Disk Group Data Availability Estimation
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Solution Overview
Problem
It is challenging to evaluate the relative effectiveness of data redundancy strategies and select an optimal configuration for redundant storage systems due to the lack of reliability statistics and difficulty in determining failure rates, making it hard to ensure data availability and minimize data loss.
Innovation Solution
A method and system to calculate the estimated mean time to data loss for different disk group configurations, allowing users to select an optimal configuration based on relative estimated mean times to data loss, which involves identifying operating characteristics of hard disks and using analytical models to evaluate data availability and configure disk groups for maximum redundancy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If redundant storage strategies are implemented to protect against data loss, then data reliability is improved, but system complexity increases due to multiple configuration options
Solution Approach 1:
The system automatically calculates estimated mean time to data loss for different configurations and selects the optimal configuration without requiring manual intervention or expert knowledge from the user
Solution Approach 2:
The system provides reliability statistics and estimated mean time to data loss as feedback to help users understand the effectiveness of different redundancy configurations, enabling informed decision-making
2Ease of operation
If reliability statistics are published for redundant storage systems, then evaluation of data redundancy strategies becomes easier, but measurement precision deteriorates because failure rates are difficult to determine experimentally
Solution Approach 1:
The system performs preliminary calculations of estimated mean time to data loss based on theoretical models and component failure rates before actual system deployment or configuration changes, allowing evaluation without waiting for experimental failure data
Solution Approach 2:
The system uses analytical models and simulation as an intermediary to bridge the gap between individual disk reliability statistics and system-level redundancy effectiveness, enabling evaluation without direct experimental measurement
3Reliability
If more disks are added to increase redundancy, then data protection is improved, but loss of time increases due to longer rebalance operations
Solution Approach 1:
The system optimizes configuration parameters such as the number of disk partners and mirroring strategy to achieve the best balance between data protection and rebalance time for the specific workload and hardware characteristics
Solution Approach 2:
The system allows dynamic adjustment of redundancy configuration based on changing requirements, enabling optimization of the trade-off between protection level and rebalance performance
Data Source
AI summary
This disclosure describes methods, systems and software that can be used to calculate the estimated mean time to data loss for a particular configuration of a disk group. For example, a system can be used to evaluate a plurality of configurations, and/or to select (and/or allow a user to select) an optimal configuration of the disk group, based, in some cases, on the relative estimated mean times to data loss of the various configurations. This can allow, if desired, the configuration of the disk group to minimize the likelihood of data loss in the disk group.