Disk Refresh Metric Based on Track Quality
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Solution Overview
Problem
Data storage devices face challenges in maintaining data quality over time due to magnetic entropy and adjacent track interference, which can lead to data degradation and loss of readability, especially exacerbated by temperature and operational conditions.
Innovation Solution
A refresh metric is updated based on quality metrics measured during write operations, including position error signals, track squeeze, environmental conditions, and head operating states, to trigger timely refresh operations and prevent data degradation across adjacent data tracks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is written to adjacent tracks during normal write operations, then writing productivity is improved, but data quality degrades due to adjacent track interference and magnetic entropy
Solution Approach 1:
The system performs preliminary assessment of data quality metrics (position error signals, track squeeze, environmental conditions, head operating states) during write operations to predict future data degradation. Refresh operations are triggered proactively before data becomes unreadable, preventing degradation rather than reacting to it after the fact.
Solution Approach 2:
The system continuously monitors quality metrics during write operations and uses this feedback to dynamically update refresh metrics. This closed-loop feedback mechanism allows the system to adapt refresh timing based on actual data quality conditions, balancing writing productivity with data quality maintenance.
2Reliability
If refresh operations are performed frequently to maintain data quality, then data reliability is improved, but writing productivity decreases due to additional operational overhead
Solution Approach 1:
The refresh metric is dynamically updated based on real-time quality metrics from write operations. The system transitions from static, predetermined refresh schedules to dynamic, condition-based refresh timing. This allows refresh operations to be performed only when and where data quality degradation is predicted, optimizing the balance between reliability and productivity.
Solution Approach 2:
The system changes the parameter of refresh timing from fixed intervals to variable intervals based on measured quality metrics. By monitoring position error signals, track squeeze, environmental conditions, and head operating states, the system adjusts refresh timing parameters to match actual data quality conditions, reducing unnecessary refresh operations.
3Reliability
If quality metrics are monitored during write operations, then data quality is improved, but device complexity increases due to additional measurement and processing requirements
Solution Approach 1:
The system uses existing head components (read element, write coil, position sensing mechanisms) to gather multiple quality metrics simultaneously. The same hardware infrastructure that performs write operations also monitors quality metrics, eliminating the need for separate dedicated measurement devices and reducing overall system complexity.
Solution Approach 2:
The system uses its own operational data (position error signals, track squeeze measurements, environmental sensors, head state information) to assess data quality. Rather than requiring external monitoring systems, the storage device self-monitors its own write operation quality using metrics already generated during normal operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The solution effectively extends the lifespan of data tracks by proactively refreshing data before it becomes unreadable, reducing the impact of magnetic entropy and adjacent track interference, thereby maintaining data integrity and reliability.
Implementation Method 1
a head connected to a distal end of an actuator arm which is rotated about a pivot by a voice coil motor (VCM) to position the head radially over the disk
Implementation Method 2
Data is typically written to the disk by modulating a write current in an inductive coil (write coil) to record magnetic transitions onto the disk surface in a process referred to as saturation recording
Implementation Method 3
the magnetic transitions are sensed by a read element (e.g., a magneto-resistive element) and the resulting read signal demodulated by a suitable read channel
Implementation Method 4
Heat assisted magnetic recording (HAMR) is a recent development that improves the quality of written data by heating the disk surface during write operations in order to decrease the coercivity of the magnetic medium
Implementation Method 5
Microwave assisted magnetic recording (MAMR) is also a recent development that improves the quality of written data by using a spin torque oscillator (STO) to apply a high frequency auxiliary magnetic field to the media close to the resonant frequency of the magnetic grains
Data Source
AI summary
A data storage device is disclosed comprising a head actuated over a disk comprising a plurality of data tracks, including a first data track and a second data track. In connection with writing to at least part of the first data track, a quality metric is measured for at least part of the first data track. In connection with writing to at least part of the second data track, a refresh metric is updated based on the write to at least part of second data track and the quality metric measured for the first data track, and at least the first data track is refreshed based on the refresh metric.