Selective Data Processing for Storage Efficiency
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Solution Overview
Problem
Existing data storage systems lack an efficient mechanism for selectively processing data before storage, which can lead to inefficiencies and increased complexity in managing data across client devices and data storage servers.
Innovation Solution
A client device and data storage server system that allows for selective data processing by determining storage locations and applying specific data operations based on storage location configuration information, enabling differential processing of data elements before storage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is stored without selective processing, then storage operation is simple and fast, but data management efficiency and flexibility are reduced
Solution Approach 1:
The patent applies local quality by enabling different data processing operations to be applied to different data elements based on their storage location configuration. Each data element can have its processing requirements independently configured, allowing selective processing of only those data elements that require it, thereby improving storage efficiency without unnecessarily increasing system complexity for all data.
Solution Approach 2:
The patent segments the data processing operation by dividing data elements into different subsets based on their storage location configuration. The processing circuitry identifies which data elements require processing and applies operations only to those, separating the processing function from the general storage function and reducing overall system complexity while maintaining efficiency.
2Reliability
If all data elements are processed before storage, then data consistency and security are improved, but processing time and resource consumption increase
Solution Approach 1:
The patent applies partial action by processing only those data elements that require processing based on their storage location configuration, rather than processing all data elements. This selective processing approach maintains data consistency and security for data that needs it while reducing processing time and resource consumption for data that does not require processing.
Solution Approach 2:
The patent implements preliminary action by determining the storage location configuration for each data element before processing. The processing circuitry uses this pre-determined configuration information to identify which data elements need processing operations applied, allowing efficient selective processing without time-consuming analysis during the processing stage itself.
3Adaptability or versatility
If selective data processing is implemented, then storage efficiency and flexibility are improved, but system complexity increases
Solution Approach 1:
The patent applies universality by designing a processing circuitry that can handle multiple data elements with different processing requirements through a single unified system. The circuitry uses storage location configuration information to dynamically determine which data elements require processing, allowing the same system to efficiently handle both processed and unprocessed data without requiring separate systems for different processing scenarios.
Data Source
AI summary
A client device for storing a data set in a database is provided. The data set includes a plurality of initial data elements. The client device is configured to determine a storage location of the database for each initial data element and to obtain storage location configuration information based on the storage location. The client device is further configured to process, based on the storage location configuration information, each initial data element of a first subset of the plurality of initial data elements into a processed data element using one or more data processing operations and to transmit a modified data set to a data storage server for storing the modified data set in the database, wherein the modified data set comprises the processed data elements in the first subset and unprocessed initial data elements in a second subset which is complementary to the first subset.


