Storage System Parity Data Classification for SSD Endurance
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Solution Overview
Problem
Current RAID systems face issues with parity inconsistency, known as the RAID write hole, which leads to data corruption due to interrupted write operations, and result in reduced endurance and performance, especially in SSDs, due to frequent garbage collection and fragmentation.
Innovation Solution
Implementing a classification-based approach to distribute user data, parity data, and log data across storage devices, using multiple streams for efficient data placement, where parity and log data are written more frequently and stored separately to prevent fragmentation and optimize SSD performance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If parity data is written frequently to maintain redundancy, then data reliability is improved, but write amplification increases and SSD endurance deteriorates
Solution Approach 1:
The patent segments data into different types (user data, parity data, log data) and writes them to different storage regions within the same storage device. This segmentation allows parity data to be written frequently without affecting the lifespan of the storage device, as each region can be optimized independently for its specific write patterns.
Solution Approach 2:
The patent applies local quality by creating different storage regions with different characteristics - one region for user data, another for parity data, and another for log data. Each region is optimized for its specific purposes, allowing parity data to be written frequently in its dedicated region without degrading the overall endurance of the storage device.
2Reliability
If frequent garbage collection is performed to maintain SSD performance, then data integrity is improved, but productivity decreases due to reduced throughput
Solution Approach 1:
By segmenting storage into distinct regions for different data types, the system can perform garbage collection more efficiently. The segregation of hot write regions (parity and log data) from user data regions allows the system to maintain data integrity through targeted garbage collection without impacting overall throughput.
Solution Approach 2:
The patent implements preliminary action by writing log data before parity data, ensuring that write operations are properly recorded and accounted for before the actual data is written. This preliminary logging action prevents data integrity issues and reduces the need for extensive garbage collection operations later.
3Device complexity
If data is written without classification, then device complexity is reduced, but fragmentation increases and performance deteriorates
Solution Approach 1:
The patent introduces segmentation by dividing the storage device into multiple regions, each dedicated to specific data types (user data, parity data, log data). This segmentation is implemented through a classification mechanism that directs different data types to appropriate regions, reducing fragmentation and improving performance without excessive complexity.
Solution Approach 2:
The patent applies local quality by creating specialized storage regions with different characteristics optimized for their specific purposes. Each region has tailored properties that match the write patterns and performance requirements of the data types stored there, thereby improving overall system performance.
4Loss of energy
If multiple data streams are used for data placement, then write amplification is reduced, but device complexity increases
Solution Approach 1:
The patent uses segmentation to create multiple data streams for writing different data types to different regions. This segmentation approach reduces write amplification by ensuring that each data type follows its own optimized write path, avoiding unnecessary data movement and rewrites.
Solution Approach 2:
The patent introduces an intermediary classification mechanism that acts as a mediator between the write operations and the storage regions. This intermediary layer directs data to the appropriate region based on its type, simplifying the data placement process and reducing the complexity of managing multiple streams.
Data Source
AI summary
According to various aspects, a storage system is provided, the storage system including a multiplicity of storage devices, and one or more processors configured to store user data on the multiplicity of storage devices, the stored user data being distributed among the multiplicity of storage devices together with redundancy data and with log data; generate a classification associated with the redundancy data and the log data to provide classified redundancy data and classified log data, and write the classified redundancy data and the classified log data on the respective storage device of the multiplicity of storage devices according to the classification associated therewith.