Data Storage Controller Internal Transformation Logic
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Solution Overview
Problem
Data storage devices face inefficiencies when accessing data in fixed-sized blocks, leading to increased resource consumption and traffic on data buses due to the need to transfer and process full blocks even when only partial data is being used.
Innovation Solution
Implementing a method and apparatus for data transformations within a data storage device that allow for efficient data processing by initiating block I/O operations and applying data transformations based on client requests or efficiency metrics, thereby optimizing data handling and reducing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If data is accessed in fixed-sized blocks, then data storage and retrieval can be simplified, but system resources are wasted when only partial data is needed
Solution Approach 1:
The patent segments data blocks into smaller units and enables selective access to only the required portions of data rather than transferring entire blocks. This allows the system to maintain simplified block-based storage architecture while enabling fine-grained data access to reduce resource consumption when only partial data is needed.
Solution Approach 2:
The patent implements partial data transfer by allowing clients to request and receive only the specific data blocks or segments they need rather than always transferring complete blocks. This partial action approach reduces unnecessary data transmission and processing while maintaining the simplicity of block-based data organization.
2Productivity
If full data blocks are transferred, then data bus bandwidth is utilized efficiently, but traffic on data buses increases unnecessarily
Solution Approach 1:
The patent introduces dynamic data transfer mechanisms that adapt to client needs in real-time. Instead of always transferring complete blocks, the system dynamically adjusts the transfer size based on actual data requirements, reducing unnecessary traffic on data buses while maintaining efficient utilization when full blocks are needed.
Solution Approach 2:
The patent changes the parameter of data transfer size from fixed block size to variable size based on client requests and efficiency metrics. This allows the system to optimize data bus traffic by transferring only the necessary amount of data while maintaining productivity through intelligent selection of when and how much data to transfer.
3Productivity
If data transformations are applied internally, then processing overhead is reduced, but device complexity increases
Solution Approach 1:
The patent implements self-service data transformation where the storage device automatically applies transformations based on client requests and efficiency metrics without requiring complex external processing. The storage controller autonomously determines when transformations are beneficial and applies them internally, reducing processing overhead while managing complexity through automated decision-making.
Solution Approach 2:
The patent applies data transformations preliminarily within the storage device before data is transferred to the client. By performing transformations internally in advance, the system reduces the processing burden on the client side and improves overall processing speed, while the complexity is managed through pre-configured transformation logic in the storage controller.
4Use of energy by moving object
If data is processed before transfer, then resource consumption is optimized, but the block I/O operation time increases
Solution Approach 1:
The patent implements periodic or conditional data transformations based on efficiency metrics rather than always transforming data before transfer. The storage controller evaluates specific conditions and applies transformations periodically or on-demand, optimizing resource consumption while minimizing the impact on block I/O operation time by avoiding unnecessary transformation steps.
Data Source
AI summary
Apparatuses, systems, and methods are disclosed for executing data transformations for a data storage device. A storage controller module controls a storage operation for a set of data within a data storage device. A transformation module determines to apply a data transformation to the set of data in response to a transformation indicator. A processing module applies the data transformation to the set of data internally on the data storage device prior to completing the storage operation.