Storage Controller UBER to MTBF Event Conversion
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data storage devices face challenges in meeting reliability requirements due to the increasing size of data storage, where block level errors significantly impact uncorrectable bit error rates (UBER) and mean time between failure (MTBF) rates, leading to inefficient design resources being dedicated to rare events.
Innovation Solution
The storage device controller converts UBER-type events to MTBF (FFR) events by detecting block failures and entering an assertion mode, updating the device to reflect these failures as MTBF events, thereby avoiding an increase in UBER counts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If block level errors are counted as UBER events, then reliability measurement becomes more stringent, but design resources are inefficiently consumed on rare events
Solution Approach 1:
The patent segments error counting by introducing separate counters for UBER events and MTBF events. Block level errors are segmented into a distinct category counted by a separate MTBF counter, while only sector level errors increment the UBER counter. This segmentation allows independent tracking and evaluation of different error types, resolving the contradiction by enabling stringent reliability measurement for UBER while preventing inefficient resource consumption from counting all errors equally.
Solution Approach 2:
The patent introduces an intermediary classification mechanism that determines whether an error is a sector level error or a block level error. This intermediary classification layer (implemented through error detection logic and counter selection) mediates between the raw error event and the reliability metrics, directing different error types to appropriate counters. This resolves the contradiction by enabling differentiated handling: UBER counting remains stringent for sector errors while block errors are routed to MTBF tracking, preserving design resource efficiency.
2Volume of stationary object
If storage device size increases, then storage capacity improves, but meeting UBER requirements becomes increasingly difficult
Solution Approach 1:
The patent segments the storage device into sectors and blocks, with different error handling policies for each level. By segmenting error counting into sector-level UBER events and block-level MTBF events, the system can accommodate larger storage capacities without being penalized for block level errors that do not affect individual sector integrity. This segmentation allows storage capacity to scale while maintaining UBER compliance for critical sector operations.
Solution Approach 2:
The patent applies different quality standards to different parts of the storage device: sector level errors affect UBER (stringent local quality requirement), while block level errors affect MTBF (less stringent local quality requirement). This local quality differentiation allows the overall device to achieve larger capacity by tolerating block level variations, while critical sector-level data integrity maintains high quality standards for UBER compliance.
Data Source
AI summary
A method and apparatus for enhancing reliability of a data storage device. The storage device controller is configured to convert a typical UBER-type event to an MTBF (FFR) event by converting a data error event into a drive functional failure. In this context, the converted error is not counted as an UBER type event for purposes of determining the reliability of the storage device.