for retiering data within a storage system, allowing users to schedule data portions to be moved between different tiers based on future time points, enabling uptiering to faster tiers during increased access and downtiering to slower tiers during decreased access, using a user interface to specify the data portion, current tier, and target tier.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If data is placed in slower performance tiers to reduce storage costs, then storage efficiency is improved, but data access performance deteriorates when data should be in faster tiers
Solution Approach 1:
The patent implements dynamic data tiering where data automatically moves between storage tiers based on changing access patterns. The system continuously monitors data access frequency and performance requirements, then relocates data portions between fast and slow tiers to optimize both access performance and storage efficiency in real-time conditions
Solution Approach 2:
The system employs feedback mechanisms by monitoring data access patterns and performance metrics, then using this information to make intelligent decisions about data placement. The feedback loop detects when data should be migrated between tiers and automatically executes the migration to maintain optimal system performance
2Loss of energy
If manual data tiering management is used, then storage cost is reduced, but system complexity and operational difficulty increase
Solution Approach 1:
The patent implements self-service automated tiering management where the storage system autonomously monitors its own performance, identifies data migration needs, and executes tiering operations without human intervention. The system self-manages the complexity of multi-tier coordination, data movement scheduling, and performance optimization
Solution Approach 2:
The system dynamically changes storage parameters such as data placement location, access priority, and tier allocation based on monitored performance metrics and access patterns. By automatically adjusting these parameters, the system reduces operational complexity while maintaining cost-effective storage utilization
3Speed
If data is kept in faster tiers for improved access performance, then data access speed is improved, but storage efficiency and cost effectiveness deteriorate
Solution Approach 1:
The patent segments data into different portions based on access patterns and performance requirements, placing frequently accessed data in fast tiers and less frequently accessed data in slow tiers. This segmentation allows the system to optimize access speed for critical data while maintaining storage efficiency for the overall dataset
Solution Approach 2:
The system applies local quality optimization by assigning different storage tier qualities to different data portions based on their specific access characteristics. Each data portion receives the appropriate storage quality (fast or slow tier placement) matched to its local access patterns, rather than applying a uniform storage strategy to all data
Data Source
AI summary
A method, computer program product, and computing system for rendering a user interface screen that is accessible by a user of a storage system. The storage system includes a plurality of data tiers. An indication is received, via the user interface screen, that identifies a data portion to be retiered and a future point-in-time when the data portion will be retiered amongst the plurality of data tiers. At the future point-in-time, the retiering of the data portion is effectuated amongst the plurality of data tiers.