Flash Memory Wear Leveling via Sampling Interval Segmentation
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Solution Overview
Problem
Conventional wear leveling methods for flash memory systems face challenges such as memory resource wastage, reliability issues due to data loss during power-offs, and incompatibility with new memory types, leading to uneven wear distribution and reduced system performance.
Innovation Solution
The method divides the memory life cycle into sampling intervals, independently tracking wear statistics to map heavily worn Physical Blocks to less frequently updated logical addresses, allowing for even erase/write operations without storing entire life cycle history, thus ensuring reliable wear leveling and power-off resilience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional wear leveling methods store entire life cycle history data for each Physical Block, then wear leveling accuracy is improved, but memory resource usage increases
Solution Approach 1:
The patent divides the memory life cycle into multiple sampling intervals and only tracks wear statistics within the current sampling interval rather than storing entire life cycle history. This segmentation approach reduces memory resource usage while maintaining sufficient wear leveling accuracy through periodic sampling.
2Stability of the object's composition
If wear leveling data is continuously updated without sampling intervals, then wear distribution evenness is improved, but reliability decreases due to power-off data loss
Solution Approach 1:
The patent implements periodic sampling intervals for wear statistics collection instead of continuous tracking. This periodic approach ensures that wear leveling data is captured at regular intervals, maintaining wear distribution evenness while providing natural checkpoints that improve reliability against power-off data loss.
3Stability of the object's composition
If conventional wear leveling methods track all erase/write operations continuously, then wear evenness is improved, but system complexity increases
Solution Approach 1:
The patent applies partial action by tracking wear statistics only for the current sampling interval rather than continuously monitoring all operations throughout the entire life cycle. This partial tracking approach reduces system complexity while maintaining sufficient wear evenness through periodic sampling and redistribution.
Data Source
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AI summary
The embodiment of the solution provides a method for performing wear leveling in a memory. The method includes: dividing the lifecycle of the memory which includes more than one physical blocks into at least one sampling interval; for each sampling interval, getting the first physical block by taking statistics of the degree of the wear leveling of each physical block in the memory in the current sampling interval; getting the second physical block by taking statistics of the updating times of each logical address in the current sampling interval; exchanging the logical addresses and data of the first physical block and the second physical block. The embodiment of the solution also provides an apparatus corresponding the method.