Computational Storage Processing for Compressed Encrypted Data
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Solution Overview
Problem
Computational storage devices face challenges in performing operations on data that has been modified, such as compression and encryption, as they cannot restore the data to its original form for local processing, leading to inefficiencies in data retrieval and processing.
Innovation Solution
The method involves dividing data into portions, modifying them individually with compression and encryption, and then sending these modified portions to a storage device where they can be restored and processed, allowing for local operations like filtering and scanning to be performed efficiently without reducing bandwidth or security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If data is compressed and encrypted before storage, then bandwidth efficiency and security are improved, but the storage device cannot perform local processing operations on the data
Solution Approach 1:
The patent divides data into multiple portions or chunks before compression and encryption. Each portion is independently processed and stored. This segmentation allows the storage device to restore and process individual portions locally without needing to decrypt/compress entire datasets, thus enabling local processing while maintaining compression and encryption benefits.
Solution Approach 2:
The patent performs preliminary compression and encryption on data portions before storage, but maintains the capability to restore them to original form. This preliminary action prepares data for efficient storage and transmission while the restoration capability enables subsequent local processing operations when needed.
2Productivity
If data is restored to original form for local processing, then processing efficiency is improved, but data security and bandwidth efficiency are reduced
Solution Approach 1:
By segmenting data into portions, the system can restore only the specific portions needed for processing rather than entire datasets. This selective restoration maintains security and bandwidth efficiency while enabling processing efficiency for the necessary data segments.
Solution Approach 2:
The patent applies partial restoration - restoring data portions to original form only when and only to the extent needed for specific processing operations. This partial action achieves processing efficiency without the full cost of restoring entire datasets, thus maintaining security and bandwidth efficiency.
3Reliability
If entire datasets are transferred for processing, then complete data availability is ensured, but transmission time and bandwidth consumption increase
Solution Approach 1:
The patent extracts or retrieves only the specific data portions needed for processing from storage, rather than transferring entire datasets. This extraction approach ensures that the necessary data is available for processing while minimizing transmission time and bandwidth consumption.
Solution Approach 2:
Segmentation of data into portions allows the system to transfer only the relevant segments needed for specific operations. This selective transfer maintains data availability for required operations while significantly reducing transmission time and bandwidth usage compared to moving entire datasets.
Data Source
AI summary
A method for computational storage may include receiving, at a storage device, a modified version of a portion of data, generating, at the storage device, a restored portion of data from the modified version of the portion of data, and performing, at the storage device, an operation on the restored portion of data. The method may further include receiving, at the storage device, a request to perform the operation on the portion of data. The generating may include decompressing the modified version of the portion of data. The generating may include decrypting the modified version of the portion of data. The method may further include sending, from the storage device, a result of the operation on the restored portion of data. The operation may include a filtering operation. The operation may include a scanning operation. The method may further include dividing data to generate the portion of data.