Predicting Secure Erase Eligibility for Nonvolatile Memory Blocks
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Solution Overview
Problem
In composable data center infrastructures, nonvolatile memory blocks often retain sensitive data that can be compromised when reused, and existing methods struggle to securely erase data from these blocks, especially when they approach the end of their write-reliability lifecycle, making it difficult to determine their eligibility for recomposition without compromising stored data.
Innovation Solution
A system and method that include a management module to determine health parameters of nonvolatile memory blocks, calculate a failure index based on these parameters, and decide whether to securely erase the blocks by comparing the index to a threshold, thereby predicting their ability to be securely erased and reused in subsequent infrastructures without compromising data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If secure erase is performed on nonvolatile memory blocks, then data security is improved, but the reliability of erase operation deteriorates when blocks approach end of write-reliability lifecycle
Solution Approach 1:
The system performs preliminary assessment of memory block health parameters (program fail count, erase fail count, power-on hours, retired block count) before executing secure erase operations. By calculating a failure index in advance and comparing it against thresholds, the system predicts whether a block is likely to fail during erase, thereby preventing unreliable erase operations while still securing data on blocks that can be reliably erased.
2Productivity
If nonvolatile memory blocks are reused in composable infrastructure, then productivity is improved, but data security deteriorates due to retained sensitive data
Solution Approach 1:
The system continuously monitors health parameters of nonvolatile memory blocks and uses this feedback to dynamically determine eligibility for secure erase and reuse. The failure index calculation incorporates real-time data about program/erase failures, power-on hours, and retired block counts, creating a feedback loop that ensures only blocks with sufficient reliability are selected for secure erase and subsequent reuse in composable infrastructure.
3Loss of information
If health parameters are monitored and failure index calculated for all blocks, then data security is improved, but device complexity increases
Solution Approach 1:
The system monitors multiple health parameters (program fail count, erase fail count, power-on hours, retired block count) and transforms them into a single failure index value through a standardized calculation process. This parameter transformation approach simplifies decision-making by converting complex multi-dimensional health data into a single comparable metric that can be directly thresholded to determine secure erase eligibility.
Data Source
AI summary
Systems and methods for predicting whether a nonvolatile memory block is likely capable of being securely erased to be eligible for composing into another composable infrastructure are described. A management module receives a secure-erase command to erase at least one nonvolatile memory block, determines health parameters of the nonvolatile memory block, calculates a failure index based on the health parameters, and, based on the failure index, either securely erases the block of memory or retires the nonvolatile memory block.