NVM Controller Self-Trimming to Limit Write Amplification
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Solution Overview
Problem
Non-volatile memory (NVM) devices, such as NAND storage devices, face challenges in efficiently storing and removing time-sensitive data due to limited write and erase cycles, leading to potential storage delays and data loss, especially in high-definition video recording applications like dashcams and IoT devices.
Innovation Solution
A data storage controller is configured to store time-sensitive data with time-based parameters, identifying and trimming data that exceeds a predetermined age threshold, thereby managing the storage and removal of obsolete data within NVM devices, allowing for efficient reuse of memory blocks without waiting for the device to be full.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If data is continuously stored in NVM devices without trimming, then data retention is maintained, but storage space is wasted and write amplification increases
Solution Approach 1:
The system performs preliminary trimming actions by proactively identifying and removing expired data before storage space is depleted. The controller continuously monitors data age using timestamps and initiates trimming operations in advance, preventing storage exhaustion and reducing write amplification before they become critical issues.
Solution Approach 2:
The NVM device performs self-trimming operations autonomously without requiring external host intervention. The controller independently manages data lifecycle by automatically detecting expired data through timestamp comparison and executing trim operations, making the system self-sufficient in maintaining storage efficiency.
2Device complexity
If waiting for NVM device to be full before trimming, then comprehensive data management is achieved, but storage delays and data loss occur
Solution Approach 1:
The system performs preliminary trimming actions by proactively identifying and removing expired data before storage space is depleted. The controller continuously monitors data age using timestamps and initiates trimming operations in advance, preventing storage exhaustion and reducing write amplification before they become critical issues.
Solution Approach 2:
The controller implements periodic trimming operations by continuously monitoring data age and performing trim operations at regular intervals or when thresholds are reached. This periodic action ensures comprehensive data management while preventing storage delays, as the system regularly cleans up expired data rather than waiting for the device to fill up.
3Productivity
If frequent write and erase operations are performed, then data turnover is managed, but NVM device lifespan is reduced
Solution Approach 1:
The system extracts only the expired data portions for trimming operations rather than performing full block erasures. By using timestamp-based identification and selective trimming, the system removes only necessary data while preserving valid data, significantly reducing the number of erase operations and extending NVM device lifespan while maintaining high data turnover capability.
Solution Approach 2:
The system changes the operational parameter from full block erasure to selective data trimming based on timestamp parameters. This parameter change allows the controller to target only expired data for removal, reducing write amplification and erase cycle frequency, thereby extending device lifespan while maintaining efficient data turnover through precise age-based identification.
Data Source
AI summary
The present disclosure describes technologies and techniques for use with a data storage controller (such as a non-volatile memory (NVM) controller) to implement self-trimming of media data. In illustrative examples, an NVM controller stores a stream of video data in a NAND storage device, such as video obtained by a security camera. The controller also stores time stamps corresponding to portions of the video data. The controller then periodically (or during idle times) scans the stored information to identify video data that has exceeded a maximum data lifetime, such as data older than one week. Such data is deemed to be old/expired and is trimmed by the controller (by, e.g., marking corresponding entries in an allocation table as deleted or invalid). In this manner, the controller performs self-trimming of older video data to, for example, limit write amplification. NVMe examples are provided.